[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-94a3fe9f005972ab-pangram-raises-9m-to-combat-ai-generated-content-p-summary":3,"summaries-facets-categories":108,"summary-related-94a3fe9f005972ab-pangram-raises-9m-to-combat-ai-generated-content-p-summary":6054},{"id":4,"title":5,"ai":6,"body":13,"categories":64,"created_at":66,"date_modified":66,"description":59,"extension":67,"faq":66,"featured":68,"kicker_label":66,"meta":69,"navigation":89,"path":90,"published_at":91,"question":66,"scraped_at":92,"seo":93,"sitemap":94,"source_id":95,"source_name":96,"source_type":97,"source_url":98,"stem":99,"tags":100,"thumbnail_url":66,"tldr":105,"tweet":66,"unknown_tags":106,"__hash__":107},"summaries\u002Fsummaries\u002F94a3fe9f005972ab-pangram-raises-9m-to-combat-ai-generated-content-p-summary.md","Pangram Raises $9M to Combat AI-Generated Content Proliferation",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","google\u002Fgemini-3.1-flash-lite",7095,704,3491,0.00282975,{"type":14,"value":15,"toc":58},"minimark",[16,21,25,28,32,35,38,55],[17,18,20],"h2",{"id":19},"detecting-ai-through-stylistic-analysis","Detecting AI Through Stylistic Analysis",[22,23,24],"p",{},"Pangram, founded by Stanford AI and machine learning graduates Max Spero and Bradley Emi, has raised $9 million to address the rise of \"AI slop\"—low-quality, automated content flooding the internet. Unlike detection methods that rely on hidden watermarks or metadata—which are easily stripped or bypassed—Pangram’s approach uses a large machine learning model trained on millions of human-authored documents.",[22,26,27],{},"To train the system, the company creates a \"synthetic mirror\" of human documents, replicating their length, topic, and tone using frontier LLMs. By comparing these mirrors against human originals, the model learns to identify the consistent stylistic choices and patterns unique to AI generation. This allows the system to detect AI-assisted content even when it has been lightly edited by a human.",[17,29,31],{"id":30},"multi-modal-detection-and-real-world-application","Multi-Modal Detection and Real-World Application",[22,33,34],{},"Beyond text, Pangram is expanding into image detection. Its image model analyzes pixel-level statistical distributions to distinguish between real photos and AI-generated imagery, regardless of the model used to create the image. This is a significant departure from watermark-based checks, which are typically limited to content produced by a specific company's own models (e.g., Google or OpenAI).",[22,36,37],{},"Pangram offers several ways to integrate this technology:",[39,40,41,49],"ul",{},[42,43,44,48],"li",{},[45,46,47],"strong",{},"Consumer Tools:"," A $20\u002Fmonth web subscription and a browser extension that provides real-time \"health scores\" for content on platforms like X, LinkedIn, and Substack.",[42,50,51,54],{},[45,52,53],{},"API Integration:"," The company provides an API for platforms like Substack, schools, and publishers to verify the provenance of content.",[22,56,57],{},"The startup claims a false positive rate of approximately one in 10,000 for human documents, though real-world testing indicates that while the model is highly effective at identifying pure AI content, it can occasionally misidentify heavily edited or specific human-written styles as AI-assisted.",{"title":59,"searchDepth":60,"depth":60,"links":61},"",2,[62,63],{"id":19,"depth":60,"text":20},{"id":30,"depth":60,"text":31},[65],"AI & LLMs",null,"md",false,{"content_references":70,"triage":84},[71,76,78,80,82],{"type":72,"title":73,"url":74,"context":75},"tool","Pangram","http:\u002F\u002Fpangram.com","mentioned",{"type":72,"title":77,"context":75},"Winston AI",{"type":72,"title":79,"context":75},"Originality.ai",{"type":72,"title":81,"context":75},"Copyleaks",{"type":72,"title":83,"context":75},"GPTZero",{"relevance":85,"novelty":86,"quality":85,"actionability":85,"composite":87,"reasoning":88},4,3,3.8,"Category: AI & LLMs. The article discusses a new AI detection technology that addresses a specific pain point regarding the proliferation of AI-generated content, which is relevant to product builders concerned with content authenticity. It provides actionable insights on how to integrate this technology through consumer tools and API, making it applicable for developers and product teams.",true,"\u002Fsummaries\u002F94a3fe9f005972ab-pangram-raises-9m-to-combat-ai-generated-content-p-summary","2026-07-29 11:00:00","2026-07-30 03:13:57",{"title":5,"description":59},{"loc":90},"94a3fe9f005972ab","TechCrunch — AI","article","https:\u002F\u002Ftechcrunch.com\u002F2026\u002F07\u002F29\u002Fas-ai-content-floods-the-internet-pangram-raises-9m-to-detect-it\u002F","summaries\u002F94a3fe9f005972ab-pangram-raises-9m-to-combat-ai-generated-content-p-summary",[101,102,103,104],"ai-tools","llm","automation","machine-learning","Pangram