[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-dd12fd1e59c3dcb8-rethinking-aleatoric-uncertainty-in-llms-via-inter-summary":3,"summaries-facets-categories":103,"summary-related-dd12fd1e59c3dcb8-rethinking-aleatoric-uncertainty-in-llms-via-inter-summary":7447},{"id":4,"title":5,"ai":6,"body":13,"categories":69,"created_at":71,"date_modified":71,"description":63,"extension":72,"faq":71,"featured":73,"kicker_label":71,"meta":74,"navigation":87,"path":88,"published_at":89,"question":71,"scraped_at":89,"seo":90,"sitemap":91,"source_id":92,"source_name":93,"source_type":94,"source_url":79,"stem":95,"tags":96,"thumbnail_url":71,"tldr":100,"tweet":71,"unknown_tags":101,"__hash__":102},"summaries\u002Fsummaries\u002Fdd12fd1e59c3dcb8-rethinking-aleatoric-uncertainty-in-llms-via-inter-summary.md","Rethinking Aleatoric Uncertainty in LLMs via Interpretations",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","google\u002Fgemini-3.1-flash-lite",4053,617,3684,0.00193875,{"type":14,"value":15,"toc":62},"minimark",[16,21,25,29,32,36,39],[17,18,20],"h2",{"id":19},"moving-beyond-answer-based-uncertainty","Moving Beyond Answer-Based Uncertainty",[22,23,24],"p",{},"Traditional approaches to measuring aleatoric uncertainty in Large Language Models (LLMs) often treat ambiguity as a simple lack of consensus among possible output tokens. This paper challenges that view, arguing that when a prompt is inherently ambiguous, the model is not merely 'guessing' between random tokens. Instead, it is navigating multiple, internally consistent interpretations of the input. By focusing solely on the variance of final answers, current methods fail to capture the underlying semantic structure of the ambiguity.",[17,26,28],{"id":27},"the-interpretation-based-framework","The Interpretation-Based Framework",[22,30,31],{},"The authors propose a new paradigm for uncertainty estimation that shifts the focus from the final generated answer to the 'interpretations' that lead to those answers. The core insight is that ambiguity is often resolved at the latent or reasoning stage before the final output is produced. By decomposing the generation process into distinct interpretative paths, developers can better quantify uncertainty. This approach treats the model's internal state as a distribution over potential world-views or task interpretations, rather than a distribution over a flat space of possible tokens. This method provides a more robust signal for when a model is genuinely confused versus when it is simply choosing between equally valid, distinct ways of framing a problem.",[17,33,35],{"id":34},"practical-implications-for-ai-engineering","Practical Implications for AI Engineering",[22,37,38],{},"This shift has significant consequences for how we build reliable AI systems. If we treat uncertainty as a function of multiple valid interpretations, we can move away from simple confidence scores (which are often poorly calibrated) toward 'interpretation-aware' systems. This allows for:",[40,41,42,50,56],"ul",{},[43,44,45,49],"li",{},[46,47,48],"strong",{},"Better User Feedback:"," Instead of saying 'I am 60% sure,' a model can present the user with the different interpretations it has identified, allowing the user to clarify their intent.",[43,51,52,55],{},[46,53,54],{},"Improved Calibration:"," By accounting for the semantic diversity of interpretations, uncertainty metrics become more representative of the model's actual reasoning process.",[43,57,58,61],{},[46,59,60],{},"Reduced Hallucination:"," By identifying when a prompt supports multiple, conflicting interpretations, systems can trigger a 'clarification' workflow rather than forcing a single, potentially incorrect, answer.",{"title":63,"searchDepth":64,"depth":64,"links":65},"",2,[66,67,68],{"id":19,"depth":64,"text":20},{"id":27,"depth":64,"text":28},{"id":34,"depth":64,"text":35},[70],"AI & LLMs",null,"md",false,{"content_references":75,"triage":81},[76],{"type":77,"title":78,"url":79,"context":80},"paper","From Answers to Interpretations: Rethinking Ambiguity-Induced Aleatoric Uncertainty Estimation in LLMs","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.04543","cited",{"relevance":82,"novelty":83,"quality":83,"actionability":84,"composite":85,"reasoning":86},5,4,3,4.15,"Category: AI & LLMs. The article presents a novel framework for understanding uncertainty in LLMs, addressing a specific pain point for AI developers regarding model reliability. It offers practical implications for AI engineering, such as improved user feedback mechanisms, though it lacks detailed actionable steps for implementation.",true,"\u002Fsummaries\u002Fdd12fd1e59c3dcb8-rethinking-aleatoric-uncertainty-in-llms-via-inter-summary","2026-09-08 03:10:00",{"title":5,"description":63},{"loc":88},"dd12fd1e59c3dcb8","arXiv cs.AI","article","summaries\u002Fdd12fd1e59c3dcb8-rethinking-aleatoric-uncertainty-in-llms-via-inter-summary",[97,98,99],"llm","research","machine-learning","The paper argues that LLM uncertainty in ambiguous tasks stems from multiple valid interpretations rather than simple randomness, proposing a shift from answer-based to interpretation-based uncertainty estimation.",[],"iJG5JXijGoB3gKoCd0dUvGliSa-XsYwYRU9U9ohE-s0",[104,106,109,111,114,116,119,122,124,126,128,130,133,136,138,140,142,144,147,149,151,153,155,158,160,162,164,166,168,170,172,174,176,178,180,182,184,186,188,190,192,194,196,198,200,202,204,206,208,210,213,215,217,219,221,223,225,227,229,231,233,235,237,239,241,244,246,248,250,252,254,256,258,260,262,264,266,268,270,272,274,276,278,280,282,285,287,289,291,293,295,297,299,301,303,305,307,309,311,313,315,317,320,322,324,326,328,330,332,334,336,338,340,342,344,346,348,350,352,354,356,358,360,362,364,366,368,370,372,374,376,378,380,382,384,386,388,391,393,395,397,399,401,403,405,407,409,411,414,416,418,420,422,424,426,428,430,432,434,436,438,440,442,444,447,449,451,453,455,457,459,461,463,465,467,469,472,474,476,478,480,482,484,486,488,490,492,494,496,498,500,502,504,506,508,510,512,514,516,518,520,522,524,526,528,530,532,534,536,538,541,543,545,548,550,552,554,556,558,560,562,564,566,568,570,572,574,576,578,580,582,584,587,589,591,593,595,597,599,601,603,605,607,609,611,614,616,618,620,622,624,626,628,630,632,634,636,638,640,642,644,646,648,650,652,654,656,658,660,662,664,666,668,670,672,674,676,678,680,682,684,686,688,690,692,694,696,698,700,702,704,706,708,710,712,714,716,718,720,722,724,726,728,730,732,734,736,738,740,742,744,746,748,750,752,754,756,758,760,762,764,766,768,770,772,774,776,778,780,782,784,786,788,790,792,794,796,798,800,802,804,806,808,810,812,814,816,818,820,822,824,826,828,830,832,834,836,838,840,842,844,846,848,850,852,854,856,858,860,862,864,866,868,870,872,874,876,878,880,882,884,886,888,890,892,894,896,898,900,902,904,906,908,910,913,915,917,919,921,924,926,928,930,932,934,936,938,940,942,944,946,948,950,953,955,957,959,961,963,965,967,969,971,973,975,977,979,981,983,985,987,989,991,993,995,997,999,1001,1003,1005,1007,1009,1011,1013,1015,1017,1019,1021,1023,1025,1027,1029,1031,1033,1035,1037,1039,1041,1043,1045,1047,1049,1051,1053,1055,1057,1059,1061,1063,1065,1067,1069,1071,1073,1075,1077,1079,1081,1083,1085,1087,1089,1091,1093,1095,1097,1099,1101,1103,1105,1107,1109,1111,1113,1115,1117,1119,1121,1123,1125,1127,1129,1131,1133,1135,1137,1139,1141,1143,1145,1147,1149,1151,1153,1155,1157,1159,1161,1163,1165,1167,1169,1171,1173,1175,1177,1179,1181,1183,1185,1187,1189,1191,1193,1195,1197,1199,1201,1203,1205,1207,1209,1211,1213,1215,1217,1219,1221,1223,1225,1227,1229,1231,1233,1235,1237,1239,1241,1243,1245,1247,1249,1251,1253,1255,1257,1259,1261,1263,1265,1267,1269,1271,1273,1275,1277,1279,1281,1283,1285,1287,1289,1291,1294,1296,1298,1300,1302,1304,1306,1308,1310,1312,1314,1316,1318,1320,1322,1324,1326,1328,1330,1332,1334,1336,1338,1340,1342,1344,1346,1348,1350,1352,1354,1356,1358,1360,1362,1364,1366,1368,1370,1372,1374,1376,1378,1380,1382,1384,1386,1388,1390,1392,1394,1396,1398,1400,1402,1404,1406,1408,1410,1412,1414,1416,1418,1420,1422,1424,1426,1428,1430,1432,1434,1436,1438,1440,1442,1444,1446,1448,1450,1452,1454,1456,1458,1460,1462,1464,1466,1468,1470,1472,1474,1476,1478,1480,1482,1484,1486,1488,1490,1492,1494,1496,1498,1500,1502,1504,1506,1508,1511,1513,1515,1517,1519,1521,1523,1525,1527,1529,1531,1533,1535,1537,1539,1541,1543,1545,1547,1549,1551,1553,1555,1557,1559,1561,1563,1565,1567,1569,1571,1573,1575,1577,1579,1581,1583,1585,1587,1589,1591,1593,1595,1597,1599,1601,1603,1605,1607,1609,1611,1613,1615,1617,1619,1621,1623,1625,1627,1629,1631,1633,1635,1637,1639,1641,1643,1645,1647,1649,1651,1653,1655,1657,1659,1661,1663,1666,1668,1670,1672,1674,1676,1678,1680,1682,1684,1686,1688,1690,1692,1694,1696,1698,1700,1702,1704,1706,1708,1710,1712,1714,1716,1718,1720,1722,1724,1726,1728,1730,1732,1734,1736,1738,1740,1742,1744,1746,1748,1750,1752,1754,1756,1758,1760,1762,1764,1766,1768,1770,1772,1774,1776,1778,1780,1782,1784,1786,1788,1790,1792,1794,1796,1798,1800,1802,1804,1806,1808,1810,1812,1814,1816,1818,1820,1822,1824,1826,1828,1830,1833,1835,1837,1839,1841,1843,1845,1847,1849,1851,1853,1855,1857,1859,1861,1863,1865,1867,1869,1871,1873,1875,1877,1879,1881,1883,1885,1887,1889,1891,1893,1895,1897,1899,1902,1904,1906,1908,1910,1912,1914,1916,1918,1920,1922,1924,1926,1928,1930,1932,1934,1936,1938,1940,1942,1944,1946,1948,1950,1952,1954,1956,1958,1960,1962,1964,1966,1968,1970,1972,1974,1976,1978,1980,1982,1984,1986,1988,1990,1992,1994,1996,1998,2000,2002,2004,2006,2008,2010,2012,2014,2016,2018,2020,2022,2024,2026,2028,2030,2032,2034,2036,2038,2040,2042,2044,2046,2048,2050,2052,2054,2056,2058,2060,2062,2064,2066,2068,2070,2072,2074,2076,2078,2080,2082,2084,2086,2088,2090,2092,2094,2096,2098,2100,2102,2104,2106,2108,2110,2112,2114,2116,2118,2120,2122,2124,2126,2128,2130,2132,2134,2136,2138,2140,2142,2144,2146,2148,2150,2152,2154,2156,2158,2160,2162,2164,2166,2168,2170,2172,2174,2176,2178,2180,2182,2184,2186,2188,2190,2192,2194,2196,2198,2200,2202,2204,2206,2208,2210,2212,2214,2216,2218,2220,2222,2224,2226,2228,2230,2232,2234,2236,2238,2240,2242,2244,2246,2248,2250,2252,2254,2256,2258,2260,2262,2264,2266,2268,2270,2272,2274,2276,2278,2280,2282,2284,2286,2288,2290,2292,2294,2296,2298,2300,2302,2304,2306,2308,2310,2312,2314,2316,2318,2320,2322,2324,2326,2328,2330,2332,2334,2336,2338,2340,2342,2344,2346,2348,2350,2352,2354,2356,2358,2360,2362,2364,2366,2368,2370,2372,2374,2376,2378,2381,2383,2385,2387,2389,2391,2393,2395,2397,2399,2401,2403,2405,2407,2409,2411,2413,2415,2417,2419,2421,2423,2425,2427,2429,2431,2433,2435,2437,2439,2441,2443,2445,2447,2449,2451,2453,2455,2457,2459,2461,2463,2465,2467,2469,2471,2473,2475,2478,2480,2482,2484,2486,2488,2490,2492,2494,2496,2498,2500,2502,2504,2506,2508,2510,2512,2514,2516,2518,2520,2522,2524,2526,2528,2530,2532,2534,2536,2538,2540,2542,2544,2546,2548,2550,2552,2554,2556,2558,2560,2562,2564,2566,2568,2570,2572,2574,2576,2578,2580,2582,2584,2586,2588,2590,2592,2594,2596,2598,2600,2602,2605,2607,2609,2611,2613,2615,2617,2619,2621,2623,2625,2627,2629,2631,2633,2635,2637,2639,2641,2643,2645,2647,2649,2652,2654,2656,2658,2660,2662,2664,2666,2668,2670,2672,2674,2676,2678,2680,2682,2684,2686,2688,2690,2692,2694,2696,2698,2700,2702,2704,2706,2708,2710,2712,2714,2716,2718,2720,2722,2724,2726,2728,2730,2732,2734,2736,2738,2740,2742,2744,2746,2748,2750,2752,2754,2756,2758,2760,2762,2764,2766,2768,2770,2772,2774,2776,2778,2780,2782,2784,2786,2788,2790,2792,2794,2796,2798,2800,2802,2804,2806,2808,2810,2812,2814,2816,2818,2820,2822,2824,2826,2828,2830,2832,2834,2836,2838,2840,2842,2844,2846,2848,2850,2852,2854,2856,2858,2860,2862,2864,2866,2868,2870,2872,2874,2876,2878,2880,2882,2884,2886,2888,2890,2892,2894,2896,2898,2900,2902,2904,2906,2908,2910,2912,2914,2916,2918,2920,2922,2924,2926,2928,2930,2932,2934,2936,2938,2940,2942,2944,2946,2948,2950,2952,2954,2956,2958,2960,2962,2964,2966,2968,2970,2972,2974,2976,2978,2980,2982,2984,2986,2988,2990,2992,2994,2996,2998,3000,3002,3004,3006,3008,3010,3012,3014,3016,3018,3020,3022,3024,3026,3028,3030,3032,3034,3036,3038,3040,3042,3044,3046,3048,3050,3052,3054,3056,3058,3060,3062,3064,3066,3068,3070,3072,3074,3076,3078,3080,3082,3084,3086,3088,3090,3092,3094,3096,3098,3100,3102,3104,3106,3108,3110,3112,3114,3116,3118,3120,3122,3124,3126,3128,3130,3132,3134,3136,3138,3140,3142,3144,3146,3148,3150,3152,3154,3156,3158,3160,3162,3164,3166,3168,3170,3172,3174,3176,3178,3180,3182,3184,3186,3188,3190,3192,3194,3196,3198,3200,3202,3204,3206,3208,3210,3212,3214,3216,3218,3220,3222,3224,3226,3228,3230,3232,3234,3236,3238,3240,3242,3244,3246,3248,3250,3252,3254,3256,3258,3260,3262,3264,3266,3268,3270,3272,3274,3276,3278,3280,3282,3284,3286,3288,3290,3292,3294,3296,3298,3300,3302,3304,3306,3308,3310,3312,3314,3316,3318,3320,3322,3324,3326,3328,3331,3333,3335,3337,3339,3341,3343,3345,3347,3349,3351,3353,3355,3357,3359,3361,3363,3365,3367,3369,3371,3373,3375,3377,3379,3381,3383,3385,3387,3389,3391,3393,3395,3397,3399,3401,3403,3405,3407,3409,3411,3413,3415,3417,3419,3421,3423,3425,3427,3429,3431,3433,3435,3437,3439,3441,3443,3445,3447,3449,3451,3453,3455,3457,3459,3461,3464,3466,3468,3470,3472,3474,3476,3478,3480,3482,3484,3486,3488,3490,3492,3494,3496,3498,3500,3502,3504,3506,3508,3510,3512,3514,3516,3518,3520,3522,3524,3526,3528,3530,3532,3534,3536,3538,3540,3542,3544,3546,3548,3550,3552,3554,3556,3558,3560,3562,3564,3566,3568,3570,3572,3574,3576,3578,3580,3582,3584,3586,3588,3590,3592,3594,3596,3598,3600,3602,3604,3606,3608,3610,3612,3614,3616,3618,3620,3622,3624,3626,3628,3630,3632,3634,3636,3638,3640,3642,3644,3646,3648,3650,3652,3654,3656,3658,3660,3662,3664,3666,3668,3670,3672,3674,3676,3678,3680,3682,3684,3686,3688,3690,3692,3694,3696,3698,3700,3702,3704,3706,3708,3710,3712,3714,3716,3718,3720,3722,3724,3726,3728,3730,3732,3734,3736,3738,3740,3742,3744,3746,3748,3750,3752,3754,3756,3758,3760,3762,3764,3766,3768,3770,3772,3774,3776,3778,3780,3782,3784,3786,3788,3790,3792,3794,3796,3798,3800,3802,3804,3806,3808,3810,3812,3814,3816,3818,3820,3822,3824,3826,3828,3830,3832,3834,3836,3838,3840,3842,3844,3846,3848,3850,3852,3854,3856,3858,3860,3862,3864,3866,3868,3870,3872,3874,3876,3878,3880,3882,3884,3886,3888,3890,3892,3894,3896,3898,3900,3902,3904,3906,3908,3910,3912,3914,3916,3918,3920,3922,3924,3926,3928,3930,3932,3934,3936,3938,3940,3942,3944,3946,3948,3950,3952,3954,3956,3958,3960,3962,3964,3966,3968,3970,3972,3974,3976,3978,3980,3982,3984,3986,3988,3990,3992,3994,3996,3998,4000,4002,4004,4006,4008,4010,4012,4014,4016,4018,4020,4022,4024,4026,4028,4030,4032,4034,4036,4038,4040,4042,4044,4046,4048,4050,4052,4054,4056,4058,4060,4062,4064,4066,4068,4070,4072,4074,4076,4078,4080,4082,4084,4086,4088,4090,4092,4094,4096,4098,4100,4102,4104,4106,4108,4110,4112,4114,4116,4118,4120,4122,4124,4126,4128,4130,4132,4134,4136,4138,4140,4142,4144,4146,4148,4150,4152,4154,4156,4158,4160,4162,4164,4166,4168,4170,4172,4174,4176,4178,4180,4182,4184,4186,4188,4190,4192,4194,4196,4198,4200,4202,4204,4206,4208,4210,4212,4214,4216,4218,4220,4222,4224,4226,4228,4230,4232,4234,4236,4238,4240,4242,4244,4246,4248,4250,4252,4254,4256,4258,4260,4262,4264,4266,4268,4270,4272,4274,4276,4278,4280,4282,4284,4286,4288,4290,4292,4294,4296,4298,4300,4302,4304,4306,4308,4310,4312,4314,4316,4318,4320,4322,4324,4326,4328,4330,4332,4334,4336,4338,4340,4342,4344,4346,4348,4350,4352,4354,4356,4358,4360,4362,4364,4366,4368,4370,4372,4374,4376,4378,4380,4382,4384,4386,4388,4390,4392,4394,4396,4398,4400,4402,4404,4406,4408,4410,4412,4414,4416,4418,4420,4422,4424,4426,4428,4430,4432,4434,4436,4438,4440,4442,4444,4446,4448,4450,4452,4454,4456,4458,4460,4462,4464,4466,4468,4470,4472,4474,4476,4478,4480,4482,4484,4486,4488,4490,4492,4494,4496,4498,4500,4502,4504,4506,4508,4510,4512,4514,4516,4518,4520,4522,4524,4526,4528,4530,4532,4534,4536,4538,4540,4542,4544,4546,4548,4550,4552,4554,4556,4558,4560,4562,4564,4566,4568,4570,4572,4574,4576,4578,4580,4582,4584,4586,4588,4590,4592,4594,4596,4598,4600,4602,4604,4606,4608,4610,4612,4614,4616,4618,4620,4622,4624,4626,4628,4630,4632,4634,4636,4638,4640,4642,4644,4646,4648,4650,4652,4654,4656,4658,4660,4662,4664,4666,4668,4670,4672,4674,4676,4678,4680,4682,4684,4686,4688,4690,4692,4694,4696,4698,4700,4702,4704,4706,4708,4710,4712,4714,4716,4718,4720,4722,4724,4726,4728,4730,4732,4734,4736,4738,4740,4742,4744,4746,4748,4750,4752,4754,4756,4758,4760,4762,4764,4766,4768,4770,4772,4774,4776,4778,4780,4782,4784,4786,4788,4790,4792,4794,4796,4798,4800,4802,4804,4806,4808,4810,4812,4814,4816,4818,4820,4822,4824,4826,4828,4830,4832,4834,4836,4838,4840,4842,4844,4846,4848,4850,4853,4855,4857,4859,4861,4863,4865,4867,4869,4871,4873,4875,4877,4879,4881,4883,4885,4887,4889,4891,4893,4895,4897,4899,4901,4903,4905,4907,4909,4911,4913,4915,4917,4919,4921,4923,4925,4927,4929,4931,4933,