has raised $9M to scale its AI detection technology, which uses machine learning to identify AI-generated text and images by analyzing stylistic patterns and pixel distributions rather than relying on watermarks.",[],"r60qhT8vUN1PV-cp7xg3dlzEYaLUn0ClfTwHn80zgdM",[109,111,114,117,119,122,125,127,129,131,134,136,138,140,142,145,147,149,151,153,156,158,160,162,164,166,168,170,172,174,176,178,180,182,184,186,188,190,192,194,197,200,202,204,206,208,210,212,214,216,218,220,222,225,227,229,231,233,235,237,239,241,243,245,247,249,251,253,255,257,260,262,264,266,268,270,272,274,276,278,280,282,284,286,289,291,293,295,297,299,301,303,305,307,309,311,313,315,317,319,321,323,325,327,329,331,333,335,337,339,341,343,345,348,350,352,354,356,358,360,362,364,366,369,371,373,375,377,379,381,383,385,387,389,391,393,396,398,400,402,404,406,408,410,412,415,417,419,421,423,425,427,429,431,433,435,437,439,441,443,445,447,449,451,453,455,457,459,461,463,466,468,470,473,475,477,479,481,483,485,487,489,491,493,495,497,499,502,504,506,508,510,512,514,516,518,520,522,525,527,529,531,533,535,537,539,541,543,545,547,549,551,553,555,557,559,561,563,565,567,569,571,573,575,577,579,581,583,585,587,589,591,593,595,597,599,601,603,605,607,609,611,613,615,617,619,621,623,625,627,629,631,633,635,637,639,641,643,645,647,649,651,653,655,657,659,661,663,665,667,669,671,673,675,677,679,681,683,685,687,689,691,693,695,697,699,701,703,705,707,709,711,713,715,717,719,721,723,725,727,729,731,733,735,737,739,741,743,745,747,749,751,753,755,757,759,761,763,765,767,769,772,774,776,778,780,783,785,787,789,791,793,795,797,799,801,803,806,808,810,812,814,816,818,820,822,824,826,828,830,832,834,836,838,840,842,844,846,848,850,852,854,856,858,860,862,864,866,868,870,872,874,876,878,880,882,884,886,888,890,892,894,896,898,900,902,904,906,908,910,912,914,916,918,920,922,924,926,928,930,932,934,936,938,940,942,944,946,948,950,952,954,956,958,960,962,964,966,968,970,972,974,976,978,980,982,984,986,988,990,992,994,996,998,1000,1002,1004,1006,1008,1010,1012,1014,1016,1018,1020,1022,1024,1026,1028,1030,1032,1034,1036,1038,1040,1042,1044,1046,1048,1050,1052,1054,1056,1058,1060,1062,1064,1066,1068,1070,1072,1074,1077,1079,1081,1083,1085,1087,1089,1091,1093,1095,1097,1099,1101,1103,1105,1107,1109,1111,1113,1115,1117,1119,1121,1123,1125,1127,1129,1131,1133,1135,1137,1139,1141,1143,1145,1147,1149,1151,1153,1155,1157,1159,1161,1163,1165,1167,1169,1171,1173,1175,1177,1179,1181,1183,1185,1187,1189,1191,1193,1195,1197,1199,1201,1203,1205,1207,1209,1211,1213,1215,1217,1219,1221,1223,1225,1227,1229,1231,1233,1235,1237,1239,1241,1243,1245,1248,1250,1252,1254,1256,1258,1260,1262,1264,1266,1268,1270,1272,1274,1276,1278,1280,1282,1284,1286,1288,1290,1292,1294,1296,1298,1300,1302,1304,1306,1308,1310,1312,1314,1316,1318,1320,1322,1324,1326,1328,1330,1332,1334,1336,1338,1340,1342,1344,1346,1348,1350,1352,1354,1356,1358,1360,1362,1364,1366,1368,1370,1372,1374,1377,1379,1381,1383,1385,1387,1389,1391,1393,1395,1397,1399,1401,1403,1405,1407,1409,1411,1413,1415,1417,1419,1421,1423,1425,1427,1429,1431,1433,1435,1437,1439,1441,1443,1445,1447,1449,1451,1453,1455,1457,1459,1461,1463,1465,1467,1469,1471,1473,1475,1477,1479,1481,1483,1485,1487,1489,1491,1493,1495,1497,1499,1501,1503,1505,1508,1510,1512,1514,1516,1518,1520,1522,1524,1526,1528,1530,1532,1534,1536,1538,1540,1542,1544,1546,1548,1550,1552,1554,1556,1558,1561,1563,1565,1567,1569,1571,1573,1575,1577,1579,1581,1583,1585,1587,1589,1591,1593,1595,1597,1599,1601,1603,1605,1607,1609,1611,1613,1615,1617,1619,1621,1623,1625,1627,1629,1631,1633,1635,1637,1639,1641,1643,1645,1647,1649,1651,1653,1655,1657,1659,1661,1663,1665,1667,1669,1671,1673,1675,1677,1679,1681,1683,1685,1687,1689,1691,1693,1695,1697,1699,1701,1703,1705,1707,1709,1711,1713,1715,1717,1719,1721,1723,1725,1727,1729,1731,1733,1735,1737,1739,1741,1743,1745,1747,1749,1751,1753,1755,1757,1759,1761,1763,1765,1767,1769,1771,1773,1775,1777,1779,1781,1783,1785,1787,1789,1791,1793,1795,1797,1799,1801,1803,1805,1807,1809,1811,1813,1815,1817,1819,1821,1823,1825,1827,1829,1831,1833,1835,1837,1839,1841,1843,1845,1847,1849,1851,1853,1855,1857,1859,1861,1863,1865,1867,1869,1871,1873,1875,1877,1879,1881,1883,1885,1887,1889,1891,1893,1895,1897,1899,1901,1903,1905,1907,1909,1911,1913,1915,1917,1919,1921,1923,1926,1928,1930,1932,1934,1936,1938,1940,1942,1944,1946,1948,1950,1952,1954,1956,1958,1960,1962,1964,1966,1968,1970,1972,1974,1976,1978,1980,1982,1984,1986,1988,1990,1992,1994,1996,1998,2000,2002,2005,2007,2009,2011,2013,2015,2017,2019,2021,2023,2025,2027,2029,2031,2033,2035,2037,2039,2041,2043,2045