4935,4937,4939,4941,4943,4945,4947,4949,4951,4953,4955,4957,4959,4961,4963,4965,4967,4969,4971,4973,4975,4977,4979,4981,4983,4985,4987,4989,4991,4993,4995,4997,4999,5001,5003,5005,5007,5009,5011,5013,5015,5017,5019,5021,5023,5025,5027,5029,5031,5033,5035,5037,5039,5041,5043,5045,5047,5049,5051,5053,5055,5057,5059,5061,5063,5065,5067,5069,5071,5073,5075,5077,5079,5081,5083,5085,5087,5089,5091,5093,5095,5097,5099,5101,5103,5105,5107,5109,5111,5113,5115,5117,5119,5121,5123,5125,5127,5129,5131,5133,5135,5137,5139,5141,5143,5145,5147,5149,5151,5153,5155,5157,5159,5161,5163,5165,5167,5169,5171,5173,5175,5177,5179,5181,5183,5185,5187,5189,5191,5193,5195,5197,5199,5201,5203,5205,5207,5209,5211,5213,5215,5217,5219,5221,5223,5225,5227,5229,5231,5233,5235,5237,5239,5241,5243,5245,5247,5249,5251,5253,5255,5257,5259,5261,5263,5265,5267,5269,5271,5273,5275,5277,5279,5281,5283,5285,5287,5289,5291,5293,5295,5297,5299,5301,5303,5305,5307,5309,5311,5313,5315,5317,5319,5321,5323,5325,5327,5329,5331,5333,5335,5337,5339,5341,5343,5345,5347,5349,5351,5353,5355,5357,5359,5361,5363,5365,5367,5369,5371,5373,5375,5377,5379,5381,5383,5385,5387,5389,5391,5393,5395,5397,5399,5401,5403,5405,5407,5409,5411,5413,5415,5417,5419,5421,5423,5425,5427,5429,5431,5433,5435,5437,5439,5441,5443,5445,5447,5449,5451,5453,5455,5457,5459,5461,5463,5465,5467,5469,5471,5473,5475,5477,5479,5481,5483,5485,5487,5489,5491,5493,5495,5497,5499,5501,5503,5505,5507,5509,5511,5513,5515,5517,5519,5521,5523,5525,5527,5529,5531,5533,5535,5537,5539,5541,5543,5545,5547,5549,5551,5553,5555,5557,5559,5561,5563,5565,5567,5569,5571,5573,5575,5577,5579,5581,5583,5585,5587,5589,5591,5593,5595,5597,5599,5601,5603,5605,5607,5609,5611,5613,5615,5617,5619,5621,5623,5625,5627,5629,5631,5633,5635,5637,5639,5641,5643,5645,5647,5649,5651,5653,5655,5657,5659,5661,5663,5665,5667,5669,5671,5673,5675,5677,5679,5681,5683,5685,5687,5689,5691,5693,5695,5697,5699,5701,5703,5705,5707,5709,5711,5713,5715,5717,5719,5721,5723,5725,5727,5729,5731,5733,5735,5737,5739,5741,5743,5745,5747,5749,5752,5754,5756,5758,5760,5762,5764,5766,5768,5770,5772,5774,5776,5778,5780,5782,5784,5786,5788,5790,5792,5794,5796,5798,5800,5802,5804,5806,5808,5810,5812,5814,5816,5818,5820,5822,5824,5826,5828,5830,5832,5834,5836,5838,5840,5842,5844,5846,5848,5850,5852,5854,5856,5858,5860,5862,5864,5866,5868,5870,5872,5874,5876,5878,5880,5882,5884,5886,5888,5890,5892,5894,5896,5898,5900,5902,5904,5906,5908,5910,5912,5914,5916,5918,5920,5922,5924,5926,5928,5930,5932,5934,5936,5938,5940,5942,5944,5946,5948,5950,5952,5954,5956,5958,5960,5962,5964,5967,5969,5971,5973,5975,5977,5979,5981,5983,5985,5987,5989,5991,5993,5995,5997,5999,6001,6003,6005,6007,6009,6011,6013,6015,6017,6019,6021,6023,6025,6027,6029,6031,6033,6035,6037,6039,6041,6043,6045,6047,6049,6051,6053,6055,6057,6059,6061,6063,6065,6067,6069,6071,6073,6075,6077,6079,6081,6083,6085,6087,6089,6091,6093,6095,6097,6099,6101,6103,6105,6107,6109,6111,6113,6115,6117,6119,6121,6123,6125,6127,6129,6131,6133,6135,6137,6139,6141,6143,6145,6147,6149,6151,6153,6155,6157,6159,6161,6163,6165,6167,6169,6171,6173,6175,6177,6179,6181,6183,6185,6187,6189,6191,6193,6195,6197,6199,6201,6203,6205,6207,6209,6211,6213,6215,6217,6219,6221,6223,6225,6227,6229,6231,6233,6235,6237,6239,6241,6243,6245,6247,6249,6251,6253,6255,6257,6259,6261,6263,6265,6267,6269,6271,6273,6275,6277,6279,6281,6283,6285,6287,6289,6291,6293,6295,6297,6299,6301,6303,6305,6307,6309,6311,6313,6315,6317,6319,6321,6323,6325,6327,6329,6331,6333,6335,6337,6339,6341,6343,6345,6347,6349,6351,6353,6355,6357,6359,6361,6363,6365,6367,6369,6371,6373,6375,6377,6379,6381,6383,6385,6387,6389,6391,6393,6395,6397,6399,6401,6403,6405,6407,6409,6411,6413,6415,6417,6419,6421,6423,6425,6427,6429,6431,6433,6435,6437,6439,6441,6443,6445,6447,6449,6451,6453,6455,6457,6459,6461,6463,6465,6467,6469,6471,6473,6475,6477,6479,6481,6483,6485,6487,6489,6491,6493,6495,6497,6499,6501,6503,6505,6507,6509,6511,6513,6515,6517,6519,6521,6523,6525,6527,6529,6531,6533,6535,6537,6539,6541,6543,6545,6547,6549,6551,6553,6555,6557,6559,6561,6563,6565,6567,6569,6571,6573,6575,6577,6579,6581,6583,6585,6587,6589,6591,6593,6595,6597,6599,6601,6603,6605,6607,6609,6611,6613,6615,6617,6619,6621,6623,6625,6627,6629,6631,6633,6635,6637,6639,6641,6643,6645,6647,6649,6651,6653,6655,6657,6659,6661,6663,6665,6667,6669,6671,6673,6675,6677,6679,6681,6683,6685,6687,6689,6691,6693,6695,6697,6699,6701,6703,6705,6707,6709,6711,6713,6715,6717,6719,6721,6723,6725,6727,6729,6731,6733,6735,6737,6739,6741,6743,6745,6747,6749,6751,6753,6755,6757,6759,6761,6763,6765,6767,6769,6771,6773,6775,6777,6779,6781,6783,6785,6787,6789,6791,6793,6795,6797,6799,6801,6803,6805,6807,6809,6811,6813,6815,6817,6819,6821,6823,6825,6827,6829,6831,6833,6835,6837,6839,6841,6843,6845,6847,6849,6851,6853,6855,6857,6859,6861,6863,6865,6867,6869,6871,6873,6875,6877,6879,6881,6883,6885,6887,6889,6891,6893,6895,6897,6899,6901,6903,6905,6907,6909,6911,6913,6915,6917,6919,6921,6923,6925,6927,6929,6931,6933,6935,6937,6939,6941,6943,6945,6947,6949,6951,6953,6955,6957,6959,6961,6963,6965,6967,6969,6971,6973,6975,6977,6979,6981,6983,6985,6987,6989,6991,6993,6995,6997,6999,7001,7003,7005,7007,7009,7011,7013,7015,7017,7019,7021,7023,7025,7027,7029,7031,7033,7035,7037,7039,7041,7043,7045,7047,7049,7051,7053,7055,7057,7059,7061,7063,7065,7067,7069,7071,7073,7075,7077,7079,7081,7083,7085,7087,7089,7091,7093,7095,7097,7099,7101,7103,7105,7107,7109,7111,7113,7115,7117,7119,7121,7123,7125,7127,7129,7131,7133,7135,7137,7139,7141,7143,7145,7147,7149,7151,7153,7155,7157,7159,7161,7163,7165,7167,7169,7171,7173,7175,7177,7179,7181,7183,7185,7187,7189,7191,7193,7195,7197,7199,7201,7203,7205,7207,7209,7211,7213,7215,7217,7219,7221,7223,7225,7227,7229,7231,7233,7235,7237,7239,7241,7243,7245,7247,7249,7251,7253,7255,7257,7259,7261,7263,7265,7267,7269,7271,7273,7275,7277,7279,7281,7283,7285,7287,7289,7291,7293,7295,7297,7299,7301,7303,7305,7307,7309,7311,7313,7315,7317,7319,7321,7323,7325,7327,7329,7331,7333,7335,7337,7339,7341,7343,7345,7347,7349,7351,7353,7355,7357,7359,7361,7363,7365,7367,7369,7371,7373,7375,7377,7379,7381,7383,7385,7387,7389,7391,7393,7395,7397,7399,7401,7403,7405,7407,7409,7411,7413,7415,7417,7419,7421,7423,7425,7427,7429,7431,7433,7435,7437,7439,7441,7443,7445],{"categories":105},[70],{"categories":107},[108],"Developer Productivity",{"categories":110},[70],{"categories":112},[113],"Business & SaaS",{"categories":115},[70],{"categories":117},[118],"AI Automation",{"categories":120},[121],"Product Strategy",{"categories":123},[118],{"categories":125},[70],{"categories":127},[108],{"categories":129},[118],{"categories":131},[132],"Software Engineering",{"categories":134},[135],"Data Science & Visualization",{"categories":137},[70],{"categories":139},[113],{"categories":141},[],{"categories":143},[70],{"categories":145},[146],"Inference & Serving",{"categories":148},[70],{"categories":150},[70],{"categories":152},[118],{"categories":154},[],{"categories":156},[157],"AI News & Trends",{"categories":159},[135],{"categories":161},[118],{"categories":163},[70],{"categories":165},[70],{"categories":167},[70],{"categories":169},[113],{"categories":171},[108],{"categories":173},[70],{"categories":175},[118],{"categories":177},[157],{"categories":179},[70],{"categories":181},[118],{"categories":183},[118],{"categories":185},[70],{"categories":187},[70],{"categories":189},[118],{"categories":191},[70],{"categories":193},[70],{"categories":195},[70],{"categories":197},[113],{"categories":199},[118],{"categories":201},[157],{"categories":203},[70],{"categories":205},[70],{"categories":207},[70],{"categories":209},[],{"categories":211},[212],"Design & Frontend",{"categories":214},[70],{"categories":216},[135],{"categories":218},[157],{"categories":220},[70],{"categories":222},[70],{"categories":224},[70],{"categories":226},[],{"categories":228},[70],{"categories":230},[70],{"categories":232},[118],{"categories":234},[132],{"categories":236},[70],{"categories":238},[118],{"categories":240},[70],{"categories":242},[243],"Marketing & Growth",{"categories":245},[212],{"categories":247},[70],{"categories":249},[118],{"categories":251},[70],{"categories":253},[70],{"categories":255},[132],{"categories":257},[70],{"categories":259},[],{"categories":261},[],{"categories":263},[212],{"categories":265},[70],{"categories":267},[118],{"categories":269},[108],{"categories":271},[132],{"categories":273},[118],{"categories":275},[212],{"categories":277},[121],{"categories":279},[70],{"categories":281},[132],{"categories":283},[284],"DevOps & Cloud",{"categories":286},[118],{"categories":288},[121],{"categories":290},[157],{"categories":292},[70],{"categories":294},[],{"categories":296},[70],{"categories":298},[70],{"categories":300},[70],{"categories":302},[],{"categories":304},[118],{"categories":306},[132],{"categories":308},[],{"categories":310},[132],{"categories":312},[118],{"categories":314},[70],{"categories":316},[212],{"categories":318},[319],"Governance & Standards",{"categories":321},[113],{"categories":323},[],{"categories":325},[70],{"categories":327},[],{"categories":329},[70],{"categories":331},[70],{"categories":333},[118],{"categories":335},[118],{"categories":337},[70],{"categories":339},[70],{"categories":341},[118],{"categories":343},[70],{"categories":345},[70],{"categories":347},[70],{"categories":349},[],{"categories":351},[132],{"categories":353},[],{"categories":355},[],{"categories":357},[70],{"categories":359},[132],{"categories":361},[],{"categories":363},[132],{"categories":365},[70],{"categories":367},[118],{"categories":369},[70],{"categories":371},[243],{"categories":373},[70],{"categories":375},[70],{"categories":377},[70],{"categories":379},[212],{"categories":381},[212],{"categories":383},[70],{"categories":385},[132],{"categories":387},[118],{"categories":389},[390],"GovTech & Public-Sector Adoption",{"categories":392},[132],{"categories":394},[70],{"categories":396},[70],{"categories":398},[70],{"categories":400},[118],{"categories":402},[118],{"categories":404},[135],{"categories":406},[70],{"categories":408},[157],{"categories":410},[118],{"categories":412},[413],"Legal AI Tools",{"categories":415},[70],{"categories":417},[118],{"categories":419},[70],{"categories":421},[243],{"categories":423},[118],{"categories":425},[121],{"categories":427},[70],{"categories":429},[132],{"categories":431},[390],{"categories":433},[],{"categories":435},[118],{"categories":437},[],{"categories":439},[113],{"categories":441},[118],{"categories":443},[118],{"categories":445},[446],"RAG & Retrieval",{"categories":448},[113],{"categories":450},[70],{"categories":452},[132],{"categories":454},[132],{"categories":456},[284],{"categories":458},[212],{"categories":460},[118],{"categories":462},[70],{"categories":464},[70],{"categories":466},[],{"categories":468},[118],{"categories":470},[471],"Agents & Orchestration",{"categories":473},[132],{"categories":475},[70],{"categories":477},[],{"categories":479},[118],{"categories":481},[113],{"categories":483},[],{"categories":485},[70],{"categories":487},[],{"categories":489},[70],{"categories":491},[108],{"categories":493},[132],{"categories":495},[113],{"categories":497},[70],{"categories":499},[70],{"categories":501},[70],{"categories":503},[118],{"categories":505},[70],{"categories":507},[70],{"categories":509},[157],{"categories":511},[70],{"categories":513},[],{"categories":515},[70],{"categories":517},[70],{"categories":519},[],{"categories":521},[70],{"categories":523},[132],{"categories":525},[70],{"categories":527},[118],{"categories":529},[135],{"categories":531},[],{"categories":533},[70],{"categories":535},[70],{"categories":537},[212],{"categories":539},[540],"Models & Frontier Labs",{"categories":542},[],{"categories":544},[212],{"categories":546},[547],"Regulation & Governance of AI",{"categories":549},[121],{"categories":551},[118],{"categories":553},[],{"categories":555},[70],{"categories":557},[70],{"categories":559},[118],{"categories":561},[118],{"categories":563},[157],{"categories":565},[70],{"categories":567},[113],{"categories":569},[70],{"categories":571},[118],{"categories":573},[],{"categories":575},[132],{"categories":577},[118],{"categories":579},[70],{"categories":581},[121],{"categories":583},[70],{"categories":585},[586],"AI Policy & Regulation",{"categories":588},[],{"categories":590},[70],{"categories":592},[118],{"categories":594},[118],{"categories":596},[121],{"categories":598},[118],{"categories":600},[70],{"categories":602},[70],{"categories":604},[70],{"categories":606},[118],{"categories":608},[],{"categories":610},[135],{"categories":612},[613],"Evals & Reliability",{"categories":615},[70],{"categories":617},[70],{"categories":619},[],{"categories":621},[135],{"categories":623},[108],{"categories":625},[390],{"categories":627},[586],{"categories":629},[70],{"categories":631},[113],{"categories":633},[70],{"categories":635},[118],{"categories":637},[70],{"categories":639},[118],{"categories":641},[471],{"categories":643},[70],{"categories":645},[132],{"categories":647},[70],{"categories":649},[70],{"categories":651},[],{"categories":653},[212],{"categories":655},[],{"categories":657},[70],{"categories":659},[390],{"categories":661},[70],{"categories":663},[70],{"categories":665},[70],{"categories":667},[],{"categories":669},[70],{"categories":671},[212],{"categories":673},[132],{"categories":675},[],{"categories":677},[70],{"categories":679},[],{"categories":681},[118],{"categories":683},[70],{"categories":685},[212],{"categories":687},[],{"categories":689},[70],{"categories":691},[70],{"categories":693},[135],{"categories":695},[118],{"categories":697},[70],{"categories":699},[113],{"categories":701},[118],{"categories":703},[70],{"categories":705},[70],{"categories":707},[132],{"categories":709},[212],{"categories":711},[70],{"categories":713},[118],{"categories":715},[],{"categories":717},[132],{"categories":719},[118],{"categories":721},[135],{"categories":723},[],{"categories":725},[70],{"categories":727},[157],{"categories":729},[70],{"categories":731},[],{"categories":733},[70],{"categories":735},[70],{"categories":737},[70],{"categories":739},[113,243],{"categories":741},[],{"categories":743},[132],{"categories":745},[70],{"categories":747},[70],{"categories":749},[118],{"categories":751},[70],{"categories":753},[70],{"categories":755},[],{"categories":757},[],{"categories":759},[70],{"categories":761},[212],{"categories":763},[70],{"categories":765},[],{"categories":767},[70],{"categories":769},[284],{"categories":771},[],{"categories":773},[118],{"categories":775},[157],{"categories":777},[70],{"categories":779},[113],{"categories":781},[70],{"categories":783},[132],{"categories":785},[212],{"categories":787},[],{"categories":789},[157],{"categories":791},[70],{"categories":793},[146],{"categories":795},[70],{"categories":797},[70],{"categories":799},[118],{"categories":801},[157],{"categories":803},[540],{"categories":805},[70],{"categories":807},[243],{"categories":809},[],{"categories":811},[118],{"categories":813},[113],{"categories":815},[132],{"categories":817},[70],{"categories":819},[118],{"categories":821},[],{"categories":823},[70,284],{"categories":825},[70],{"categories":827},[70],{"categories":829},[70],{"categories":831},[118],{"categories":833},[70,132],{"categories":835},[135],{"categories":837},[70],{"categories":839},[70],{"categories":841},[70],{"categories":843},[132],{"categories":845},[70],{"categories":847},[118],{"categories":849},[118],{"categories":851},[586],{"categories":853},[243],{"categories":855},[70],{"categories":857},[118],{"categories":859},[70],{"categories":861},[70],{"categories":863},[118],{"categories":865},[],{"categories":867},[118],{"categories":869},[70],{"categories":871},[70],{"categories":873},[118],{"categories":875},[70],{"categories":877},[70,113],{"categories":879},[70],{"categories":881},[113],{"categories":883},[],{"categories":885},[212],{"categories":887},[212],{"categories":889},[70],{"categories":891},[],{"categories":893},[],{"categories":895},[70],{"categories":897},[157],{"categories":899},[],{"categories":901},[108],{"categories":903},[70],{"categories":905},[132],{"categories":907},[118],{"categories":909},[70],{"categories":911},[912],"Generative UI & Design-to-Code",{"categories":914},[70],{"categories":916},[70],{"categories":918},[212],{"categories":920},[70],{"categories":922},[923],"Algorithmic Accountability",{"categories":925},[118],{"categories":927},[132],{"categories":929},[157],{"categories":931},[212],{"categories":933},[70],{"categories":935},[],{"categories":937},[121],{"categories":939},[70],{"categories":941},[70],{"categories":943},[70],{"categories":945},[70],{"categories":947},[70],{"categories":949},[118],{"categories":951},[952],"MLOps & Infrastructure",{"categories":954},[70],{"categories":956},[70],{"categories":958},[70],{"categories":960},[70],{"categories":962},[70],{"categories":964},[132],{"categories":966},[157],{"categories":968},[70],{"categories":970},[70],{"categories":972},[121],{"categories":974},[108],{"categories":976},[70],{"categories":978},[118],{"categories":980},[284],{"categories":982},[70],{"categories":984},[113],{"categories":986},[70],{"categories":988},[212],{"categories":990},[70],{"categories":992},[121],{"categories":994},[70],{"categories":996},[118],{"categories":998},[],{"categories":1000},[],{"categories":1002},[70],{"categories":1004},[146],{"categories":1006},[212],{"categories":1008},[157],{"categories":1010},[135],{"categories":1012},[],{"categories":1014},[70],{"categories":1016},[70],{"categories":1018},[113],{"categories":1020},[118],{"categories":1022},[70],{"categories":1024},[70],{"categories":1026},[70],{"categories":1028},[70],{"categories":1030},[70],{"categories":1032},[157],{"categories":1034},[146],{"categories":1036},[70],{"categories":1038},[212],{"categories":1040},[70],{"categories":1042},[],{"categories":1044},[118],{"categories":1046},[132],{"categories":1048},[],{"categories":1050},[70],{"categories":1052},[70],{"categories":1054},[118],{"categories":1056},[132],{"categories":1058},[70],{"categories":1060},[135],{"categories":1062},[212],{"categories":1064},[],{"categories":1066},[70],{"categories":1068},[],{"categories":1070},[70],{"categories":1072},[],{"categories":1074},[70],{"categories":1076},[70],{"categories":1078},[121],{"categories":1080},[113],{"categories":1082},[118],{"categories":1084},[118],{"categories":1086},[],{"categories":1088},[70],{"categories":1090},[108],{"categories":1092},[70],{"categories":1094},[70],{"categories":1096},[113],{"categories":1098},[157],{"categories":1100},[108],{"categories":1102},[],{"categories":1104},[70],{"categories":1106},[],{"categories":1108},[70],{"categories":1110},[],{"categories":1112},[70],{"categories":1114},[157],{"categories":1116},[157],{"categories":1118},[],{"categories":1120},[471],{"categories":1122},[70],{"categories":1124},[212],{"categories":1126},[132],{"categories":1128},[],{"categories":1130},[413],{"categories":1132},[118],{"categories":1134},[113],{"categories":1136},[],{"categories":1138},[],{"categories":1140},[108],{"categories":1142},[135],{"categories":1144},[],{"categories":1146},[243],{"categories":1148},[118],{"categories":1150},[113],{"categories":1152},[118],{"categories":1154},[70],{"categories":1156},[113],{"categories":1158},[70],{"categories":1160},[132],{"categories":1162},[],{"categories":1164},[146],{"categories":1166},[121],{"categories":1168},[70],{"categories":1170},[212],{"categories":1172},[132],{"categories":1174},[113],{"categories":1176},[70],{"categories":1178},[132],{"categories":1180},[70],{"categories":1182},[118],{"categories":1184},[113],{"categories":1186},[70],{"categories":1188},[70],{"categories":1190},[70],{"categories":1192},[70],{"categories":1194},[70],{"categories":1196},[70],{"categories":1198},[],{"categories":1200},[],{"categories":1202},[132],{"categories":1204},[135],{"categories":1206},[121],{"categories":1208},[70],{"categories":1210},[118],{"categories":1212},[132],{"categories":1214},[132],{"categories":1216},[70],{"categories":1218},[],{"categories":1220},[70],{"categories":1222},[157],{"categories":1224},[121],{"categories":1226},[121],{"categories":1228},[132],{"categories":1230},[70],{"categories":1232},[613],{"categories":1234},[284],{"categories":1236},[],{"categories":1238},[118],{"categories":1240},[70],{"categories":1242},[108],{"categories":1244},[],{"categories":1246},[108],{"categories":1248},[],{"categories":1250},[70],{"categories":1252},[70],{"categories":1254},[70],{"categories":1256},[212],{"categories":1258},[243],{"categories":1260},[121],{"categories":1262},[70],{"categories":1264},[132],{"categories":1266},[70],{"categories":1268},[118],{"categories":1270},[],{"categories":1272},[132],{"categories":1274},[70],{"categories":1276},[108],{"categories":1278},[],{"categories":1280},[113],{"categories":1282},[70],{"categories":1284},[70],{"categories":1286},[157],{"categories":1288},[70,284],{"categories":1290},[70],{"categories":1292},[1293],"Design Systems for AI",{"categories":1295},[70],{"categories":1297},[70],{"categories":1299},[157],{"categories":1301},[70],{"categories":1303},[70],{"categories":1305},[70],{"categories":1307},[113],{"categories":1309},[70],{"categories":1311},[70],{"categories":1313},[70],{"categories":1315},[],{"categories":1317},[70],{"categories":1319},[70],{"categories":1321},[113],{"categories":1323},[70],{"categories":1325},[],{"categories":1327},[118],{"categories":1329},[118],{"categories":1331},[132],{"categories":1333},[157],{"categories":1335},[132],{"categories":1337},[70],{"categories":1339},[212],{"categories":1341},[157],{"categories":1343},[135],{"categories":1345},[70],{"categories":1347},[70],{"categories":1349},[70],{"categories":1351},[70],{"categories":1353},[118],{"categories":1355},[108],{"categories":1357},[586],{"categories":1359},[70],{"categories":1361},[70],{"categories":1363},[118],{"categories":1365},[70],{"categories":1367},[132],{"categories":1369},[70],{"categories":1371},[132],{"categories":1373},[],{"categories":1375},[212],{"categories":1377},[],{"categories":1379},[70],{"categories":1381},[118],{"categories":1383},[121],{"categories":1385},[],{"categories":1387},[113],{"categories":1389},[70],{"categories":1391},[],{"categories":1393},[212],{"categories":1395},[132],{"categories":1397},[118],{"categories":1399},[132],{"categories":1401},[212],{"categories":1403},[70],{"categories":1405},[132],{"categories":1407},[70],{"categories":1409},[212],{"categories":1411},[],{"categories":1413},[],{"categories":1415},[157],{"categories":1417},[118],{"categories":1419},[118],{"categories":1421},[70],{"categories":1423},[70],{"categories":1425},[70],{"categories":1427},[70],{"categories":1429},[70],{"categories":1431},[113],{"categories":1433},[70],{"categories":1435},[70],{"categories":1437},[],{"categories":1439},[132],{"categories":1441},[132],{"categories":1443},[70],{"categories":1445},[132],{"categories":1447},[113],{"categories":1449},[],{"categories":1451},[70],{"categories":1453},[70],{"categories":1455},[212],{"categories":1457},[70],{"categories":1459},[70],{"categories":1461},[70],{"categories":1463},[118],{"categories":1465},[108],{"categories":1467},[113],{"categories":1469},[70],{"categories":1471},[118],{"categories":1473},[157],{"categories":1475},[118],{"categories":1477},[146],{"categories":1479},[243],{"categories":1481},[70],{"categories":1483},[118],{"categories":1485},[70],{"categories":1487},[70],{"categories":1489},[70],{"categories":1491},[],{"categories":1493},[212],{"categories":1495},[],{"categories":1497},[70],{"categories":1499},[70],{"categories":1501},[],{"categories":1503},[70],{"categories":1505},[132],{"categories":1507},[113],{"categories":1509},[1510],"Visual & Generative Media",{"categories":1512},[118],{"categories":1514},[],{"categories":1516},[70],{"categories":1518},[70],{"categories":1520},[132],{"categories":1522},[70],{"categories":1524},[284],{"categories":1526},[70],{"categories":1528},[135],{"categories":1530},[586],{"categories":1532},[132],{"categories":1534},[243],{"categories":1536},[70],{"categories":1538},[121],{"categories":1540},[212],{"categories":1542},[70],{"categories":1544},[70],{"categories":1546},[132],{"categories":1548},[118],{"categories":1550},[70],{"categories":1552},[],{"categories":1554},[],{"categories":1556},[118],{"categories":1558},[132],{"categories":1560},[108],{"categories":1562},[118],{"categories":1564},[540],{"categories":1566},[70],{"categories":1568},[121],{"categories":1570},[70],{"categories":1572},[113],{"categories":1574},[],{"categories":1576},[70],{"categories":1578},[121],{"categories":1580},[70],{"categories":1582},[70],{"categories":1584},[70],{"categories":1586},[121],{"categories":1588},[70],{"categories":1590},[70],{"categories":1592},[243],{"categories":1594},[70],{"categories":1596},[471],{"categories":1598},[118],{"categories":1600},[70],{"categories":1602},[118],{"categories":1604},[70],{"categories":1606},[70],{"categories":1608},[118],{"categories":1610},[70],{"categories":1612},[70],{"categories":1614},[118],{"categories":1616},[70],{"categories":1618},[212],{"categories":1620},[118],{"categories":1622},[],{"categories":1624},[118],{"categories":1626},[70],{"categories":1628},[],{"categories":1630},[284],{"categories":1632},[132],{"categories":1634},[],{"categories":1636},[540],{"categories":1638},[70],{"categories":1640},[118],{"categories":1642},[118],{"categories":1644},[70],{"categories":1646},[212,70],{"categories":1648},[108],{"categories":1650},[70],{"categories":1652},[118],{"categories":1654},[212],{"categories":1656},[],{"categories":1658},[70],{"categories":1660},[108],{"categories":1662},[70],{"categories":1664},[1665],"Medical Imaging & Radiology",{"categories":1667},[70],{"categories":1669},[70],{"categories":1671},[70],{"categories":1673},[212],{"categories":1675},[118],{"categories":1677},[132],{"categories":1679},[],{"categories":1681},[70],{"categories":1683},[70],{"categories":1685},[70],{"categories":1687},[],{"categories":1689},[],{"categories":1691},[70],{"categories":1693},[70],{"categories":1695},[471],{"categories":1697},[70],{"categories":1699},[108],{"categories":1701},[70],{"categories":1703},[70],{"categories":1705},[],{"categories":1707},[118],{"categories":1709},[70],{"categories":1711},[121],{"categories":1713},[132],{"categories":1715},[70],{"categories":1717},[118],{"categories":1719},[471],{"categories":1721},[70],{"categories":1723},[118],{"categories":1725},[70],{"categories":1727},[70],{"categories":1729},[70],{"categories":1731},[70],{"categories":1733},[212],{"categories":1735},[118],{"categories":1737},[284],{"categories":1739},[212],{"categories":1741},[113],{"categories":1743},[118],{"categories":1745},[157],{"categories":1747},[70],{"categories":1749},[70],{"categories":1751},[121],{"categories":1753},[70],{"categories":1755},[70],{"categories":1757},[70],{"categories":1759},[70],{"categories":1761},[70],{"categories":1763},[118],{"categories":1765},[70],{"categories":1767},[132],{"categories":1769},[132],{"categories":1771},[70],{"categories":1773},[121],{"categories":1775},[],{"categories":1777},[157],{"categories":1779},[],{"categories":1781},[121],{"categories":1783},[118],{"categories":1785},[70],{"categories":1787},[118],{"categories":1789},[1293],{"categories":1791},[70],{"categories":1793},[1293],{"categories":1795},[212],{"categories":1797},[70],{"categories":1799},[70],{"categories":1801},[70],{"categories":1803},[118],{"categories":1805},[132],{"categories":1807},[212],{"categories":1809},[118],{"categories":1811},[157],{"categories":1813},[],{"categories":1815},[70],{"categories":1817},[],{"categories":1819},[70],{"categories":1821},[70],{"categories":1823},[70],{"categories":1825},[70],{"categories":1827},[70],{"categories":1829},[118],{"categories":1831},[1832],"Contract Review & E-Discovery",{"categories":1834},[70],{"categories":1836},[212],{"categories":1838},[70],{"categories":1840},[108],{"categories":1842},[70],{"categories":1844},[157],{"categories":1846},[70],{"categories":1848},[70],{"categories":1850},[243],{"categories":1852},[132],{"categories":1854},[118],{"categories":1856},[70],{"categories":1858},[70],{"categories":1860},[70],{"categories":1862},[118],{"categories":1864},[118],{"categories":1866},[923],{"categories":1868},[70],{"categories":1870},[70],{"categories":1872},[118],{"categories":1874},[118],{"categories":1876},[70],{"categories":1878},[70],{"categories":1880},[70],{"categories":1882},[118],{"categories":1884},[70],{"categories":1886},[132],{"categories":1888},[70],{"categories":1890},[471],{"categories":1892},[446],{"categories":1894},[70],{"categories":1896},[118],{"categories":1898},[70],{"categories":1900},[1901],"Law-Firm Practice & Adoption",{"categories":1903},[70],{"categories":1905},[118],{"categories":1907},[212],{"categories":1909},[70],{"categories":1911},[70],{"categories":1913},[70],{"categories":1915},[],{"categories":1917},[132],{"categories":1919},[],{"categories":1921},[132],{"categories":1923},[70],{"categories":1925},[],{"categories":1927},[118],{"categories":1929},[108],{"categories":1931},[284],{"categories":1933},[70],{"categories":1935},[],{"categories":1937},[70],{"categories":1939},[108],{"categories":1941},[113],{"categories":1943},[70],{"categories":1945},[243],{"categories":1947},[70],{"categories":1949},[],{"categories":1951},[113],{"categories":1953},[118],{"categories":1955},[113],{"categories":1957},[],{"categories":1959},[70],{"categories":1961},[121],{"categories":1963},[70],{"categories":1965},[132],{"categories":1967},[],{"categories":1969},[],{"categories":1971},[],{"categories":1973},[],{"categories":1975},[70],{"categories":1977},[121],{"categories":1979},[118],{"categories":1981},[284],{"categories":1983},[70],{"categories":1985},[108],{"categories":1987},[132],{"categories":1989},[70],{"categories":1991},[70],{"categories":1993},[132],{"categories":1995},[121],{"categories":1997},[70],{"categories":1999},[70],{"categories":2001},[70],{"categories":2003},[952],{"categories":2005},[70],{"categories":2007},[132],{"categories":2009},[70],{"categories":2011},[243],{"categories":2013},[132],{"categories":2015},[113],{"categories":2017},[70],{"categories":2019},[70],{"categories":2021},[70],{"categories":2023},[212],{"categories":2025},[70],{"categories":2027},[70],{"categories":2029},[70],{"categories":2031},[70],{"categories":2033},[113],{"categories":2035},[118],{"categories":2037},[70,108],{"categories":2039},[471],{"categories":2041},[70],{"categories":2043},[70],{"categories":2045},[132],{"categories":2047},[132],{"categories":2049},[212],{"categories":2051},[118],{"categories":2053},[118],{"categories":2055},[132],{"categories":2057},[70],{"categories":2059},[118],{"categories":2061},[70],{"categories":2063},[70],{"categories":2065},[],{"categories":2067},[],{"categories":2069},[70],{"categories":2071},[135],{"categories":2073},[70],{"categories":2075},[212],{"categories":2077},[118],{"categories":2079},[],{"categories":2081},[70],{"categories":2083},[70],{"categories":2085},[132],{"categories":2087},[135],{"categories":2089},[157],{"categories":2091},[212],{"categories":2093},[70],{"categories":2095},[118],{"categories":2097},[70],{"categories":2099},[132],{"categories":2101},[],{"categories":2103},[118],{"categories":2105},[70],{"categories":2107},[70],{"categories":2109},[70],{"categories":2111},[70],{"categories":2113},[70],{"categories":2115},[],{"categories":2117},[118],{"categories":2119},[70],{"categories":2121},[70],{"categories":2123},[70],{"categories":2125},[],{"categories":2127},[118],{"categories":2129},[118],{"categories":2131},[70],{"categories":2133},[70],{"categories":2135},[113],{"categories":2137},[70],{"categories":2139},[70],{"categories":2141},[],{"categories":2143},[108],{"categories":2145},[70],{"categories":2147},[70],{"categories":2149},[70],{"categories":2151},[212],{"categories":2153},[70],{"categories":2155},[132],{"categories":2157},[70],{"categories":2159},[108],{"categories":2161},[70],{"categories":2163},[132],{"categories":2165},[243],{"categories":2167},[132],{"categories":2169},[118],{"categories":2171},[118],{"categories":2173},[70],{"categories":2175},[70],{"categories":2177},[70,212],{"categories":2179},[70],{"categories":2181},[118],{"categories":2183},[157],{"categories":2185},[70],{"categories":2187},[157],{"categories":2189},[118],{"categories":2191},[212],{"categories":2193},[70],{"categories":2195},[],{"categories":2197},[132],{"categories":2199},[284],{"categories":2201},[212],{"categories":2203},[132],{"categories":2205},[70],{"categories":2207},[121],{"categories":2209},[70],{"categories":2211},[70],{"categories":2213},[118],{"categories":2215},[],{"categories":2217},[],{"categories":2219},[70],{"categories":2221},[],{"categories":2223},[],{"categories":2225},[121],{"categories":2227},[132],{"categories":2229},[70],{"categories":2231},[70],{"categories":2233},[118],{"categories":2235},[118],{"categories":2237},[113],{"categories":2239},[118],{"categories":2241},[284],{"categories":2243},[70],{"categories":2245},[70],{"categories":2247},[70],{"categories":2249},[146],{"categories":2251},[70],{"categories":2253},[70],{"categories":2255},[70],{"categories":2257},[70],{"categories":2259},[132],{"categories":2261},[118],{"categories":2263},[70],{"categories":2265},[70],{"categories":2267},[70],{"categories":2269},[132],{"categories":2271},[413],{"categories":2273},[118],{"categories":2275},[923],{"categories":2277},[],{"categories":2279},[118],{"categories":2281},[212],{"categories":2283},[1901],{"categories":2285},[132],{"categories":2287},[],{"categories":2289},[],{"categories":2291},[70],{"categories":2293},[118],{"categories":2295},[],{"categories":2297},[],{"categories":2299},[70],{"categories":2301},[243],{"categories":2303},[70],{"categories":2305},[243],{"categories":2307},[70],{"categories":2309},[118],{"categories":2311},[70],{"categories":2313},[135],{"categories":2315},[70],{"categories":2317},[132],{"categories":2319},[121],{"categories":2321},[],{"categories":2323},[70],{"categories":2325},[70],{"categories":2327},[70],{"categories":2329},[132],{"categories":2331},[70],{"categories":2333},[1832],{"categories":2335},[70],{"categories":2337},[212],{"categories":2339},[212],{"categories":2341},[70],{"categories":2343},[118],{"categories":2345},[108],{"categories":2347},[70],{"categories":2349},[70],{"categories":2351},[70],{"categories":2353},[70],{"categories":2355},[212],{"categories":2357},[212],{"categories":2359},[118],{"categories":2361},[118],{"categories":2363},[118],{"categories":2365},[70],{"categories":2367},[70],{"categories":2369},[70],{"categories":2371},[118],{"categories":2373},[],{"categories":2375},[70],{"categories":2377},[],{"categories":2379},[2380],"Interaction & Product Design",{"categories":2382},[70],{"categories":2384},[118],{"categories":2386},[132],{"categories":2388},[319],{"categories":2390},[157],{"categories":2392},[132],{"categories":2394},[70],{"categories":2396},[70],{"categories":2398},[70],{"categories":2400},[132],{"categories":2402},[70],{"categories":2404},[108],{"categories":2406},[118],{"categories":2408},[70],{"categories":2410},[],{"categories":2412},[118],{"categories":2414},[118],{"categories":2416},[118],{"categories":2418},[],{"categories":2420},[132],{"categories":2422},[70],{"categories":2424},[118],{"categories":2426},[108],{"categories":2428},[2380],{"categories":2430},[70],{"categories":2432},[108],{"categories":2434},[108],{"categories":2436},[70],{"categories":2438},[],{"categories":2440},[70],{"categories":2442},[118],{"categories":2444},[132],{"categories":2446},[],{"categories":2448},[118],{"categories":2450},[157],{"categories":2452},[70],{"categories":2454},[118],{"categories":2456},[70],{"categories":2458},[118],{"categories":2460},[118],{"categories":2462},[70],{"categories":2464},[70],{"categories":2466},[157],{"categories":2468},[135],{"categories":2470},[70],{"categories":2472},[121],{"categories":2474},[132],{"categories":2476},[2477],"Coding Agents & Dev Productivity",{"categories":2479},[157],{"categories":2481},[212],{"categories":2483},[70],{"categories":2485},[70],{"categories":2487},[],{"categories":2489},[70],{"categories":2491},[923],{"categories":2493},[],{"categories":2495},[70],{"categories":2497},[70],{"categories":2499},[284],{"categories":2501},[70],{"categories":2503},[157],{"categories":2505},[],{"categories":2507},[],{"categories":2509},[70],{"categories":2511},[],{"categories":2513},[118],{"categories":2515},[70],{"categories":2517},[118],{"categories":2519},[],{"categories":2521},[132],{"categories":2523},[132],{"categories":2525},[70],{"categories":2527},[135],{"categories":2529},[],{"categories":2531},[70],{"categories":2533},[70],{"categories":2535},[70],{"categories":2537},[135],{"categories":2539},[132],{"categories":2541},[118],{"categories":2543},[],{"categories":2545},[],{"categories":2547},[70],{"categories":2549},[70],{"categories":2551},[70],{"categories":2553},[70],{"categories":2555},[118],{"categories":2557},[118],{"categories":2559},[390],{"categories":2561},[132],{"categories":2563},[121],{"categories":2565},[132],{"categories":2567},[118],{"categories":2569},[157],{"categories":2571},[157],{"categories":2573},[118],{"categories":2575},[118],{"categories":2577},[70],{"categories":2579},[108],{"categories":2581},[2380],{"categories":2583},[121],{"categories":2585},[70,284],{"categories":2587},[135],{"categories":2589},[],{"categories":2591},[212],{"categories":2593},[118],{"categories":2595},[132],{"categories":2597},[108],{"categories":2599},[70],{"categories":2601},[118],{"categories":2603},[2604],"The Designer's Role & Craft",{"categories":2606},[212],{"categories":2608},[],{"categories":2610},[118],{"categories":2612},[70],{"categories":2614},[118],{"categories":2616},[118],{"categories":2618},[70],{"categories":2620},[243],{"categories":2622},[70],{"categories":2624},[132],{"categories":2626},[118],{"categories":2628},[70],{"categories":2630},[212],{"categories":2632},[70],{"categories":2634},[],{"categories":2636},[118],{"categories":2638},[212],{"categories":2640},[121],{"categories":2642},[70],{"categories":2644},[118],{"categories":2646},[70],{"categories":2648},[70],{"categories":2650},[2651],"AI UX Patterns",{"categories":2653},[118],{"categories":2655},[118],{"categories":2657},[118],{"categories":2659},[70],{"categories":2661},[118],{"categories":2663},[243],{"categories":2665},[135],{"categories":2667},[70],{"categories":2669},[118],{"categories":2671},[70],{"categories":2673},[1293],{"categories":2675},[],{"categories":2677},[243],{"categories":2679},[118],{"categories":2681},[157],{"categories":2683},[132],{"categories":2685},[70],{"categories":2687},[118],{"categories":2689},[],{"categories":2691},[],{"categories":2693},[70],{"categories":2695},[70],{"categories":2697},[118],{"categories":2699},[70],{"categories":2701},[118],{"categories":2703},[390],{"categories":2705},[212],{"categories":2707},[70],{"categories":2709},[157],{"categories":2711},[132],{"categories":2713},[70],{"categories":2715},[118],{"categories":2717},[118],{"categories":2719},[],{"categories":2721},[70],{"categories":2723},[],{"categories":2725},[70],{"categories":2727},[],{"categories":2729},[70],{"categories":2731},[70],{"categories":2733},[70],{"categories":2735},[118],{"categories":2737},[132],{"categories":2739},[],{"categories":2741},[],{"categories":2743},[135],{"categories":2745},[146],{"categories":2747},[70],{"categories":2749},[70],{"categories":2751},[70],{"categories":2753},[135],{"categories":2755},[135],{"categories":2757},[70],{"categories":2759},[70],{"categories":2761},[157],{"categories":2763},[70],{"categories":2765},[70],{"categories":2767},[70],{"categories":2769},[118],{"categories":2771},[70],{"categories":2773},[118],{"categories":2775},[70],{"categories":2777},[70],{"categories":2779},[70],{"categories":2781},[118],{"categories":2783},[],{"categories":2785},[70],{"categories":2787},[],{"categories":2789},[70],{"categories":2791},[70],{"categories":2793},[284],{"categories":2795},[70],{"categories":2797},[],{"categories":2799},[],{"categories":2801},[212],{"categories":2803},[952],{"categories":2805},[118],{"categories":2807},[108],{"categories":2809},[2604],{"categories":2811},[],{"categories":2813},[],{"categories":2815},[70],{"categories":2817},[],{"categories":2819},[],{"categories":2821},[132],{"categories":2823},[157],{"categories":2825},[243],{"categories":2827},[118],{"categories":2829},[113],{"categories":2831},[70],{"categories":2833},[70],{"categories":2835},[113],{"categories":2837},[],{"categories":2839},[212],{"categories":2841},[121],{"categories":2843},[70],{"categories":2845},[70],{"categories":2847},[118],{"categories":2849},[113],{"categories":2851},[70],{"categories":2853},[70],{"categories":2855},[108],{"categories":2857},[70],{"categories":2859},[70],{"categories":2861},[],{"categories":2863},[108],{"categories":2865},[70],{"categories":2867},[243],{"categories":2869},[118],{"categories":2871},[157],{"categories":2873},[70],{"categories":2875},[132],{"categories":2877},[70],{"categories":2879},[70],{"categories":2881},[70],{"categories":2883},[70],{"categories":2885},[113],{"categories":2887},[70],{"categories":2889},[70],{"categories":2891},[70],{"categories":2893},[118],{"categories":2895},[70],{"categories":2897},[70],{"categories":2899},[],{"categories":2901},[70],{"categories":2903},[132],{"categories":2905},[108],{"categories":2907},[70],{"categories":2909},[70],{"categories":2911},[212],{"categories":2913},[70],{"categories":2915},[],{"categories":2917},[70],{"categories":2919},[471],{"categories":2921},[118],{"categories":2923},[113],{"categories":2925},[157],{"categories":2927},[70],{"categories":2929},[70],{"categories":2931},[],{"categories":2933},[113],{"categories":2935},[113],{"categories":2937},[70],{"categories":2939},[70],{"categories":2941},[121],{"categories":2943},[70],{"categories":2945},[70],{"categories":2947},[70],{"categories":2949},[70],{"categories":2951},[132],{"categories":2953},[135],{"categories":2955},[132],{"categories":2957},[70],{"categories":2959},[],{"categories":2961},[70],{"categories":2963},[132],{"categories":2965},[70],{"categories":2967},[132],{"categories":2969},[118],{"categories":2971},[586],{"categories":2973},[],{"categories":2975},[],{"categories":2977},[70],{"categories":2979},[157],{"categories":2981},[],{"categories":2983},[284],{"categories":2985},[70],{"categories":2987},[70],{"categories":2989},[70],{"categories":2991},[212],{"categories":2993},[912],{"categories":2995},[],{"categories":2997},[70],{"categories":2999},[70],{"categories":3001},[70],{"categories":3003},[132],{"categories":3005},[70],{"categories":3007},[70],{"categories":3009},[70],{"categories":3011},[70,284],{"categories":3013},[70],{"categories":3015},[70],{"categories":3017},[212],{"categories":3019},[118],{"categories":3021},[],{"categories":3023},[118],{"categories":3025},[118],{"categories":3027},[70],{"categories":3029},[70],{"categories":3031},[70],{"categories":3033},[70],{"categories":3035},[135],{"categories":3037},[70],{"categories":3039},[2651],{"categories":3041},[108],{"categories":3043},[70],{"categories":3045},[135],{"categories":3047},[108],{"categories":3049},[132],{"categories":3051},[212],{"categories":3053},[118],{"categories":3055},[70],{"categories":3057},[],{"categories":3059},[113],{"categories":3061},[70],{"categories":3063},[70],{"categories":3065},[157],{"categories":3067},[70],{"categories":3069},[70],{"categories":3071},[70],{"categories":3073},[118],{"categories":3075},[70],{"categories":3077},[70],{"categories":3079},[212],{"categories":3081},[70],{"categories":3083},[113],{"categories":3085},[],{"categories":3087},[284],{"categories":3089},[70],{"categories":3091},[390],{"categories":3093},[212],{"categories":3095},[212],{"categories":3097},[132],{"categories":3099},[118],{"categories":3101},[70],{"categories":3103},[113],{"categories":3105},[157],{"categories":3107},[70],{"categories":3109},[70],{"categories":3111},[70],{"categories":3113},[212],{"categories":3115},[118],{"categories":3117},[70],{"categories":3119},[118],{"categories":3121},[70],{"categories":3123},[118],{"categories":3125},[70],{"categories":3127},[540],{"categories":3129},[70],{"categories":3131},[118],{"categories":3133},[],{"categories":3135},[70],{"categories":3137},[70],{"categories":3139},[70],{"categories":3141},[70],{"categories":3143},[],{"categories":3145},[],{"categories":3147},[70],{"categories":3149},[70],{"categories":3151},[118],{"categories":3153},[70],{"categories":3155},[70],{"categories":3157},[70],{"categories":3159},[132],{"categories":3161},[70],{"categories":3163},[70],{"categories":3165},[118],{"categories":3167},[70],{"categories":3169},[70],{"categories":3171},[70],{"categories":3173},[70],{"categories":3175},[70],{"categories":3177},[],{"categories":3179},[132],{"categories":3181},[135],{"categories":3183},[70],{"categories":3185},[118],{"categories":3187},[118],{"categories":3189},[70],{"categories":3191},[70],{"categories":3193},[],{"categories":3195},[],{"categories":3197},[70],{"categories":3199},[70],{"categories":3201},[70],{"categories":3203},[157],{"categories":3205},[135],{"categories":3207},[],{"categories":3209},[70],{"categories":3211},[212],{"categories":3213},[70],{"categories":3215},[284],{"categories":3217},[1901],{"categories":3219},[70],{"categories":3221},[157],{"categories":3223},[132],{"categories":3225},[70],{"categories":3227},[132],{"categories":3229},[132],{"categories":3231},[70],{"categories":3233},[70],{"categories":3235},[132],{"categories":3237},[157],{"categories":3239},[157],{"categories":3241},[284],{"categories":3243},[118],{"categories":3245},[],{"categories":3247},[157],{"categories":3249},[113],{"categories":3251},[70],{"categories":3253},[118],{"categories":3255},[108],{"categories":3257},[132],{"categories":3259},[70],{"categories":3261},[157],{"categories":3263},[],{"categories":3265},[70],{"categories":3267},[132],{"categories":3269},[132],{"categories":3271},[135],{"categories":3273},[70],{"categories":3275},[157],{"categories":3277},[70],{"categories":3279},[132],{"categories":3281},[118],{"categories":3283},[118],{"categories":3285},[157],{"categories":3287},[118],{"categories":3289},[284],{"categories":3291},[118],{"categories":3293},[70],{"categories":3295},[70],{"categories":3297},[70],{"categories":3299},[70],{"categories":3301},[70],{"categories":3303},[132],{"categories":3305},[70],{"categories":3307},[],{"categories":3309},[118],{"categories":3311},[113],{"categories":3313},[132],{"categories":3315},[],{"categories":3317},[],{"categories":3319},[70],{"categories":3321},[118],{"categories":3323},[70],{"categories":3325},[70],{"categories":3327},[70],{"categories":3329},[3330],"Frameworks & Tooling",{"categories":3332},[70],{"categories":3334},[70],{"categories":3336},[132],{"categories":3338},[70],{"categories":3340},[70],{"categories":3342},[],{"categories":3344},[135],{"categories":3346},[135],{"categories":3348},[70],{"categories":3350},[108],{"categories":3352},[70],{"categories":3354},[118],{"categories":3356},[70],{"categories":3358},[212],{"categories":3360},[],{"categories":3362},[1901],{"categories":3364},[70],{"categories":3366},[132],{"categories":3368},[70],{"categories":3370},[284],{"categories":3372},[284],{"categories":3374},[],{"categories":3376},[118],{"categories":3378},[118],{"categories":3380},[70],{"categories":3382},[70],{"categories":3384},[157],{"categories":3386},[118],{"categories":3388},[157],{"categories":3390},[70],{"categories":3392},[118],{"categories":3394},[],{"categories":3396},[212],{"categories":3398},[70],{"categories":3400},[70],{"categories":3402},[],{"categories":3404},[70],{"categories":3406},[118],{"categories":3408},[70],{"categories":3410},[70],{"categories":3412},[70],{"categories":3414},[],{"categories":3416},[113],{"categories":3418},[132],{"categories":3420},[70],{"categories":3422},[132],{"categories":3424},[284],{"categories":3426},[70],{"categories":3428},[70],{"categories":3430},[70],{"categories":3432},[132],{"categories":3434},[70],{"categories":3436},[113],{"categories":3438},[70],{"categories":3440},[1901],{"categories":3442},[],{"categories":3444},[118],{"categories":3446},[108],{"categories":3448},[70],{"categories":3450},[108],{"categories":3452},[70],{"categories":3454},[],{"categories":3456},[118],{"categories":3458},[70],{"categories":3460},[70],{"categories":3462},[3463],"AI Design