,2047,2049,2051,2053,2055,2057,2059,2061,2063,2065,2067,2069,2071,2073,2075,2077,2079,2081,2083,2085,2087,2089,2091,2093,2095,2097,2099,2101,2103,2105,2107,2109,2111,2114,2116,2118,2120,2122,2124,2126,2128,2130,2132,2134,2136,2138,2140,2142,2144,2146,2148,2151,2153,2155,2157,2159,2161,2163,2165,2167,2169,2171,2173,2175,2177,2179,2181,2183,2185,2187,2189,2191,2193,2195,2197,2199,2201,2203,2205,2207,2209,2211,2213,2215,2217,2219,2221,2223,2225,2227,2229,2231,2233,2235,2237,2239,2241,2243,2245,2247,2249,2251,2253,2255,2257,2259,2261,2263,2265,2267,2269,2271,2273,2275,2277,2279,2281,2283,2285,2287,2289,2291,2293,2295,2297,2299,2301,2303,2305,2307,2309,2311,2313,2315,2317,2319,2321,2323,2325,2327,2329,2331,2333,2335,2337,2339,2341,2343,2345,2347,2349,2351,2353,2355,2357,2359,2361,2363,2365,2367,2369,2371,2373,2375,2377,2379,2381,2383,2385,2387,2389,2391,2393,2395,2397,2399,2401,2403,2405,2407,2409,2411,2413,2415,2417,2419,2421,2423,2425,2427,2429,2431,2433,2435,2437,2439,2441,2443,2445,2447,2449,2451,2453,2455,2457,2459,2461,2463,2465,2467,2469,2471,2473,2475,2477,2479,2481,2483,2485,2487,2489,2491,2493,2495,2497,2499,2501,2503,2505,2507,2509,2511,2513,2515,2517,2519,2521,2523,2525,2527,2529,2531,2533,2535,2537,2539,2541,2543,2545,2547,2549,2551,2553,2555,2557,2559,2561,2563,2565,2567,2569,2571,2573,2575,2577,2579,2581,2583,2585,2587,2589,2591,2593,2595,2597,2599,2601,2603,2605,2607,2609,2611,2613,2615,2617,2619,2621,2623,2625,2627,2629,2631,2633,2635,2637,2639,2641,2643,2645,2647,2649,2651,2653,2655,2657,2659,2661,2663,2665,2667,2669,2671,2673,2675,2677,2679,2681,2683,2685,2687,2689,2691,2693,2695,2698,2700,2702,2704,2706,2708,2710,2712,2714,2716,2718,2720,2722,2724,2726,2728,2730,2732,2734,2736,2738,2740,2742,2744,2746,2748,2750,2752,2754,2756,2758,2760,2762,2764,2766,2768,2770,2772,2774,2776,2778,2780,2782,2784,2786,2788,2790,2792,2794,2796,2799,2801,2803,2805,2807,2809,2811,2813,2815,2817,2819,2821,2823,2825,2827,2829,2831,2833,2835,2837,2839,2841,2843,2845,2847,2849,2851,2853,2855,2857,2859,2861,2863,2865,2867,2869,2871,2873,2875,2877,2879,2881,2883,2885,2887,2889,2891,2893,2895,2897,2899,2901,2903,2905,2907,2909,2911,2913,2915,2917,2919,2921,2923,2925,2927,2929,2931,2933,2935,2937,2939,2941,2943,2945,2947,2949,2951,2953,2955,2957,2959,2961,2963,2965,2967,2969,2971,2973,2975,2977,2979,2981,2983,2985,2987,2989,2991,2993,2995,2997,2999,3001,3003,3005,3007,3009,3011,3013,3015,3017,3019,3021,3023,3025,3027,3029,3031,3033,3035,3037,3039,3041,3043,3045,3047,3049,3051,3053,3055,3057,3059,3061,3063,3065,3067,3069,3071,3073,3075,3077,3079,3081,3083,3085,3087,3089,3091,3093,3095,3097,3099,3101,3103,3105,3107,3109,3111,3113,3115,3117,3119,3121,3123,3125,3127,3129,3131,3133,3135,3137,3139,3141,3143,3145,3147,3149,3151,3153,3155,3157,3159,3161,3163,3165,3167,3169,3171,3173,3175,3177,3179,3181,3183,3185,3187,3189,3191,3193,3195,3197,3199,3201,3203,3205,3207,3209,3211,3213,3215,3217,3219,3221,3223,3225,3227,3229,3231,3233,3235,3237,3239,3241,3243,3245,3247,3249,3251,3253,3255,3257,3259,3261,3263,3265,3267,3269,3271,3273,3275,3277,3279,3281,3283,3285,3287,3289,3291,3293,3295,3297,3299,3301,3303,3305,3307,3309,3311,3313,3315,3317,3319,3321,3323,3325,3327,3329,3331,3333,3335,3337,3339,3341,3343,3345,3347,3349,3351,3353,3355,3357,3359,3361,3363,3365,3367,3369,3371,3373,3375,3377,3379,3381,3383,3385,3387,3389,3391,3393,3395,3397,3399,3401,3403,3405,3407,3409,3411,3413,3415,3417,3419,3421,3423,3425,3427,3429,3431,3433,3435,3437,3439,3441,3443,3445,3447,3449,3451,3453,3455,3457,3459,3461,3463,3465,3467,3469,3471,3473,3475,3477,3479,3481,3483,3485,3487,3489,3491,3493,3495,3497,3499,3501,3503,3505,3507,3509,3511,3513,3515,3517,3519,3521,3523,3525,3527,3529,3531,3533,3535,3537,3539,3541,3543,3545,3547,3549,3551,3553,3555,3557,3559,3561,3563,3565,3567,3569,3571,3573,3575,3577,3579,3581,3583,3585,3587,3589,3591,3593,3595,3597,3599,3601,3603,3605,3607,3609,3611,3613,3615,3617,3619,3621,3623,3625,3627,3629,3631,3633,3635,3637,3639,3641,3643,3645,3647,3649,3651,3653,3655,3657,3659,3661,3663,3665,3667,3669,3671,3673,3675,3677,3679,3681,3683,3685,3687,3689,3691,3693,3695,3697,3699,3701,3703,3705,3707,3709,3711,3713,3715,3717,3719,3721,3723,3725,3727,3729,3731,3733,3735,3737,3739,3741,3743,3745,3747,3749,3751,3753,3755,3757,3759,3761,3763,3765,3767,3769,3771,3773,3775,3777,3779,3781,3783,3785,3787,3789,3791,3793,3795,3797,3799,3801,3803,3805,3807,3809,3811,3813,3815,3817,3819,3821,3823,3825,3827,3829,3831,3833,3835,3837,3839,3841,3843,3845,3847,3849,3851,3853,3855,3857,3859,3861,3863,3865,3867,3869,3871,3873,3875,3877,3879,3881,3883,3885,3887,3889,3891,3893,3895,3897,3899,3901,3903,3905,3907,3909,3912,3914,3916,3918,3920,3922,3924,3926,3928,3930,3932,3934,3936,3938,3940,3942,3944,3946,3948,3950,3952