Tooling",{"categories":3465},[212],{"categories":3467},[70],{"categories":3469},[70],{"categories":3471},[132],{"categories":3473},[212],{"categories":3475},[70],{"categories":3477},[70],{"categories":3479},[132],{"categories":3481},[118],{"categories":3483},[157],{"categories":3485},[121],{"categories":3487},[132],{"categories":3489},[70],{"categories":3491},[70],{"categories":3493},[70],{"categories":3495},[118],{"categories":3497},[70],{"categories":3499},[],{"categories":3501},[118],{"categories":3503},[70],{"categories":3505},[70],{"categories":3507},[118],{"categories":3509},[70],{"categories":3511},[70],{"categories":3513},[70],{"categories":3515},[118],{"categories":3517},[],{"categories":3519},[118],{"categories":3521},[3330],{"categories":3523},[70],{"categories":3525},[70],{"categories":3527},[118],{"categories":3529},[118],{"categories":3531},[132],{"categories":3533},[132],{"categories":3535},[70],{"categories":3537},[70],{"categories":3539},[],{"categories":3541},[132],{"categories":3543},[70],{"categories":3545},[70],{"categories":3547},[118],{"categories":3549},[113],{"categories":3551},[70],{"categories":3553},[],{"categories":3555},[70],{"categories":3557},[70],{"categories":3559},[2380],{"categories":3561},[],{"categories":3563},[70],{"categories":3565},[70],{"categories":3567},[70],{"categories":3569},[70],{"categories":3571},[212],{"categories":3573},[70],{"categories":3575},[],{"categories":3577},[70],{"categories":3579},[70],{"categories":3581},[70],{"categories":3583},[70],{"categories":3585},[243],{"categories":3587},[157],{"categories":3589},[70],{"categories":3591},[70],{"categories":3593},[1901],{"categories":3595},[70],{"categories":3597},[108],{"categories":3599},[70],{"categories":3601},[70],{"categories":3603},[135],{"categories":3605},[118],{"categories":3607},[70],{"categories":3609},[70],{"categories":3611},[157],{"categories":3613},[118],{"categories":3615},[],{"categories":3617},[70],{"categories":3619},[70],{"categories":3621},[212],{"categories":3623},[70],{"categories":3625},[243],{"categories":3627},[118],{"categories":3629},[70],{"categories":3631},[118],{"categories":3633},[70],{"categories":3635},[],{"categories":3637},[],{"categories":3639},[],{"categories":3641},[108],{"categories":3643},[157],{"categories":3645},[118],{"categories":3647},[70],{"categories":3649},[70],{"categories":3651},[70],{"categories":3653},[70],{"categories":3655},[413],{"categories":3657},[212],{"categories":3659},[118],{"categories":3661},[70],{"categories":3663},[],{"categories":3665},[118],{"categories":3667},[118],{"categories":3669},[],{"categories":3671},[70],{"categories":3673},[118],{"categories":3675},[70],{"categories":3677},[],{"categories":3679},[70],{"categories":3681},[70],{"categories":3683},[70],{"categories":3685},[157],{"categories":3687},[212],{"categories":3689},[118],{"categories":3691},[212],{"categories":3693},[118],{"categories":3695},[70],{"categories":3697},[113],{"categories":3699},[],{"categories":3701},[],{"categories":3703},[70],{"categories":3705},[70],{"categories":3707},[70],{"categories":3709},[108],{"categories":3711},[70],{"categories":3713},[118],{"categories":3715},[157],{"categories":3717},[],{"categories":3719},[212],{"categories":3721},[118],{"categories":3723},[],{"categories":3725},[132],{"categories":3727},[70],{"categories":3729},[132],{"categories":3731},[212],{"categories":3733},[132],{"categories":3735},[70],{"categories":3737},[],{"categories":3739},[70],{"categories":3741},[70],{"categories":3743},[118],{"categories":3745},[],{"categories":3747},[70],{"categories":3749},[70],{"categories":3751},[243],{"categories":3753},[70],{"categories":3755},[70],{"categories":3757},[284],{"categories":3759},[132],{"categories":3761},[70],{"categories":3763},[118],{"categories":3765},[],{"categories":3767},[70],{"categories":3769},[118],{"categories":3771},[70],{"categories":3773},[108],{"categories":3775},[540],{"categories":3777},[70],{"categories":3779},[70],{"categories":3781},[70],{"categories":3783},[118],{"categories":3785},[70],{"categories":3787},[118],{"categories":3789},[70],{"categories":3791},[70],{"categories":3793},[70],{"categories":3795},[118],{"categories":3797},[70],{"categories":3799},[70],{"categories":3801},[],{"categories":3803},[70],{"categories":3805},[108],{"categories":3807},[70],{"categories":3809},[113],{"categories":3811},[132],{"categories":3813},[212],{"categories":3815},[],{"categories":3817},[70],{"categories":3819},[],{"categories":3821},[118],{"categories":3823},[70],{"categories":3825},[118],{"categories":3827},[],{"categories":3829},[118],{"categories":3831},[70],{"categories":3833},[132],{"categories":3835},[212],{"categories":3837},[157],{"categories":3839},[70],{"categories":3841},[157],{"categories":3843},[118],{"categories":3845},[212],{"categories":3847},[70],{"categories":3849},[],{"categories":3851},[70],{"categories":3853},[146],{"categories":3855},[118],{"categories":3857},[70],{"categories":3859},[212],{"categories":3861},[157],{"categories":3863},[70],{"categories":3865},[113],{"categories":3867},[132],{"categories":3869},[70],{"categories":3871},[70],{"categories":3873},[70],{"categories":3875},[70],{"categories":3877},[70],{"categories":3879},[157],{"categories":3881},[132],{"categories":3883},[243],{"categories":3885},[],{"categories":3887},[],{"categories":3889},[135],{"categories":3891},[471],{"categories":3893},[70],{"categories":3895},[118],{"categories":3897},[70,132],{"categories":3899},[157],{"categories":3901},[70],{"categories":3903},[70],{"categories":3905},[70],{"categories":3907},[70],{"categories":3909},[70],{"categories":3911},[70],{"categories":3913},[70],{"categories":3915},[118],{"categories":3917},[70],{"categories":3919},[70],{"categories":3921},[118],{"categories":3923},[70],{"categories":3925},[70],{"categories":3927},[70],{"categories":3929},[],{"categories":3931},[70],{"categories":3933},[1293],{"categories":3935},[132],{"categories":3937},[212],{"categories":3939},[70],{"categories":3941},[70],{"categories":3943},[70],{"categories":3945},[70],{"categories":3947},[135],{"categories":3949},[118],{"categories":3951},[243],{"categories":3953},[284],{"categories":3955},[],{"categories":3957},[132],{"categories":3959},[70],{"categories":3961},[113],{"categories":3963},[118],{"categories":3965},[70],{"categories":3967},[108],{"categories":3969},[118],{"categories":3971},[70],{"categories":3973},[118],{"categories":3975},[118],{"categories":3977},[121],{"categories":3979},[132],{"categories":3981},[70],{"categories":3983},[70],{"categories":3985},[],{"categories":3987},[],{"categories":3989},[],{"categories":3991},[284],{"categories":3993},[70],{"categories":3995},[157],{"categories":3997},[70],{"categories":3999},[70],{"categories":4001},[70],{"categories":4003},[70],{"categories":4005},[132],{"categories":4007},[70],{"categories":4009},[],{"categories":4011},[70],{"categories":4013},[135],{"categories":4015},[113],{"categories":4017},[118],{"categories":4019},[70],{"categories":4021},[],{"categories":4023},[70],{"categories":4025},[118],{"categories":4027},[132],{"categories":4029},[70],{"categories":4031},[70],{"categories":4033},[70],{"categories":4035},[284],{"categories":4037},[],{"categories":4039},[212],{"categories":4041},[212],{"categories":4043},[70],{"categories":4045},[118],{"categories":4047},[],{"categories":4049},[132],{"categories":4051},[70],{"categories":4053},[212],{"categories":4055},[70],{"categories":4057},[113],{"categories":4059},[118],{"categories":4061},[70],{"categories":4063},[],{"categories":4065},[157],{"categories":4067},[70],{"categories":4069},[70],{"categories":4071},[70],{"categories":4073},[70],{"categories":4075},[212],{"categories":4077},[118],{"categories":4079},[157],{"categories":4081},[],{"categories":4083},[118],{"categories":4085},[70],{"categories":4087},[113],{"categories":4089},[118],{"categories":4091},[212],{"categories":4093},[70],{"categories":4095},[70],{"categories":4097},[70],{"categories":4099},[471],{"categories":4101},[70],{"categories":4103},[118],{"categories":4105},[],{"categories":4107},[70],{"categories":4109},[70],{"categories":4111},[284],{"categories":4113},[157],{"categories":4115},[135],{"categories":4117},[586],{"categories":4119},[135],{"categories":4121},[135],{"categories":4123},[70],{"categories":4125},[],{"categories":4127},[],{"categories":4129},[],{"categories":4131},[118],{"categories":4133},[70],{"categories":4135},[70],{"categories":4137},[118],{"categories":4139},[118],{"categories":4141},[132],{"categories":4143},[70],{"categories":4145},[446],{"categories":4147},[132],{"categories":4149},[70],{"categories":4151},[118],{"categories":4153},[70],{"categories":4155},[70],{"categories":4157},[70],{"categories":4159},[113],{"categories":4161},[70],{"categories":4163},[70],{"categories":4165},[70],{"categories":4167},[118],{"categories":4169},[70],{"categories":4171},[],{"categories":4173},[],{"categories":4175},[70],{"categories":4177},[],{"categories":4179},[70],{"categories":4181},[118],{"categories":4183},[212],{"categories":4185},[70],{"categories":4187},[70],{"categories":4189},[118],{"categories":4191},[],{"categories":4193},[118],{"categories":4195},[70],{"categories":4197},[70],{"categories":4199},[121],{"categories":4201},[70],{"categories":4203},[212],{"categories":4205},[70],{"categories":4207},[118],{"categories":4209},[113],{"categories":4211},[70],{"categories":4213},[70],{"categories":4215},[70],{"categories":4217},[243],{"categories":4219},[118],{"categories":4221},[70],{"categories":4223},[70],{"categories":4225},[912],{"categories":4227},[70],{"categories":4229},[118],{"categories":4231},[70],{"categories":4233},[132],{"categories":4235},[70],{"categories":4237},[540],{"categories":4239},[212],{"categories":4241},[],{"categories":4243},[70],{"categories":4245},[70],{"categories":4247},[157],{"categories":4249},[471],{"categories":4251},[118],{"categories":4253},[70],{"categories":4255},[],{"categories":4257},[157],{"categories":4259},[390],{"categories":4261},[118],{"categories":4263},[118],{"categories":4265},[118],{"categories":4267},[70],{"categories":4269},[70],{"categories":4271},[118],{"categories":4273},[70],{"categories":4275},[],{"categories":4277},[113],{"categories":4279},[70],{"categories":4281},[212],{"categories":4283},[113],{"categories":4285},[118],{"categories":4287},[],{"categories":4289},[132],{"categories":4291},[70],{"categories":4293},[70],{"categories":4295},[108],{"categories":4297},[70],{"categories":4299},[157],{"categories":4301},[284],{"categories":4303},[146],{"categories":4305},[118],{"categories":4307},[118],{"categories":4309},[70],{"categories":4311},[70],{"categories":4313},[118],{"categories":4315},[70],{"categories":4317},[108],{"categories":4319},[],{"categories":4321},[118],{"categories":4323},[70],{"categories":4325},[70],{"categories":4327},[70],{"categories":4329},[118],{"categories":4331},[70],{"categories":4333},[],{"categories":4335},[70],{"categories":4337},[],{"categories":4339},[212],{"categories":4341},[118],{"categories":4343},[70,113],{"categories":4345},[118],{"categories":4347},[70],{"categories":4349},[],{"categories":4351},[108],{"categories":4353},[135],{"categories":4355},[113],{"categories":4357},[70],{"categories":4359},[132],{"categories":4361},[70],{"categories":4363},[70],{"categories":4365},[118],{"categories":4367},[70],{"categories":4369},[70],{"categories":4371},[70],{"categories":4373},[157],{"categories":4375},[1293],{"categories":4377},[118],{"categories":4379},[70],{"categories":4381},[],{"categories":4383},[],{"categories":4385},[70],{"categories":4387},[118],{"categories":4389},[70],{"categories":4391},[70],{"categories":4393},[284],{"categories":4395},[],{"categories":4397},[70],{"categories":4399},[118],{"categories":4401},[146],{"categories":4403},[118],{"categories":4405},[70],{"categories":4407},[471],{"categories":4409},[],{"categories":4411},[413],{"categories":4413},[70],{"categories":4415},[118],{"categories":4417},[70],{"categories":4419},[70],{"categories":4421},[70],{"categories":4423},[243],{"categories":4425},[70],{"categories":4427},[118],{"categories":4429},[70],{"categories":4431},[135],{"categories":4433},[121],{"categories":4435},[118],{"categories":4437},[70],{"categories":4439},[471],{"categories":4441},[70],{"categories":4443},[284],{"categories":4445},[113],{"categories":4447},[],{"categories":4449},[70],{"categories":4451},[70],{"categories":4453},[243],{"categories":4455},[212],{"categories":4457},[70],{"categories":4459},[70],{"categories":4461},[70],{"categories":4463},[],{"categories":4465},[243],{"categories":4467},[157],{"categories":4469},[70],{"categories":4471},[70],{"categories":4473},[70],{"categories":4475},[586],{"categories":4477},[108],{"categories":4479},[70],{"categories":4481},[121],{"categories":4483},[70],{"categories":4485},[70],{"categories":4487},[],{"categories":4489},[],{"categories":4491},[212],{"categories":4493},[70],{"categories":4495},[70],{"categories":4497},[135],{"categories":4499},[243],{"categories":4501},[118],{"categories":4503},[70],{"categories":4505},[70],{"categories":4507},[243],{"categories":4509},[157],{"categories":4511},[70],{"categories":4513},[],{"categories":4515},[70],{"categories":4517},[70],{"categories":4519},[],{"categories":4521},[70],{"categories":4523},[70],{"categories":4525},[613],{"categories":4527},[70],{"categories":4529},[70],{"categories":4531},[118],{"categories":4533},[132],{"categories":4535},[471],{"categories":4537},[70],{"categories":4539},[113],{"categories":4541},[70],{"categories":4543},[70],{"categories":4545},[],{"categories":4547},[70,132],{"categories":4549},[157],{"categories":4551},[118],{"categories":4553},[132],{"categories":4555},[118],{"categories":4557},[952],{"categories":4559},[132],{"categories":4561},[132],{"categories":4563},[118],{"categories":4565},[70],{"categories":4567},[108],{"categories":4569},[70],{"categories":4571},[],{"categories":4573},[],{"categories":4575},[118],{"categories":4577},[70],{"categories":4579},[132],{"categories":4581},[118],{"categories":4583},[70],{"categories":4585},[108],{"categories":4587},[132],{"categories":4589},[132],{"categories":4591},[70],{"categories":4593},[243],{"categories":4595},[70],{"categories":4597},[70],{"categories":4599},[132],{"categories":4601},[70],{"categories":4603},[],{"categories":4605},[70],{"categories":4607},[70],{"categories":4609},[212,70],{"categories":4611},[284],{"categories":4613},[108],{"categories":4615},[70],{"categories":4617},[],{"categories":4619},[70],{"categories":4621},[70],{"categories":4623},[113],{"categories":4625},[70],{"categories":4627},[113],{"categories":4629},[70],{"categories":4631},[70],{"categories":4633},[390],{"categories":4635},[70],{"categories":4637},[113],{"categories":4639},[132],{"categories":4641},[135],{"categories":4643},[118],{"categories":4645},[70],{"categories":4647},[132],{"categories":4649},[70],{"categories":4651},[70],{"categories":4653},[157],{"categories":4655},[243],{"categories":4657},[212],{"categories":4659},[70],{"categories":4661},[70],{"categories":4663},[121],{"categories":4665},[70],{"categories":4667},[70],{"categories":4669},[108],{"categories":4671},[70],{"categories":4673},[118],{"categories":4675},[118],{"categories":4677},[132],{"categories":4679},[70],{"categories":4681},[157],{"categories":4683},[132],{"categories":4685},[132],{"categories":4687},[70],{"categories":4689},[70],{"categories":4691},[],{"categories":4693},[],{"categories":4695},[135],{"categories":4697},[70],{"categories":4699},[132],{"categories":4701},[70],{"categories":4703},[212],{"categories":4705},[471],{"categories":4707},[413],{"categories":4709},[390],{"categories":4711},[70],{"categories":4713},[70],{"categories":4715},[132],{"categories":4717},[70],{"categories":4719},[135],{"categories":4721},[70],{"categories":4723},[70],{"categories":4725},[70],{"categories":4727},[70],{"categories":4729},[70],{"categories":4731},[70],{"categories":4733},[70],{"categories":4735},[118],{"categories":4737},[108],{"categories":4739},[118],{"categories":4741},[70,113],{"categories":4743},[],{"categories":4745},[212],{"categories":4747},[],{"categories":4749},[121],{"categories":4751},[70],{"categories":4753},[157],{"categories":4755},[108],{"categories":4757},[70],{"categories":4759},[108],{"categories":4761},[118],{"categories":4763},[135],{"categories":4765},[118],{"categories":4767},[113],{"categories":4769},[121],{"categories":4771},[70],{"categories":4773},[118],{"categories":4775},[70],{"categories":4777},[70],{"categories":4779},[70],{"categories":4781},[113],{"categories":4783},[118],{"categories":4785},[132],{"categories":4787},[243],{"categories":4789},[70],{"categories":4791},[70],{"categories":4793},[],{"categories":4795},[157],{"categories":4797},[70],{"categories":4799},[70],{"categories":4801},[70],{"categories":4803},[70],{"categories":4805},[70],{"categories":4807},[70],{"categories":4809},[132],{"categories":4811},[157],{"categories":4813},[132],{"categories":4815},[132],{"categories":4817},[70],{"categories":4819},[70],{"categories":4821},[70],{"categories":4823},[70],{"categories":4825},[413],{"categories":4827},[70],{"categories":4829},[118],{"categories":4831},[118],{"categories":4833},[157],{"categories":4835},[70],{"categories":4837},[70],{"categories":4839},[70],{"categories":4841},[118],{"categories":4843},[70],{"categories":4845},[70],{"categories":4847},[70],{"categories":4849},[3330],{"categories":4851},[4852],"Clinical AI",{"categories":4854},[212],{"categories":4856},[70],{"categories":4858},[70],{"categories":4860},[70],{"categories":4862},[70],{"categories":4864},[284],{"categories":4866},[2651],{"categories":4868},[70],{"categories":4870},[121],{"categories":4872},[212],{"categories":4874},[70],{"categories":4876},[118],{"categories":4878},[70],{"categories":4880},[70],{"categories":4882},[157],{"categories":4884},[70],{"categories":4886},[118],{"categories":4888},[132],{"categories":4890},[243],{"categories":4892},[70],{"categories":4894},[70],{"categories":4896},[113],{"categories":4898},[70],{"categories":4900},[70],{"categories":4902},[540],{"categories":4904},[70],{"categories":4906},[],{"categories":4908},[118],{"categories":4910},[70],{"categories":4912},[132],{"categories":4914},[108],{"categories":4916},[70],{"categories":4918},[],{"categories":4920},[],{"categories":4922},[70],{"categories":4924},[],{"categories":4926},[113],{"categories":4928},[70],{"categories":4930},[70],{"categories":4932},[118],{"categories":4934},[70],{"categories":4936},[157],{"categories":4938},[157],{"categories":4940},[157],{"categories":4942},[157],{"categories":4944},[],{"categories":4946},[108],{"categories":4948},[118],{"categories":4950},[157],{"categories":4952},[70],{"categories":4954},[613],{"categories":4956},[121],{"categories":4958},[118],{"categories":4960},[70],{"categories":4962},[108],{"categories":4964},[70],{"categories":4966},[118],{"categories":4968},[70],{"categories":4970},[70],{"categories":4972},[70],{"categories":4974},[70],{"categories":4976},[70,118],{"categories":4978},[118],{"categories":4980},[284],{"categories":4982},[157],{"categories":4984},[118],{"categories":4986},[157],{"categories":4988},[118],{"categories":4990},[70],{"categories":4992},[],{"categories":4994},[157],{"categories":4996},[243],{"categories":4998},[108],{"categories":5000},[70],{"categories":5002},[70],{"categories":5004},[],{"categories":5006},[132],{"categories":5008},[],{"categories":5010},[108],{"categories":5012},[118],{"categories":5014},[157],{"categories":5016},[70],{"categories":5018},[157],{"categories":5020},[108],{"categories":5022},[157],{"categories":5024},[157],{"categories":5026},[],{"categories":5028},[113],{"categories":5030},[118],{"categories":5032},[157],{"categories":5034},[157],{"categories":5036},[157],{"categories":5038},[157],{"categories":5040},[157],{"categories":5042},[157],{"categories":5044},[157],{"categories":5046},[157],{"categories":5048},[157],{"categories":5050},[157],{"categories":5052},[135],{"categories":5054},[108],{"categories":5056},[70],{"categories":5058},[70],{"categories":5060},[118],{"categories":5062},[118],{"categories":5064},[],{"categories":5066},[70],{"categories":5068},[70,108],{"categories":5070},[],{"categories":5072},[118],{"categories":5074},[70],{"categories":5076},[157],{"categories":5078},[118],{"categories":5080},[118],{"categories":5082},[952],{"categories":5084},[70],{"categories":5086},[70],{"categories":5088},[70],{"categories":5090},[70],{"categories":5092},[121],{"categories":5094},[70],{"categories":5096},[70],{"categories":5098},[390],{"categories":5100},[70],{"categories":5102},[70],{"categories":5104},[118],{"categories":5106},[70],{"categories":5108},[70],{"categories":5110},[70],{"categories":5112},[113],{"categories":5114},[121],{"categories":5116},[118],{"categories":5118},[118],{"categories":5120},[],{"categories":5122},[118],{"categories":5124},[212],{"categories":5126},[157],{"categories":5128},[70],{"categories":5130},[],{"categories":5132},[121],{"categories":5134},[],{"categories":5136},[132],{"categories":5138},[70],{"categories":5140},[118],{"categories":5142},[212],{"categories":5144},[70],{"categories":5146},[70],{"categories":5148},[],{"categories":5150},[70],{"categories":5152},[70],{"categories":5154},[],{"categories":5156},[243],{"categories":5158},[70],{"categories":5160},[118],{"categories":5162},[],{"categories":5164},[],{"categories":5166},[157],{"categories":5168},[108],{"categories":5170},[70],{"categories":5172},[70],{"categories":5174},[113],{"categories":5176},[70],{"categories":5178},[70],{"categories":5180},[118],{"categories":5182},[70],{"categories":5184},[113],{"categories":5186},[113],{"categories":5188},[212],{"categories":5190},[],{"categories":5192},[70],{"categories":5194},[157],{"categories":5196},[],{"categories":5198},[70],{"categories":5200},[70],{"categories":5202},[212],{"categories":5204},[70],{"categories":5206},[70],{"categories":5208},[243],{"categories":5210},[70],{"categories":5212},[284],{"categories":5214},[],{"categories":5216},[118],{"categories":5218},[70],{"categories":5220},[243],{"categories":5222},[132],{"categories":5224},[],{"categories":5226},[70],{"categories":5228},[],{"categories":5230},[118],{"categories":5232},[212],{"categories":5234},[132],{"categories":5236},[],{"categories":5238},[3330],{"categories":5240},[113],{"categories":5242},[108],{"categories":5244},[70],{"categories":5246},[135],{"categories":5248},[118],{"categories":5250},[212],{"categories":5252},[70],{"categories":5254},[70],{"categories":5256},[132],{"categories":5258},[],{"categories":5260},[],{"categories":5262},[70],{"categories":5264},[108],{"categories":5266},[70],{"categories":5268},[243],{"categories":5270},[],{"categories":5272},[118],{"categories":5274},[118],{"categories":5276},[70],{"categories":5278},[118],{"categories":5280},[70],{"categories":5282},[157],{"categories":5284},[70],{"categories":5286},[132],{"categories":5288},[70],{"categories":5290},[118],{"categories":5292},[121],{"categories":5294},[70],{"categories":5296},[70],{"categories":5298},[70],{"categories":5300},[70],{"categories":5302},[118],{"categories":5304},[70],{"categories":5306},[121],{"categories":5308},[243],{"categories":5310},[157],{"categories":5312},[],{"categories":5314},[243],{"categories":5316},[70],{"categories":5318},[],{"categories":5320},[132],{"categories":5322},[118],{"categories":5324},[],{"categories":5326},[70],{"categories":5328},[70],{"categories":5330},[70],{"categories":5332},[70],{"categories":5334},[70],{"categories":5336},[118],{"categories":5338},[113],{"categories":5340},[108],{"categories":5342},[70],{"categories":5344},[70],{"categories":5346},[118],{"categories":5348},[70],{"categories":5350},[212],{"categories":5352},[132],{"categories":5354},[132],{"categories":5356},[70],{"categories":5358},[135],{"categories":5360},[118],{"categories":5362},[70],{"categories":5364},[70],{"categories":5366},[118],{"categories":5368},[70],{"categories":5370},[70],{"categories":5372},[118],{"categories":5374},[113],{"categories":5376},[70],{"categories":5378},[212],{"categories":5380},[132],{"categories":5382},[118],{"categories":5384},[70],{"categories":5386},[121],{"categories":5388},[70],{"categories":5390},[118],{"categories":5392},[70],{"categories":5394},[70],{"categories":5396},[157],{"categories":5398},[70],{"categories":5400},[],{"categories":5402},[108],{"categories":5404},[70],{"categories":5406},[70],{"categories":5408},[70],{"categories":5410},[132],{"categories":5412},[132],{"categories":5414},[70],{"categories":5416},[132],{"categories":5418},[70],{"categories":5420},[118],{"categories":5422},[70],{"categories":5424},[70],{"categories":5426},[70],{"categories":5428},[70],{"categories":5430},[70],{"categories":5432},[],{"categories":5434},[70],{"categories":5436},[212],{"categories":5438},[118],{"categories":5440},[113],{"categories":5442},[157],{"categories":5444},[70],{"categories":5446},[118],{"categories":5448},[70],{"categories":5450},[118],{"categories":5452},[70],{"categories":5454},[70],{"categories":5456},[212],{"categories":5458},[118],{"categories":5460},[70],{"categories":5462},[243],{"categories":5464},[113],{"categories":5466},[70],{"categories":5468},[135],{"categories":5470},[70],{"categories":5472},[70],{"categories":5474},[157],{"categories":5476},[70],{"categories":5478},[70],{"categories":5480},[70],{"categories":5482},[70],{"categories":5484},[118],{"categories":5486},[284],{"categories":5488},[70],{"categories":5490},[132],{"categories":5492},[118],{"categories":5494},[135],{"categories":5496},[],{"categories":5498},[118],{"categories":5500},[132],{"categories":5502},[70],{"categories":5504},[70],{"categories":5506},[70],{"categories":5508},[2477],{"categories":5510},[70],{"categories":5512},[212],{"categories":5514},[319],{"categories":5516},[70],{"categories":5518},[70],{"categories":5520},[70],{"categories":5522},[70],{"categories":5524},[70],{"categories":5526},[108],{"categories":5528},[118],{"categories":5530},[70],{"categories":5532},[70],{"categories":5534},[132],{"categories":5536},[113],{"categories":5538},[70],{"categories":5540},[132],{"categories":5542},[70],{"categories":5544},[],{"categories":5546},[118],{"categories":5548},[118],{"categories":5550},[70],{"categories":5552},[70],{"categories":5554},[70],{"categories":5556},[135],{"categories":5558},[],{"categories":5560},[157],{"categories":5562},[],{"categories":5564},[157],{"categories":5566},[70],{"categories":5568},[70],{"categories":5570},[70],{"categories":5572},[118],{"categories":5574},[70],{"categories":5576},[118],{"categories":5578},[118],{"categories":5580},[],{"categories":5582},[70],{"categories":5584},[157],{"categories":5586},[70],{"categories":5588},[],{"categories":5590},[70],{"categories":5592},[70],{"categories":5594},[],{"categories":5596},[70],{"categories":5598},[70],{"categories":5600},[212],{"categories":5602},[132],{"categories":5604},[118],{"categories":5606},[70],{"categories":5608},[70],{"categories":5610},[70],{"categories":5612},[70],{"categories":5614},[243],{"categories":5616},[70],{"categories":5618},[70],{"categories":5620},[70],{"categories":5622},[108],{"categories":5624},[70],{"categories":5626},[70],{"categories":5628},[],{"categories":5630},[70],{"categories":5632},[70],{"categories":5634},[70],{"categories":5636},[],{"categories":5638},[108],{"categories":5640},[70],{"categories":5642},[70],{"categories":5644},[70],{"categories":5646},[157],{"categories":5648},[70],{"categories":5650},[132],{"categories":5652},[121],{"categories":5654},[118],{"categories":5656},[471],{"categories":5658},[70],{"categories":5660},[70],{"categories":5662},[70],{"categories":5664},[132],{"categories":5666},[157],{"categories":5668},[212],{"categories":5670},[70],{"categories":5672},[70],{"categories":5674},[70],{"categories":5676},[70],{"categories":5678},[70],{"categories":5680},[70],{"categories":5682},[157],{"categories":5684},[70],{"categories":5686},[212],{"categories":5688},[70],{"categories":5690},[70],{"categories":5692},[157],{"categories":5694},[212],{"categories":5696},[70],{"categories":5698},[157],{"categories":5700},[70],{"categories":5702},[118],{"categories":5704},[118],{"categories":5706},[118],{"categories":5708},[132],{"categories":5710},[157],{"categories":5712},[118],{"categories":5714},[118],{"categories":5716},[70],{"categories":5718},[132],{"categories":5720},[212],{"categories":5722},[70],{"categories":5724},[70],{"categories":5726},[118],{"categories":5728},[70],{"categories":5730},[],{"categories":5732},[118],{"categories":5734},[],{"categories":5736},[70],{"categories":5738},[70],{"categories":5740},[],{"categories":5742},[],{"categories":5744},[118],{"categories":5746},[113],{"categories":5748},[118],{"categories":5750},[5751],"Liability & Ethics",{"categories":5753},[70],{"categories":5755},[70],{"categories":5757},[70],{"categories":5759},[118],{"categories":5761},[108],{"categories":5763},[118],{"categories":5765},[113],{"categories":5767},[243],{"categories":5769},[70],{"categories":5771},[118],{"categories":5773},[70],{"categories":5775},[70],{"categories":5777},[70],{"categories":5779},[],{"categories":5781},[586],{"categories":5783},[118],{"categories":5785},[],{"categories":5787},[70],{"categories":5789},[108],{"categories":5791},[118],{"categories":5793},[70],{"categories":5795},[],{"categories":5797},[118],{"categories":5799},[70],{"categories":5801},[70],{"categories":5803},[132],{"categories":5805},[70],{"categories":5807},[157],{"categories":5809},[70],{"categories":5811},[70],{"categories":5813},[121],{"categories":5815},[70],{"categories":5817},[118],{"categories":5819},[70],{"categories":5821},[70],{"categories":5823},[70],{"categories":5825},[157],{"categories":5827},[118],{"categories":5829},[132],{"categories":5831},[212],{"categories":5833},[108],{"categories":5835},[70],{"categories":5837},[70],{"categories":5839},[70],{"categories":5841},[],{"categories":5843},[118],{"categories":5845},[118],{"categories":5847},[118],{"categories":5849},[471],{"categories":5851},[212],{"categories":5853},[118],{"categories":5855},[284],{"categories":5857},[132],{"categories":5859},[157],{"categories":5861},[70],{"categories":5863},[212],{"categories":5865},[70],{"categories":5867},[108],{"categories":5869},[],{"categories":5871},[118],{"categories":5873},[70],{"categories":5875},[70],{"categories":5877},[70],{"categories":5879},[70],{"categories":5881},[118],{"categories":5883},[70],{"categories":5885},[70],{"categories":5887},[212],{"categories":5889},[118],{"categories":5891},[],{"categories":5893},[118],{"categories":5895},[121],{"categories":5897},[70],{"categories":5899},[157],{"categories":5901},[118],{"categories":5903},[113],{"categories":5905},[],{"categories":5907},[70],{"categories":5909},[70],{"categories":5911},[121],{"categories":5913},[70],{"categories":5915},[118],{"categories":5917},[157],{"categories":5919},[108],{"categories":5921},[284],{"categories":5923},[70],{"categories":5925},[70],{"categories":5927},[70],{"categories":5929},[157],{"categories":5931},[113],{"categories":5933},[70],{"categories":5935},[212],{"categories":5937},[157],{"categories":5939},[284],{"categories":5941},[70],{"categories":5943},[118],{"categories":5945},[],{"categories":5947},[540],{"categories":5949},[],{"categories":5951},[70],{"categories":5953},[284],{"categories":5955},[70],{"categories":5957},[135],{"categories":5959},[70],{"categories":5961},[118],{"categories":5963},[118],{"categories":5965},[5966],"Design News & Tools",{"categories":5968},[70],{"categories":5970},[70],{"categories":5972},[157],{"categories":5974},[70],{"categories":5976},[70],{"categories":5978},[70],{"categories":5980},[108],{"categories":5982},[118],{"categories":5984},[70],{"categories":5986},[212],{"categories":5988},[118],{"categories":5990},[118],{"categories":5992},[212],{"categories":5994},[70],{"categories":5996},[70],{"categories":5998},[70],{"categories":6000},[471],{"categories":6002},[118],{"categories":6004},[70],{"categories":6006},[70],{"categories":6008},[70],{"categories":6010},[471],{"categories":6012},[70],{"categories":6014},[243],{"categories":6016},[70],{"categories":6018},[118],{"categories":6020},[],{"categories":6022},[70],{"categories":6024},[70],{"categories":6026},[70],{"categories":6028},[157],{"categories":6030},[70],{"categories":6032},[108],{"categories":6034},[],{"categories":6036},[70],{"categories":6038},[70],{"categories":6040},[70],{"categories":6042},[132],{"categories":6044},[613],{"categories":6046},[132],{"categories":6048},[212],{"categories":6050},[70],{"categories":6052},[70,118],{"categories":6054},[243,113],{"categories":6056},[132],{"categories":6058},[70],{"categories":6060},[70],{"categories":6062},[70],{"categories":6064},[70],{"categories":6066},[],{"categories":6068},[132],{"categories":6070},[118],{"categories":6072},[70],{"categories":6074},[70],{"categories":6076},[],{"categories":6078},[70],{"categories":6080},[132],{"categories":6082},[70],{"categories":6084},[132],{"categories":6086},[70],{"categories":6088},[],{"categories":6090},[118],{"categories":6092},[70],{"categories":6094},[113],{"categories":6096},[70],{"categories":6098},[157],{"categories":6100},[70],{"categories":6102},[],{"categories":6104},[70],{"categories":6106},[118],{"categories":6108},[70],{"categories":6110},[],{"categories":6112},[212],{"categories":6114},[70],{"categories":6116},[70],{"categories":6118},[118],{"categories":6120},[70],{"categories":6122},[70],{"categories":6124},[70],{"categories":6126},[108],{"categories":6128},[70],{"categories":6130},[118],{"categories":6132},[70],{"categories":6134},[],{"categories":6136},[70],{"categories":6138},[284],{"categories":6140},[243],{"categories":6142},[113],{"categories":6144},[113],{"categories":6146},[70],{"categories":6148},[108],{"categories":6150},[108],{"categories":6152},[70],{"categories":6154},[118],{"categories":6156},[70],{"categories":6158},[70],{"categories":6160},[70],{"categories":6162},[70],{"categories":6164},[132],{"categories":6166},[70],{"categories":6168},[108],{"categories":6170},[70],{"categories":6172},[70],{"categories":6174},[118],{"categories":6176},[70],{"categories":6178},[243],{"categories":6180},[70],{"categories":6182},[157],{"categories":6184},[70],{"categories":6186},[70],{"categories":6188},[118],{"categories":6190},[121],{"categories":6192},[70],{"categories":6194},[118],{"categories":6196},[70],{"categories":6198},[118],{"categories":6200},[],{"categories":6202},[132],{"categories":6204},[],{"categories":6206},[132],{"categories":6208},[118],{"categories":6210},[108],{"categories":6212},[70],{"categories":6214},[],{"categories":6216},[135],{"categories":6218},[284],{"categories":6220},[70],{"categories":6222},[132],{"categories":6224},[70],{"categories":6226},[],{"categories":6228},[157],{"categories":6230},[118],{"categories":6232},[132],{"categories":6234},[212],{"categories":6236},[113],{"categories":6238},[70],{"categories":6240},[70],{"categories":6242},[118],{"categories":6244},[132],{"categories":6246},[118],{"categories":6248},[157],{"categories":