,3954,3956,3958,3960,3962,3964,3966,3968,3970,3972,3974,3976,3978,3980,3982,3984,3986,3988,3990,3992,3994,3996,3998,4000,4002,4004,4006,4008,4010,4012,4014,4016,4018,4020,4022,4024,4026,4028,4030,4032,4034,4036,4038,4040,4042,4044,4046,4048,4050,4052,4054,4056,4058,4060,4062,4064,4066,4068,4070,4072,4074,4076,4078,4080,4082,4084,4086,4088,4090,4092,4094,4096,4098,4100,4102,4104,4106,4108,4110,4112,4114,4116,4118,4120,4122,4124,4126,4128,4130,4132,4134,4136,4138,4140,4142,4144,4146,4148,4150,4152,4154,4156,4158,4160,4162,4164,4166,4168,4170,4172,4174,4176,4178,4180,4182,4184,4186,4188,4190,4192,4194,4196,4198,4200,4202,4204,4206,4208,4210,4212,4214,4216,4218,4220,4222,4224,4226,4228,4230,4232,4234,4236,4238,4240,4242,4244,4246,4248,4250,4252,4254,4256,4258,4260,4262,4264,4266,4268,4270,4272,4274,4276,4278,4280,4282,4284,4286,4288,4290,4292,4294,4296,4298,4300,4302,4304,4306,4308,4310,4312,4314,4316,4318,4320,4322,4324,4326,4328,4330,4332,4334,4336,4338,4340,4342,4344,4346,4348,4350,4352,4354,4356,4358,4360,4362,4364,4366,4368,4370,4372,4374,4376,4378,4380,4382,4384,4386,4388,4390,4392,4394,4396,4398,4400,4402,4404,4406,4408,4410,4412,4414,4416,4418,4420,4422,4424,4426,4428,4430,4432,4434,4436,4438,4440,4442,4444,4446,4448,4450,4452,4454,4456,4458,4460,4462,4464,4466,4468,4470,4472,4474,4476,4478,4480,4482,4484,4486,4488,4490,4492,4494,4496,4498,4500,4502,4504,4506,4508,4510,4512,4514,4516,4518,4520,4522,4524,4526,4528,4530,4532,4534,4536,4538,4540,4542,4544,4546,4548,4550,4552,4554,4556,4558,4560,4562,4564,4566,4568,4570,4572,4574,4576,4578,4580,4582,4584,4586,4588,4590,4592,4594,4596,4598,4600,4602,4604,4606,4608,4610,4612,4614,4616,4618,4620,4622,4624,4626,4628,4630,4632,4634,4636,4638,4640,4642,4644,4646,4648,4650,4652,4654,4656,4659,4661,4663,4665,4667,4669,4671,4673,4675,4677,4679,4681,4683,4685,4687,4689,4691,4693,4695,4697,4699,4701,4703,4705,4707,4709,4711,4713,4715,4717,4719,4721,4723,4725,4727,4729,4731,4733,4735,4737,4739,4741,4743,4745,4747,4749,4751,4753,4755,4757,4759,4761,4763,4765,4767,4769,4771,4773,4775,4777,4779,4781,4783,4785,4787,4789,4791,4793,4795,4797,4799,4801,4803,4805,4807,4809,4811,4813,4815,4817,4819,4821,4823,4825,4827,4830,4832,4834,4836,4838,4840,4842,4844,4846,4848,4850,4852,4854,4856,4858,4860,4862,4864,4866,4868,4870,4872,4874,4876,4878,4880,4882,4884,4886,4888,4890,4892,4894,4896,4898,4900,4902,4904,4906,4908,4910,4912,4914,4916,4918,4920,4922,4924,4926,4928,4930,4932,4934,4936,4938,4940,4942,4944,4946,4948,4950,4952,4954,4956,4958,4960,4962,4964,4966,4968,4970,4972,4974,4976,4978,4980,4982,4984,4986,4988,4990,4992,4994,4996,4998,5000,5002,5004,5006,5008,5010,5012,5014,5016,5018,5020,5022,5024,5026,5028,5030,5032,5034,5036,5038,5040,5042,5044,5046,5048,5050,5052,5054,5056,5058,5060,5062,5064,5066,5068,5070,5072,5074,5076,5078,5080,5082,5084,5086,5088,5090,5092,5094,5096,5098,5100,5102,5104,5106,5108,5110,5112,5114,5116,5118,5120,5122,5124,5126,5128,5130,5132,5134,5136,5138,5140,5142,5144,5146,5148,5150,5152,5154,5156,5158,5160,5162,5164,5166,5168,5170,5172,5174,5176,5178,5180,5182,5184,5186,5188,5190,5192,5194,5196,5198,5200,5202,5204,5206,5208,5210,5212,5214,5216,5218,5220,5222,5224,5226,5228,5230,5232,5234,5236,5238,5240,5242,5244,5246,5248,5250,5252,5254,5256,5258,5260,5262,5264,5266,5268,5270,5272,5274,5276,5278,5280,5282,5284,5286,5288,5290,5292,5294,5296,5298,5300,5302,5304,5306,5308,5310,5312,5314,5316,5318,5320,5322,5324,5326,5328,5330,5332,5334,5336,5338,5340,5342,5344,5346,5348,5350,5352,5354,5356,5358,5360,5362,5364,5366,5368,5370,5372,5374,5376,5378,5380,5382,5384,5386,5388,5390,5392,5394,5396,5398,5400,5402,5404,5406,5408,5410,5412,5414,5416,5418,5420,5422,5424,5426,5428,5430,5432,5434,5436,5438,5440,5442,5444,5446,5448,5450,5452,5454,5456,5458,5460,5462,5464,5466,5468,5470,5472,5474,5476,5478,5480,5482,5484,5486,5488,5490,5492,5494,5496,5498,5500,5502,5504,5506,5508,5510,5512,5514,5516,5518,5520,5522,5524,5526,5528,5530,5532,5534,5536,5538,5540,5542,5544,5546,5548,5550,5552,5554,5556,5558,5560,5562,5564,5566,5568,5570,5572,5574,5576,5578,5580,5582,5584,5586,5588,5590,5592,5594,5596,5598,5600,5602,5604,5606,5608,5610,5612,5614,5616,5618,5620,5622,5624,5626,5628,5630,5632,5634,5636,5638,5640,5642,5644,5646,5648,5650,5652,5654,5656,5658,5660,5662,5664,5666,5668,5670,5672,5674,5676,5678,5680,5682,5684,5686,5688,5690,5692,5694,5696,5698,5700,5702,5704,5706,5708,5710,5712,5714,5716,5718,5720,5722,5724,5726,5728,5730,5732,5734,5736,5738,5740,5742,5744,5746,5748,5750,5752,5754,5756,5758,5760,5762,5764,5766,5768,5770,5772,5774,5776,5778,5780,5782,5784,5786,5788,5790,5792,5794,5796,5798,5800,5802,5804,5806,5808,5810,5812,5814,5816,5818,5820,5822,5824,5826,5828,5830,5832,5834,5836,5838,5840,5842,5844,5846,5848,5850,5852,5854,5856,5858,5860,5862,5864,5866,5868,5870,5872,5874,5876,5878,5880,5882,5884,5886,5888,5890,5892,5894,5896,5898,5900,5902,5904,5906,5908,5910,5912,5914,5916,5918,5920,5922,5924,5926,5928,5930,5932,5934,5936,5938,5940,5942,5944,5946,5948,5950,5952,5954,5956,5958,5960,5962,5964,5966,5968,5970,5972,5974,5976,5978,5980,5982,5984,5986,5988,5990,5992,5994,5996,5998,6000,6002,6004,6006,6008,6010,6012,6014,6016,6018,6020,6022,6024,6026,6028,6030,6032,6034,6036,6038,6040,6042,6044,6046,6048,6050,6052],{"categories":110},[65],{"categories":112},[113],"Developer