6250},[70],{"categories":6252},[121],{"categories":6254},[108],{"categories":6256},[121],{"categories":6258},[157],{"categories":6260},[70],{"categories":6262},[132],{"categories":6264},[70],{"categories":6266},[212],{"categories":6268},[113],{"categories":6270},[70],{"categories":6272},[70],{"categories":6274},[70],{"categories":6276},[70],{"categories":6278},[70],{"categories":6280},[70],{"categories":6282},[118],{"categories":6284},[70],{"categories":6286},[70],{"categories":6288},[118],{"categories":6290},[70],{"categories":6292},[70],{"categories":6294},[108],{"categories":6296},[70],{"categories":6298},[118],{"categories":6300},[118],{"categories":6302},[212],{"categories":6304},[118],{"categories":6306},[70],{"categories":6308},[118],{"categories":6310},[70],{"categories":6312},[108],{"categories":6314},[118],{"categories":6316},[212],{"categories":6318},[],{"categories":6320},[70],{"categories":6322},[135],{"categories":6324},[471],{"categories":6326},[70],{"categories":6328},[118],{"categories":6330},[70],{"categories":6332},[70],{"categories":6334},[132],{"categories":6336},[70],{"categories":6338},[],{"categories":6340},[70],{"categories":6342},[118],{"categories":6344},[70],{"categories":6346},[243],{"categories":6348},[212],{"categories":6350},[70],{"categories":6352},[132],{"categories":6354},[70],{"categories":6356},[157],{"categories":6358},[118],{"categories":6360},[70],{"categories":6362},[243],{"categories":6364},[118],{"categories":6366},[113],{"categories":6368},[113],{"categories":6370},[70],{"categories":6372},[70],{"categories":6374},[70],{"categories":6376},[70],{"categories":6378},[70],{"categories":6380},[70],{"categories":6382},[108],{"categories":6384},[70],{"categories":6386},[],{"categories":6388},[70],{"categories":6390},[70],{"categories":6392},[118],{"categories":6394},[70],{"categories":6396},[118],{"categories":6398},[70],{"categories":6400},[70],{"categories":6402},[70],{"categories":6404},[70],{"categories":6406},[70],{"categories":6408},[70],{"categories":6410},[132],{"categories":6412},[],{"categories":6414},[108],{"categories":6416},[70],{"categories":6418},[70],{"categories":6420},[118],{"categories":6422},[118],{"categories":6424},[],{"categories":6426},[132],{"categories":6428},[132],{"categories":6430},[70],{"categories":6432},[243],{"categories":6434},[113],{"categories":6436},[212],{"categories":6438},[70],{"categories":6440},[],{"categories":6442},[70],{"categories":6444},[118],{"categories":6446},[108],{"categories":6448},[70],{"categories":6450},[70],{"categories":6452},[132],{"categories":6454},[108],{"categories":6456},[70],{"categories":6458},[70],{"categories":6460},[157],{"categories":6462},[135],{"categories":6464},[70],{"categories":6466},[157],{"categories":6468},[118],{"categories":6470},[70],{"categories":6472},[],{"categories":6474},[157],{"categories":6476},[118],{"categories":6478},[212],{"categories":6480},[135],{"categories":6482},[70],{"categories":6484},[70],{"categories":6486},[70],{"categories":6488},[],{"categories":6490},[118],{"categories":6492},[118],{"categories":6494},[118],{"categories":6496},[3330],{"categories":6498},[157],{"categories":6500},[70],{"categories":6502},[132],{"categories":6504},[70],{"categories":6506},[70],{"categories":6508},[70],{"categories":6510},[70],{"categories":6512},[70],{"categories":6514},[118],{"categories":6516},[70],{"categories":6518},[113],{"categories":6520},[70],{"categories":6522},[108],{"categories":6524},[1901],{"categories":6526},[284],{"categories":6528},[108],{"categories":6530},[],{"categories":6532},[70],{"categories":6534},[],{"categories":6536},[70],{"categories":6538},[157],{"categories":6540},[118],{"categories":6542},[212],{"categories":6544},[70],{"categories":6546},[70],{"categories":6548},[70],{"categories":6550},[70],{"categories":6552},[70],{"categories":6554},[157],{"categories":6556},[],{"categories":6558},[118],{"categories":6560},[70],{"categories":6562},[118],{"categories":6564},[118],{"categories":6566},[],{"categories":6568},[70],{"categories":6570},[],{"categories":6572},[157],{"categories":6574},[108],{"categories":6576},[70],{"categories":6578},[212],{"categories":6580},[70],{"categories":6582},[118],{"categories":6584},[157],{"categories":6586},[70],{"categories":6588},[157],{"categories":6590},[],{"categories":6592},[157],{"categories":6594},[70],{"categories":6596},[108],{"categories":6598},[118],{"categories":6600},[471],{"categories":6602},[118],{"categories":6604},[70],{"categories":6606},[],{"categories":6608},[132],{"categories":6610},[118],{"categories":6612},[121],{"categories":6614},[118],{"categories":6616},[108],{"categories":6618},[70],{"categories":6620},[70],{"categories":6622},[],{"categories":6624},[],{"categories":6626},[],{"categories":6628},[212],{"categories":6630},[70],{"categories":6632},[118],{"categories":6634},[70],{"categories":6636},[70],{"categories":6638},[],{"categories":6640},[],{"categories":6642},[],{"categories":6644},[70],{"categories":6646},[118],{"categories":6648},[212],{"categories":6650},[70],{"categories":6652},[],{"categories":6654},[118],{"categories":6656},[70],{"categories":6658},[70],{"categories":6660},[108],{"categories":6662},[],{"categories":6664},[],{"categories":6666},[70],{"categories":6668},[70],{"categories":6670},[118],{"categories":6672},[212],{"categories":6674},[70],{"categories":6676},[157],{"categories":6678},[],{"categories":6680},[70],{"categories":6682},[70],{"categories":6684},[243],{"categories":6686},[157],{"categories":6688},[243],{"categories":6690},[132],{"categories":6692},[135],{"categories":6694},[70],{"categories":6696},[70],{"categories":6698},[],{"categories":6700},[],{"categories":6702},[118],{"categories":6704},[],{"categories":6706},[70],{"categories":6708},[471],{"categories":6710},[70],{"categories":6712},[70],{"categories":6714},[70],{"categories":6716},[70],{"categories":6718},[],{"categories":6720},[118],{"categories":6722},[70],{"categories":6724},[70],{"categories":6726},[],{"categories":6728},[118],{"categories":6730},[118],{"categories":6732},[70],{"categories":6734},[157],{"categories":6736},[70],{"categories":6738},[243],{"categories":6740},[70],{"categories":6742},[118],{"categories":6744},[113],{"categories":6746},[121],{"categories":6748},[70],{"categories":6750},[70],{"categories":6752},[118],{"categories":6754},[135],{"categories":6756},[118],{"categories":6758},[118],{"categories":6760},[],{"categories":6762},[70],{"categories":6764},[118],{"categories":6766},[],{"categories":6768},[70],{"categories":6770},[],{"categories":6772},[157],{"categories":6774},[113],{"categories":6776},[],{"categories":6778},[70],{"categories":6780},[70],{"categories":6782},[70],{"categories":6784},[],{"categories":6786},[118],{"categories":6788},[212],{"categories":6790},[108],{"categories":6792},[70],{"categories":6794},[],{"categories":6796},[113],{"categories":6798},[243],{"categories":6800},[70],{"categories":6802},[132],{"categories":6804},[108],{"categories":6806},[135],{"categories":6808},[113],{"categories":6810},[132],{"categories":6812},[118],{"categories":6814},[132],{"categories":6816},[],{"categories":6818},[70],{"categories":6820},[121],{"categories":6822},[121],{"categories":6824},[70],{"categories":6826},[],{"categories":6828},[118],{"categories":6830},[118],{"categories":6832},[108],{"categories":6834},[212],{"categories":6836},[70],{"categories":6838},[108],{"categories":6840},[118],{"categories":6842},[284],{"categories":6844},[70],{"categories":6846},[70],{"categories":6848},[70],{"categories":6850},[70],{"categories":6852},[70],{"categories":6854},[108],{"categories":6856},[70],{"categories":6858},[132],{"categories":6860},[135],{"categories":6862},[118],{"categories":6864},[],{"categories":6866},[70],{"categories":6868},[70],{"categories":6870},[70],{"categories":6872},[132],{"categories":6874},[118],{"categories":6876},[157],{"categories":6878},[132],{"categories":6880},[70],{"categories":6882},[121],{"categories":6884},[],{"categories":6886},[212],{"categories":6888},[132],{"categories":6890},[157],{"categories":6892},[70],{"categories":6894},[108],{"categories":6896},[118],{"categories":6898},[70],{"categories":6900},[70],{"categories":6902},[118],{"categories":6904},[121],{"categories":6906},[70],{"categories":6908},[118],{"categories":6910},[70],{"categories":6912},[113],{"categories":6914},[70],{"categories":6916},[118],{"categories":6918},[118,284],{"categories":6920},[70],{"categories":6922},[70],{"categories":6924},[118],{"categories":6926},[132],{"categories":6928},[70],{"categories":6930},[70],{"categories":6932},[135],{"categories":6934},[118],{"categories":6936},[243],{"categories":6938},[118],{"categories":6940},[113],{"categories":6942},[],{"categories":6944},[118],{"categories":6946},[70],{"categories":6948},[113],{"categories":6950},[],{"categories":6952},[],{"categories":6954},[70],{"categories":6956},[132],{"categories":6958},[70],{"categories":6960},[70],{"categories":6962},[118],{"categories":6964},[135],{"categories":6966},[243],{"categories":6968},[70],{"categories":6970},[70],{"categories":6972},[70],{"categories":6974},[70],{"categories":6976},[118],{"categories":6978},[],{"categories":6980},[118],{"categories":6982},[157],{"categories":6984},[70],{"categories":6986},[118],{"categories":6988},[118],{"categories":6990},[70],{"categories":6992},[],{"categories":6994},[157],{"categories":6996},[132],{"categories":6998},[3330],{"categories":7000},[108],{"categories":7002},[132],{"categories":7004},[70],{"categories":7006},[118],{"categories":7008},[70],{"categories":7010},[70],{"categories":7012},[243],{"categories":7014},[132],{"categories":7016},[135],{"categories":7018},[],{"categories":7020},[157],{"categories":7022},[70],{"categories":7024},[70],{"categories":7026},[],{"categories":7028},[118],{"categories":7030},[70],{"categories":7032},[70],{"categories":7034},[70],{"categories":7036},[70],{"categories":7038},[118],{"categories":7040},[70],{"categories":7042},[70],{"categories":7044},[70],{"categories":7046},[121],{"categories":7048},[70],{"categories":7050},[118],{"categories":7052},[70],{"categories":7054},[70],{"categories":7056},[70],{"categories":7058},[70],{"categories":7060},[70],{"categories":7062},[70],{"categories":7064},[70],{"categories":7066},[113],{"categories":7068},[],{"categories":7070},[121],{"categories":7072},[70],{"categories":7074},[157],{"categories":7076},[118],{"categories":7078},[70],{"categories":7080},[132],{"categories":7082},[],{"categories":7084},[132],{"categories":7086},[132],{"categories":7088},[118],{"categories":7090},[132],{"categories":7092},[70],{"categories":7094},[70],{"categories":7096},[70],{"categories":7098},[118],{"categories":7100},[132],{"categories":7102},[70],{"categories":7104},[70],{"categories":7106},[70],{"categories":7108},[118],{"categories":7110},[157],{"categories":7112},[70],{"categories":7114},[70],{"categories":7116},[70],{"categories":7118},[113],{"categories":7120},[70],{"categories":7122},[118],{"categories":7124},[212],{"categories":7126},[],{"categories":7128},[70],{"categories":7130},[70],{"categories":7132},[135],{"categories":7134},[70],{"categories":7136},[118],{"categories":7138},[70],{"categories":7140},[70],{"categories":7142},[],{"categories":7144},[70],{"categories":7146},[70],{"categories":7148},[157],{"categories":7150},[70],{"categories":7152},[70],{"categories":7154},[118],{"categories":7156},[243],{"categories":7158},[],{"categories":7160},[],{"categories":7162},[132],{"categories":7164},[70],{"categories":7166},[70],{"categories":7168},[157],{"categories":7170},[70],{"categories":7172},[132],{"categories":7174},[157],{"categories":7176},[70],{"categories":7178},[70],{"categories":7180},[243],{"categories":7182},[135],{"categories":7184},[70],{"categories":7186},[70],{"categories":7188},[108],{"categories":7190},[118],{"categories":7192},[70],{"categories":7194},[70],{"categories":7196},[118],{"categories":7198},[113],{"categories":7200},[118],{"categories":7202},[132],{"categories":7204},[70],{"categories":7206},[113],{"categories":7208},[],{"categories":7210},[70],{"categories":7212},[135],{"categories":7214},[70],{"categories":7216},[70],{"categories":7218},[],{"categories":7220},[157],{"categories":7222},[70],{"categories":7224},[118],{"categories":7226},[135],{"categories":7228},[70],{"categories":7230},[132],{"categories":7232},[132],{"categories":7234},[132],{"categories":7236},[70],{"categories":7238},[118],{"categories":7240},[118],{"categories":7242},[70],{"categories":7244},[118],{"categories":7246},[70],{"categories":7248},[70],{"categories":7250},[212],{"categories":7252},[135],{"categories":7254},[135],{"categories":7256},[],{"categories":7258},[157],{"categories":7260},[70],{"categories":7262},[70],{"categories":7264},[132],{"categories":7266},[],{"categories":7268},[157],{"categories":7270},[157],{"categories":7272},[157],{"categories":7274},[],{"categories":7276},[118],{"categories":7278},[70],{"categories":7280},[],{"categories":7282},[108],{"categories":7284},[113],{"categories":7286},[],{"categories":7288},[70],{"categories":7290},[70],{"categories":7292},[],{"categories":7294},[132],{"categories":7296},[],{"categories":7298},[],{"categories":7300},[],{"categories":7302},[],{"categories":7304},[70],{"categories":7306},[157],{"categories":7308},[],{"categories":7310},[],{"categories":7312},[70],{"categories":7314},[70],{"categories":7316},[70],{"categories":7318},[135],{"categories":7320},[70],{"categories":7322},[135],{"categories":7324},[],{"categories":7326},[135],{"categories":7328},[135],{"categories":7330},[284],{"categories":7332},[118],{"categories":7334},[132],{"categories":7336},[],{"categories":7338},[],{"categories":7340},[135],{"categories":7342},[132],{"categories":7344},[132],{"categories":7346},[132],{"categories":7348},[],{"categories":7350},[108],{"categories":7352},[132],{"categories":7354},[132],{"categories":7356},[108],{"categories":7358},[132],{"categories":7360},[113],{"categories":7362},[132],{"categories":7364},[132],{"categories":7366},[132],{"categories":7368},[135],{"categories":7370},[157],{"categories":7372},[157],{"categories":7374},[70],{"categories":7376},[132],{"categories":7378},[135],{"categories":7380},[284],{"categories":7382},[135],{"categories":7384},[135],{"categories":7386},[135],{"categories":7388},[],{"categories":7390},[113],{"categories":7392},[],{"categories":7394},[284],{"categories":7396},[132],{"categories":7398},[132],{"categories":7400},[132],{"categories":7402},[118],{"categories":7404},[157,113],{"categories":7406},[135],{"categories":7408},[],{"categories":7410},[],{"categories":7412},[135],{"categories":7414},[],{"categories":7416},[135],{"categories":7418},[157],{"categories":7420},[118],{"categories":7422},[],{"categories":7424},[132],{"categories":7426},[70],{"categories":7428},[212],{"categories":7430},[],{"categories":7432},[70],{"categories":7434},[],{"categories":7436},[157],{"categories":7438},[108],{"categories":7440},[135],{"categories":7442},[],{"categories":7444},[132],{"categories":7446},[157],[7448,7519,7595,7668],{"id":7449,"title":7450,"ai":7451,"body":7456,"categories":7499,"created_at":71,"date_modified":71,"description":63,"extension":72,"faq":71,"featured":73,"kicker_label":71,"meta":7500,"navigation":87,"path":7509,"published_at":7510,"question":71,"scraped_at":7510,"seo":7511,"sitemap":7512,"source_id":7513,"source_name":93,"source_type":94,"source_url":7505,"stem":7514,"tags":7515,"thumbnail_url":71,"tldr":7516,"tweet":71,"unknown_tags":7517,"__hash__":7518},"summaries\u002Fsummaries\u002F9da9f37be06b530a-kuairp-technical-report-on-role-playing-model-opti-summary.md","KuaiRP: Technical Report on Role-Playing Model Optimization",{"provider":7,"model":8,"input_tokens":7452,"output_tokens":7453,"processing_time_ms":7454,"cost_usd":7455},4016,445,2626,0.0016715,{"type":14,"value":7457,"toc":7495},[7458,7462,7465,7469,7472,7492],[17,7459,7461],{"id":7460},"enhancing-role-playing-capabilities-in-llms","Enhancing Role-Playing Capabilities in LLMs",[22,7463,7464],{},"The KuaiRP technical report outlines a systematic approach to fine-tuning Large Language Models specifically for role-playing (RP) tasks. The core challenge addressed is the tendency of base models to drift from character personas or revert to generic, helpful assistant behaviors during long-form narrative interactions. By curating specialized datasets that emphasize character consistency, emotional nuance, and narrative adherence, the authors demonstrate how to steer models toward more immersive and stable role-play performance.",[17,7466,7468],{"id":7467},"methodological-framework","Methodological Framework",[22,7470,7471],{},"The report details a multi-stage training pipeline that prioritizes:",[40,7473,7474,7480,7486],{},[43,7475,7476,7479],{},[46,7477,7478],{},"Character Fidelity:"," Ensuring the model maintains a consistent voice, background, and set of motivations throughout extended dialogues.",[43,7481,7482,7485],{},[46,7483,7484],{},"Narrative Coherence:"," Improving the model's ability to track plot points and context over long interaction windows, reducing the likelihood of contradictory responses.",[43,7487,7488,7491],{},[46,7489,7490],{},"Instruction Following in Character:"," Balancing the need for the model to remain in-character while still adhering to user-defined constraints or format requirements.",[22,7493,7494],{},"The researchers emphasize that standard instruction-tuning datasets are often insufficient for RP tasks because they lack the necessary creative depth and stylistic variance required for high-quality character simulation. The KuaiRP approach involves synthetic data generation techniques and rigorous filtering to ensure the training corpus reflects the desired creative output quality.",{"title":63,"searchDepth":64,"depth":64,"links":7496},[7497,7498],{"id":7460,"depth":64,"text":7461},{"id":7467,"depth":64,"text":7468},[70],{"content_references":7501,"triage":7506},[7502],{"type":77,"title":7503,"publisher":7504,"url":7505,"context":80},"KuaiRP Series Role-playing Models Technical Report","arXiv","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.11127",{"relevance":84,"novelty":83,"quality":83,"actionability":64,"composite":7507,"reasoning":7508},3.25,"Category: AI & LLMs. The article maps to the AI & LLMs category by discussing methodologies for optimizing LLMs for role-playing tasks, which is relevant for developers looking to enhance AI features. However, while it presents novel insights into training techniques, it lacks specific actionable steps that the audience can directly implement.","\u002Fsummaries\u002F9da9f37be06b530a-kuairp-technical-report-on-role-playing-model-opti-summary","2026-09-13 03:09:05",{"title":7450,"description":63},{"loc":7509},"9da9f37be06b530a","summaries\u002F9da9f37be06b530a-kuairp-technical-report-on-role-playing-model-opti-summary",[97,98,99],"The KuaiRP technical report details specialized training methodologies for enhancing LLM performance in role-playing scenarios, focusing on character consistency and narrative depth.",[],"wBe2hkwbqtcO2IMoQkzOpilZJgVZX6bR8oFYjK_YRh8",{"id":7520,"title":7521,"ai":7522,"body":7527,"categories":7576,"created_at":71,"date_modified":71,"description":63,"extension":72,"faq":71,"featured":73,"kicker_label":71,"meta":7577,"navigation":87,"path":7585,"published_at":7586,"question":71,"scraped_at":7586,"seo":7587,"sitemap":7588,"source_id":7589,"source_name":93,"source_type":94,"source_url":7581,"stem":7590,"tags":7591,"thumbnail_url":71,"tldr":7592,"tweet":71,"unknown_tags":7593,"__hash__":7594},"summaries\u002Fsummaries\u002F6a960783061e5b6c-improving-llm-faithfulness-via-test-time-activatio-summary.md","Improving LLM Faithfulness via Test-Time Activation Removal",{"provider":7,"model":8,"input_tokens":7523,"output_tokens":7524,"processing_time_ms":7525,"cost_usd":7526},4024,659,3660,0.0019945,{"type":14,"value":7528,"toc":7571},[7529,7533,7536,7539,7543,7546,7566,7568],[17,7530,7532],{"id":7531},"the-mechanism-of-activation-removal","The Mechanism of Activation Removal",[22,7534,7535],{},"The core insight of this research is that LLM unfaithfulness—where a model generates a correct answer based on incorrect or hallucinated reasoning—can be mitigated by intervening directly on the model's internal states during inference. Instead of attempting to fix the model through expensive fine-tuning or prompt engineering, the authors propose a test-time intervention that identifies specific internal activations contributing to unfaithful output and removes them.",[22,7537,7538],{},"By isolating the latent representations that correlate with \"unfaithful\" reasoning patterns, the system can perform a surgical intervention. When the model begins to generate a response, the intervention mechanism monitors the activation flow. If it detects patterns associated with internal states that lead to hallucinations or logical disconnects, it suppresses those specific activations. This allows the model to re-route its generation process toward more faithful, grounded reasoning paths without altering the underlying model weights.",[17,7540,7542],{"id":7541},"advantages-over-traditional-alignment","Advantages Over Traditional Alignment",[22,7544,7545],{},"This removal-based approach offers several distinct advantages over standard alignment techniques like RLHF (Reinforcement Learning from Human Feedback) or SFT (Supervised Fine-Tuning):",[40,7547,7548,7554,7560],{},[43,7549,7550,7553],{},[46,7551,7552],{},"No Retraining Required:"," Because the intervention happens at test-time, there is no need to update the model parameters. This makes the method highly portable across different model architectures and sizes.",[43,7555,7556,7559],{},[46,7557,7558],{},"Precision:"," Unlike prompt-based methods which are often brittle and sensitive to minor input changes, activation removal targets the causal mechanism of the reasoning process itself.",[43,7561,7562,7565],{},[46,7563,7564],{},"Dynamic Correction:"," The method acts as a real-time monitor. It does not force the model to be faithful in all scenarios, but rather intervenes only when the internal state indicates that the model is drifting into unfaithful reasoning territory.",[17,7567,35],{"id":34},[22,7569,7570],{},"The research suggests that faithfulness is not just a property of the model's training data, but a dynamic state that can be managed during inference. For developers building AI-powered products, this implies a shift in how we handle hallucinations: rather than trying to \"train out\" errors, we can build \"guardrail\" layers that operate on the model's internal activations. This approach is particularly valuable for high-stakes applications where verifying the reasoning process is as important as the final output accuracy.",{"title":63,"searchDepth":64,"depth":64,"links":7572},[7573,7574,7575],{"id":7531,"depth":64,"text":7532},{"id":7541,"depth":64,"text":7542},{"id":34,"depth":64,"text":35},[70],{"content_references":7578,"triage":7583},[7579],{"type":77,"title":7580,"url":7581,"context":7582},"A Removal Based Approach to Improve LLM Faithfulness at Test-Time","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.04343","reviewed",{"relevance":84,"novelty":83,"quality":83,"actionability":64,"composite":7507,"reasoning":7584},"Category: AI & LLMs. The article discusses a novel method for improving LLM faithfulness through test-time activation removal, which addresses a specific challenge in AI engineering. However, while it presents interesting insights, it lacks detailed practical applications that the audience can immediately act upon.","\u002Fsummaries\u002F6a960783061e5b6c-improving-llm-faithfulness-via-test-time-activatio-summary","2026-09-08 03:09:59",{"title":7521,"description":63},{"loc":7585},"6a960783061e5b6c","summaries\u002F6a960783061e5b6c-improving-llm-faithfulness-via-test-time-activatio-summary",[97,99,98],"The paper introduces a test-time intervention method that improves LLM faithfulness by identifying and removing internal activations associated with unfaithful reasoning, rather than relying on retraining or fine-tuning.",[],"Wa5Pwh2stUu7VsDLpexDEX8Qp6OaazqmGtkW82yV7BI",{"id":7596,"title":7597,"ai":7598,"body":7603,"categories":7651,"created_at":71,"date_modified":71,"description":63,"extension":72,"faq":71,"featured":73,"kicker_label":71,"meta":7652,"navigation":87,"path":7659,"published_at":7586,"question":71,"scraped_at":7586,"seo":7660,"sitemap":7661,"source_id":7662,"source_name":93,"source_type":94,"source_url":7656,"stem":7663,"tags":7664,"thumbnail_url":71,"tldr":7665,"tweet":71,"unknown_tags":7666,"__hash__":7667},"summaries\u002Fsummaries\u002Fa23461b6e67ae91f-llm-reasoning-capabilities-in-hardware-performance-summary.md","LLM Reasoning Capabilities in Hardware Performance Analysis",{"provider":7,"model":8,"input_tokens":7599,"output_tokens":7600,"processing_time_ms":7601,"cost_usd":7602},4022,536,3493,0.0018095,{"type":14,"value":7604,"toc":7646},[7605,7609,7612,7616,7619,7639,7643],[17,7606,7608],{"id":7607},"the-gap-in-hardware-performance-reasoning","The Gap in Hardware Performance Reasoning",[22,7610,7611],{},"Recent research into 'PerfReasoning' highlights a significant limitation in current Large Language Models (LLMs) when tasked with predicting or analyzing hardware performance. While these models excel at general-purpose coding and natural language tasks, they demonstrate a lack of deep, mechanistic understanding of how software interacts with underlying hardware architectures. The study suggests that LLMs often rely on superficial patterns rather than true performance modeling, leading to inaccurate predictions regarding latency, throughput, and resource utilization.",[17,7613,7615],{"id":7614},"limitations-in-architectural-modeling","Limitations in Architectural Modeling",[22,7617,7618],{},"Performance reasoning requires an understanding of complex, non-linear interactions—such as cache hierarchy, branch prediction, and instruction-level parallelism. The research indicates that LLMs frequently fail to:",[40,7620,7621,7627,7633],{},[43,7622,7623,7626],{},[46,7624,7625],{},"Account for Micro-architectural Nuance:"," Models struggle to differentiate between performance impacts on varying CPU generations or specific cache configurations.",[43,7628,7629,7632],{},[46,7630,7631],{},"Synthesize Hardware-Software Interactions:"," LLMs often treat performance as a static property of code rather than a dynamic outcome of the interplay between code structure and hardware execution units.",[43,7634,7635,7638],{},[46,7636,7637],{},"Reason Through Bottlenecks:"," When presented with performance optimization problems, models often suggest generic improvements (e.g., 'use a faster algorithm') rather than specific, hardware-aware optimizations (e.g., 'improve cache locality to reduce L3 misses').",[17,7640,7642],{"id":7641},"implications-for-ai-driven-development","Implications for AI-Driven Development",[22,7644,7645],{},"For engineers building AI-powered tools, these findings serve as a warning against relying on LLMs for automated performance tuning or architectural decision-making. The research suggests that until models are trained on specialized datasets that include hardware performance counters and low-level execution traces, they should be treated as assistants for boilerplate code rather than experts in systems engineering. Developers should validate any AI-generated performance claims with empirical benchmarking tools rather than trusting the model's reasoning capabilities.",{"title":63,"searchDepth":64,"depth":64,"links":7647},[7648,7649,7650],{"id":7607,"depth":64,"text":7608},{"id":7614,"depth":64,"text":7615},{"id":7641,"depth":64,"text":7642},[70],{"content_references":7653,"triage":7657},[7654],{"type":77,"title":7655,"url":7656,"context":7582},"PerfReasoning: How Well Do LLMs Reason on Hardware Performance?","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.04476",{"relevance":84,"novelty":83,"quality":83,"actionability":64,"composite":7507,"reasoning":7658},"Category: AI & LLMs. The article discusses the limitations of LLMs in hardware performance analysis, which is relevant to AI engineering. It provides new insights into how LLMs fail to account for complex hardware interactions, but lacks specific actionable steps for developers to improve their use of LLMs in this context.","\u002Fsummaries\u002Fa23461b6e67ae91f-llm-reasoning-capabilities-in-hardware-performance-summary",{"title":7597,"description":63},{"loc":7659},"a23461b6e67ae91f","summaries\u002Fa23461b6e67ae91f-llm-reasoning-capabilities-in-hardware-performance-summary",[97,99,98],"Current LLMs struggle to accurately reason about hardware performance metrics, often failing to account for complex architectural bottlenecks and micro-architectural interactions.",[],"A7ZrGHvJtgwfs4MZAk2Sm6Vq5c2EBEXrgvm2CLeXJWo",{"id":7669,"title":7670,"ai":7671,"body":7676,"categories":7719,"created_at":71,"date_modified":71,"description":63,"extension":72,"faq":71,"featured":73,"kicker_label":71,"meta":7720,"navigation":87,"path":7727,"published_at":7728,"question":71,"scraped_at":7728,"seo":7729,"sitemap":7730,"source_id":7731,"source_name":93,"source_type":94,"source_url":7724,"stem":7732,"tags":7733,"thumbnail_url":71,"tldr":7734,"tweet":71,"unknown_tags":7735,"__hash__":7736},"summaries\u002Fsummaries\u002F7105b55e57007fe4-optimizing-kv-cache-eviction-via-temporal-aggregat-summary.md","Optimizing KV Cache Eviction via Temporal Aggregation",{"provider":7,"model":8,"input_tokens":7672,"output_tokens":7673,"processing_time_ms":7674,"cost_usd":7675},4042,515,3218,0.001783,{"type":14,"value":7677,"toc":7714},[7678,7682,7685,7689,7692,7707,7711],[17,7679,7681],{"id":7680},"the-challenge-of-kv-cache-memory-constraints","The Challenge of KV Cache Memory Constraints",[22,7683,7684],{},"Large Language Models (LLMs) face significant memory bottlenecks during inference due to the Key-Value (KV) cache, which grows linearly with sequence length. While aggressive eviction strategies aim to reduce this memory footprint, they often degrade model performance by discarding tokens that are critical for future generation. This research identifies that effective eviction is not merely about identifying 'important' tokens, but about maintaining the structural integrity of the attention mechanism.",[17,7686,7688],{"id":7687},"core-mechanisms-for-effective-eviction","Core Mechanisms for Effective Eviction",[22,7690,7691],{},"The authors demonstrate that two factors are paramount for successful decoding-time eviction:",[7693,7694,7695,7701],"ol",{},[43,7696,7697,7700],{},[46,7698,7699],{},"Ranking Preservation:"," The primary failure mode of naive eviction is the disruption of the relative importance ranking of tokens. Effective strategies must ensure that the attention scores assigned to remaining tokens accurately reflect their contribution to the model's output. When eviction alters the distribution of attention weights, the model loses its ability to attend to relevant context.",[43,7702,7703,7706],{},[46,7704,7705],{},"Temporal Aggregation:"," Rather than treating tokens as isolated entities, the model benefits from aggregating temporal information. By capturing how token importance evolves over time, eviction policies can make more informed decisions about which KV pairs are redundant. This approach mitigates the risk of discarding tokens that may appear low-importance in the short term but are vital for long-range dependencies.",[17,7708,7710],{"id":7709},"practical-implications","Practical Implications",[22,7712,7713],{},"The findings suggest that future KV cache management should move away from static importance metrics (like simple attention score thresholds) toward dynamic, context-aware policies. By prioritizing the preservation of the attention ranking and incorporating temporal context, developers can achieve higher compression ratios—allowing for longer context windows or higher throughput—without sacrificing the model's reasoning capabilities.",{"title":63,"searchDepth":64,"depth":64,"links":7715},[7716,7717,7718],{"id":7680,"depth":64,"text":7681},{"id":7687,"depth":64,"text":7688},{"id":7709,"depth":64,"text":7710},[70],{"content_references":7721,"triage":7725},[7722],{"type":77,"title":7723,"publisher":7504,"url":7724,"context":7582},"What Matters for Aggressive Decoding-Time KV Eviction? Temporal Aggregation and Ranking Preservation","https:\u002F\u002Farxiv.org\u002Fabs\u002F2609.03515",{"relevance":82,"novelty":83,"quality":83,"actionability":84,"composite":85,"reasoning":7726},"Category: AI & LLMs. The article addresses a specific challenge in optimizing KV cache eviction for LLMs, which is highly relevant for developers working on AI-powered products. It provides insights into maintaining attention ranking and leveraging temporal aggregation, which are actionable concepts, though it lacks detailed frameworks for implementation.","\u002Fsummaries\u002F7105b55e57007fe4-optimizing-kv-cache-eviction-via-temporal-aggregat-summary","2026-09-05 03:11:03",{"title":7670,"description":63},{"loc":7727},"7105b55e57007fe4","summaries\u002F7105b55e57007fe4-optimizing-kv-cache-eviction-via-temporal-aggregat-summary",[97,99,98],"Aggressive KV cache eviction requires preserving attention ranking and leveraging temporal aggregation to maintain model performance under memory constraints.",[],"y9PO0w7dwOMEm0ksweyZmkhxnsDSypvpxjAa-5c-it0"]