Productivity",{"categories":115},[116],"Business & SaaS",{"categories":118},[65],{"categories":120},[121],"AI Automation",{"categories":123},[124],"Product Strategy",{"categories":126},[65],{"categories":128},[113],{"categories":130},[121],{"categories":132},[133],"Software Engineering",{"categories":135},[65],{"categories":137},[116],{"categories":139},[],{"categories":141},[65],{"categories":143},[144],"Inference & Serving",{"categories":146},[65],{"categories":148},[65],{"categories":150},[121],{"categories":152},[],{"categories":154},[155],"AI News & Trends",{"categories":157},[121],{"categories":159},[65],{"categories":161},[116],{"categories":163},[113],{"categories":165},[65],{"categories":167},[121],{"categories":169},[155],{"categories":171},[121],{"categories":173},[121],{"categories":175},[65],{"categories":177},[121],{"categories":179},[65],{"categories":181},[65],{"categories":183},[65],{"categories":185},[155],{"categories":187},[65],{"categories":189},[65],{"categories":191},[65],{"categories":193},[],{"categories":195},[196],"Design & Frontend",{"categories":198},[199],"Data Science & Visualization",{"categories":201},[155],{"categories":203},[65],{"categories":205},[65],{"categories":207},[65],{"categories":209},[],{"categories":211},[65],{"categories":213},[121],{"categories":215},[133],{"categories":217},[65],{"categories":219},[121],{"categories":221},[65],{"categories":223},[224],"Marketing & Growth",{"categories":226},[196],{"categories":228},[65],{"categories":230},[121],{"categories":232},[65],{"categories":234},[133],{"categories":236},[],{"categories":238},[],{"categories":240},[196],{"categories":242},[65],{"categories":244},[121],{"categories":246},[113],{"categories":248},[133],{"categories":250},[196],{"categories":252},[124],{"categories":254},[65],{"categories":256},[133],{"categories":258},[259],"DevOps & Cloud",{"categories":261},[121],{"categories":263},[124],{"categories":265},[155],{"categories":267},[65],{"categories":269},[],{"categories":271},[65],{"categories":273},[65],{"categories":275},[],{"categories":277},[121],{"categories":279},[133],{"categories":281},[],{"categories":283},[133],{"categories":285},[65],{"categories":287},[288],"Governance & Standards",{"categories":290},[116],{"categories":292},[],{"categories":294},[],{"categories":296},[65],{"categories":298},[65],{"categories":300},[121],{"categories":302},[65],{"categories":304},[65],{"categories":306},[121],{"categories":308},[65],{"categories":310},[65],{"categories":312},[65],{"categories":314},[],{"categories":316},[133],{"categories":318},[],{"categories":320},[],{"categories":322},[133],{"categories":324},[],{"categories":326},[133],{"categories":328},[65],{"categories":330},[65],{"categories":332},[224],{"categories":334},[65],{"categories":336},[196],{"categories":338},[196],{"categories":340},[65],{"categories":342},[133],{"categories":344},[121],{"categories":346},[347],"GovTech & Public-Sector Adoption",{"categories":349},[133],{"categories":351},[65],{"categories":353},[65],{"categories":355},[121],{"categories":357},[121],{"categories":359},[199],{"categories":361},[65],{"categories":363},[155],{"categories":365},[121],{"categories":367},[368],"Legal AI Tools",{"categories":370},[121],{"categories":372},[224],{"categories":374},[121],{"categories":376},[124],{"categories":378},[133],{"categories":380},[347],{"categories":382},[],{"categories":384},[121],{"categories":386},[],{"categories":388},[116],{"categories":390},[121],{"categories":392},[121],{"categories":394},[395],"RAG & Retrieval",{"categories":397},[116],{"categories":399},[65],{"categories":401},[133],{"categories":403},[133],{"categories":405},[259],{"categories":407},[196],{"categories":409},[65],{"categories":411},[],{"categories":413},[414],"Agents & Orchestration",{"categories":416},[133],{"categories":418},[65],{"categories":420},[],{"categories":422},[121],{"categories":424},[116],{"categories":426},[],{"categories":428},[65],{"categories":430},[],{"categories":432},[113],{"categories":434},[133],{"categories":436},[116],{"categories":438},[65],{"categories":440},[65],{"categories":442},[155],{"categories":444},[65],{"categories":446},[],{"categories":448},[65],{"categories":450},[],{"categories":452},[133],{"categories":454},[65],{"categories":456},[199],{"categories":458},[],{"categories":460},[65],{"categories":462},[196],{"categories":464},[465],"Models & Frontier Labs",{"categories":467},[],{"categories":469},[196],{"categories":471},[472],"Regulation & Governance of AI",{"categories":474},[121],{"categories":476},[],{"categories":478},[65],{"categories":480},[65],{"categories":482},[121],{"categories":484},[155],{"categories":486},[116],{"categories":488},[65],{"categories":490},[],{"categories":492},[133],{"categories":494},[121],{"categories":496},[65],{"categories":498},[124],{"categories":500},[501],"AI Policy & Regulation",{"categories":503},[],{"categories":505},[65],{"categories":507},[124],{"categories":509},[121],{"categories":511},[65],{"categories":513},[65],{"categories":515},[65],{"categories":517},[121],{"categories":519},[],{"categories":521},[199],{"categories":523},[524],"Evals & Reliability",{"categories":526},[65],{"categories":528},[],{"categories":530},[113],{"categories":532},[347],{"categories":534},[501],{"categories":536},[65],{"categories":538},[116],{"categories":540},[65],{"categories":542},[121],{"categories":544},[65],{"categories":546},[121],{"categories":548},[414],{"categories":550},[65],{"categories":552},[133],{"categories":554},[65],{"categories":556},[],{"categories":558},[],{"categories":560},[65],{"categories":562},[347],{"categories":564},[65],{"categories":566},[65],{"categories":568},[],{"categories":570},[196],{"categories":572},[],{"categories":574},[65],{"categories":576},[],{"categories":578},[121],{"categories":580},[65],{"categories":582},[196],{"categories":584},[],{"categories":586},[65],{"categories":588},[121],{"categories":590},[65],{"categories":592},[116],{"categories":594},[121],{"categories":596},[65],{"categories":598},[65],{"categories":600},[133],{"categories":602},[196],{"categories":604},[121],{"categories":606},[],{"categories":608},[133],{"categories":610},[121],{"categories":612},[199],{"categories":614},[],{"categories":616},[155],{"categories":618},[],{"categories":620},[65],{"categories":622},[65],{"categories":624},[65],{"categories":626},[116,224],{"categories":628},[],{"categories":630},[65],{"categories":632},[65],{"categories":634},[121],{"categories":636},[],{"categories":638},[],{"categories":640},[65],{"categories":642},[196],{"categories":644},[65],{"categories":646},[],{"categories":648},[65],{"categories":650},[259],{"categories":652},[],{"categories":654},[121],{"categories":656},[155],{"categories":658},[65],{"categories":660},[196],{"categories":662},[],{"categories":664},[155],{"categories":666},[65],{"categories":668},[144],{"categories":670},[65],{"categories":672},[121],{"categories":674},[155],{"categories":676},[465],{"categories":678},[65],{"categories":680},[224],{"categories":682},[],{"categories":684},[121],{"categories":686},[116],{"categories":688},[133],{"categories":690},[65],{"categories":692},[121],{"categories":694},[],{"categories":696},[65,259],{"categories":698},[65],{"categories":700},[65],{"categories":702},[65],{"categories":704},[121],{"categories":706},[65,133],{"categories":708},[199],{"categories":710},[65],{"categories":712},[65],{"categories":714},[133],{"categories":716},[121],{"categories":718},[501],{"categories":720},[224],{"categories":722},[65],{"categories":724},[121],{"categories":726},[65],{"categories":728},[65],{"categories":730},[121],{"categories":732},[],{"categories":734},[121],{"categories":736},[65],{"categories":738},[65],{"categories":740},[121],{"categories":742},[65],{"categories":744},[65,116],{"categories":746},[116],{"categories":748},[],{"categories":750},[196],{"categories":752},[196],{"categories":754},[65],{"categories":756},[],{"categories":758},[],{"categories":760},[155],{"categories":762},[],{"categories":764},[113],{"categories":766},[65],{"categories":768},[133],{"categories":770},[771],"Generative UI & Design-to-Code",{"categories":773},[65],{"categories":775},[65],{"categories":777},[196],{"categories":779},[65],{"categories":781},[782],"Algorithmic Accountability",{"categories":784},[121],{"categories":786},[133],{"categories":788},[155],{"categories":790},[196],{"categories":792},[],{"categories":794},[124],{"categories":796},[65],{"categories":798},[65],{"categories":800},[65],{"categories":802},[121],{"categories":804},[805],"MLOps & Infrastructure",{"categories":807},[65],{"categories":809},[65],{"categories":811},[65],{"categories":813},[65],{"categories":815},[65],{"categories":817},[155],{"categories":819},[113],{"categories":821},[65],{"categories":823},[121],{"categories":825},[259],{"categories":827},[65],{"categories":829},[116],{"categories":831},[65],{"categories":833},[196],{"categories":835},[65],{"categories":837},[65],{"categories":839},[121],{"categories":841},[],{"categories":843},[],{"categories":845},[144],{"categories":847},[196],{"categories":849},[155],{"categories":851},[199],{"categories":853},[],{"categories":855},[65],{"categories":857},[65],{"categories":859},[116],{"categories":861},[121],{"categories":863},[65],{"categories":865},[65],{"categories":867},[65],{"categories":869},[155],{"categories":871},[144],{"categories":873},[65],{"categories":875},[196],{"categories":877},[],{"categories":879},[121],{"categories":881},[133],{"categories":883},[],{"categories":885},[65],{"categories":887},[65],{"categories":889},[121],{"categories":891},[133],{"categories":893},[65],{"categories":895},[199],{"categories":897},[],{"categories":899},[65],{"categories":901},[],{"categories":903},[65],{"categories":905},[],{"categories":907},[124],{"categories":909},[116],{"categories":911},[121],{"categories":913},[121],{"categories":915},[],{"categories":917},[113],{"categories":919},[65],{"categories":921},[65],{"categories":923},[116],{"categories":925},[155],{"categories":927},[113],{"categories":929},[],{"categories":931},[65],{"categories":933},[],{"categories":935},[],{"categories":937},[155],{"categories":939},[155],{"categories":941},[],{"categories":943},[414],{"categories":945},[65],{"categories":947},[196],{"categories":949},[133],{"categories":951},[],{"categories":953},[368],{"categories":955},[116],{"categories":957},[],{"categories":959},[],{"categories":961},[113],{"categories":963},[199],{"categories":965},[],{"categories":967},[224],{"categories":969},[121],{"categories":971},[116],{"categories":973},[121],{"categories":975},[116],{"categories":977},[133],{"categories":979},[],{"categories":981},[144],{"categories":983},[124],{"categories":985},[65],{"categories":987},[196],{"categories":989},[133],{"categories":991},[116],{"categories":993},[65],{"categories":995},[121],{"categories":997},[116],{"categories":999},[65],{"categories":1001},[65],{"categories":1003},[65],{"categories":1005},[65],{"categories":1007},[],{"categories":1009},[],{"categories":1011},[133],{"categories":1013},[199],{"categories":1015},[124],{"categories":1017},[65],{"categories":1019},[121],{"categories":1021},[65],{"categories":1023},[],{"categories":1025},[155],{"categories":1027},[124],{"categories":1029},[65],{"categories":1031},[524],{"categories":1033},[259],{"categories":1035},[],{"categories":1037},[121],{"categories":1039},[],{"categories":1041},[113],{"categories":1043},[],{"categories":1045},[65],{"categories":1047},[65],{"categories":1049},[196],{"categories":1051},[224],{"categories":1053},[133],{"categories":1055},[121],{"categories":1057},[],{"categories":1059},[133],{"categories":1061},[65],{"categories":1063},[113],{"categories":1065},[],{"categories":1067},[116],{"categories":1069},[65],{"categories":1071},[155],{"categories":1073},[65,259],{"categories":1075},[1076],"Design Systems for AI",{"categories":1078},[65],{"categories":1080},[65],{"categories":1082},[155],{"categories":1084},[65],{"categories":1086},[65],{"categories":1088},[116],{"categories":1090},[65],{"categories":1092},[65],{"categories":1094},[],{"categories":1096},[65],{"categories":1098},[65],{"categories":1100},[116],{"categories":1102},[65],{"categories":1104},[],{"categories":1106},[121],{"categories":1108},[133],{"categories":1110},[155],{"categories":1112},[133],{"categories":1114},[196],{"categories":1116},[155],{"categories":1118},[199],{"categories":1120},[65],{"categories":1122},[113],{"categories":1124},[501],{"categories":1126},[65],{"categories":1128},[121],{"categories":1130},[65],{"categories":1132},[133],{"categories":1134},[133],{"categories":1136},[],{"categories":1138},[],{"categories":1140},[121],{"categories":1142},[124],{"categories":1144},[],{"categories":1146},[65],{"categories":1148},[],{"categories":1150},[196],{"categories":1152},[121],{"categories":1154},[133],{"categories":1156},[196],{"categories":1158},[65],{"categories":1160},[65],{"categories":1162},[196],{"categories":1164},[],{"categories":1166},[],{"categories":1168},[155],{"categories":1170},[121],{"categories":1172},[121],{"categories":1174},[65],{"categories":1176},[65],{"categories":1178},[65],{"categories":1180},[116],{"categories":1182},[65],{"categories":1184},[65],{"categories":1186},[],{"categories":1188},[133],{"categories":1190},[133],{"categories":1192},[65],{"categories":1194},[133],{"categories":1196},[116],{"categories":1198},[],{"categories":1200},[65],{"categories":1202},[65],{"categories":1204},[65],{"categories":1206},[65],{"categories":1208},[121],{"categories":1210},[113],{"categories":1212},[116],{"categories":1214},[65],{"categories":1216},[155],{"categories":1218},[121],{"categories":1220},[144],{"categories":1222},[224],{"categories":1224},[65],{"categories":1226},[121],{"categories":1228},[65],{"categories":1230},[],{"categories":1232},[196],{"categories":1234},[],{"categories":1236},[65],{"categories":1238},[65],{"categories":1240},[],{"categories":1242},[133],{"categories":1244},[116],{"categories":1246},[1247],"Visual & Generative Media",{"categories":1249},[121],{"categories":1251},[],{"categories":1253},[65],{"categories":1255},[65],{"categories":1257},[133],{"categories":1259},[259],{"categories":1261},[199],{"categories":1263},[501],{"categories":1265},[133],{"categories":1267},[224],{"categories":1269},[65],{"categories":1271},[196],{"categories":1273},[65],{"categories":1275},[65],{"categories":1277},[133],{"categories":1279},[121],{"categories":1281},[65],{"categories":1283},[],{"categories":1285},[],{"categories":1287},[121],{"categories":1289},[133],{"categories":1291},[113],{"categories":1293},[121],{"categories":1295},[465],{"categories":1297},[65],{"categories":1299},[124],{"categories":1301},[65],{"categories":1303},[116],{"categories":1305},[],{"categories":1307},[65],{"categories":1309},[124],{"categories":1311},[65],{"categories":1313},[65],{"categories":1315},[65],{"categories":1317},[124],{"categories":1319},[65],{"categories":1321},[65],{"categories":1323},[224],{"categories":1325},[65],{"categories":1327},[414],{"categories":1329},[65],{"categories":1331},[121],{"categories":1333},[65],{"categories":1335},[65],{"categories":1337},[65],{"categories":1339},[65],{"categories":1341},[196],{"categories":1343},[121],{"categories":1345},[],{"categories":1347},[121],{"categories":1349},[],{"categories":1351},[259],{"categories":1353},[133],{"categories":1355},[],{"categories":1357},[465],{"categories":1359},[65],{"categories":1361},[121],{"categories":1363},[65],{"categories":1365},[196,65],{"categories":1367},[113],{"categories":1369},[],{"categories":1371},[65],{"categories":1373},[113],{"categories":1375},[1376],"Medical Imaging & Radiology",{"categories":1378},[196],{"categories":1380},[121],{"categories":1382},[133],{"categories":1384},[],{"categories":1386},[65],{"categories":1388},[65],{"categories":1390},[65],{"categories":1392},[],{"categories":1394},[],{"categories":1396},[65],{"categories":1398},[414],{"categories":1400},[65],{"categories":1402},[113],{"categories":1404},[65],{"categories":1406},[65],{"categories":1408},[],{"categories":1410},[121],{"categories":1412},[65],{"categories":1414},[124],{"categories":1416},[133],{"categories":1418},[65],{"categories":1420},[414],{"categories":1422},[65],{"categories":1424},[121],{"categories":1426},[65],{"categories":1428},[196],{"categories":1430},[121],{"categories":1432},[259],{"categories":1434},[196],{"categories":1436},[116],{"categories":1438},[121],{"categories":1440},[65],{"categories":1442},[65],{"categories":1444},[124],{"categories":1446},[65],{"categories":1448},[65],{"categories":1450},[65],{"categories":1452},[121],{"categories":1454},[133],{"categories":1456},[65],{"categories":1458},[124],{"categories":1460},[],{"categories":1462},[155],{"categories":1464},[],{"categories":1466},[124],{"categories":1468},[121],{"categories":1470},[121],{"categories":1472},[1076],{"categories":1474},[1076],{"categories":1476},[196],{"categories":1478},[65],{"categories":1480},[65],{"categories":1482},[121],{"categories":1484},[133],{"categories":1486},[196],{"categories":1488},[121],{"categories":1490},[155],{"categories":1492},[],{"categories":1494},[65],{"categories":1496},[],{"categories":1498},[65],{"categories":1500},[65],{"categories":1502},[65],{"categories":1504},[121],{"categories":1506},[1507],"Contract Review & E-Discovery",{"categories":1509},[196],{"categories":1511},[65],{"categories":1513},[113],{"categories":1515},[155],{"categories":1517},[65],{"categories":1519},[65],{"categories":1521},[224],{"categories":1523},[133],{"categories":1525},[65],{"categories":1527},[65],{"categories":1529},[121],{"categories":1531},[121],{"categories":1533},[782],{"categories":1535},[65],{"categories":1537},[121],{"categories":1539},[121],{"categories":1541},[65],{"categories":1543},[65],{"categories":1545},[121],{"categories":1547},[65],{"categories":1549},[414],{"categories":1551},[395],{"categories":1553},[65],{"categories":1555},[121],{"categories":1557},[65],{"categories":1559},[1560],"Law-Firm Practice & Adoption",{"categories":1562},[65],{"categories":1564},[121],{"categories":1566},[196],{"categories":1568},[65],{"categories":1570},[65],{"categories":1572},[],{"categories":1574},[],{"categories":1576},[133],{"categories":1578},[],{"categories":1580},[121],{"categories":1582},[113],{"categories":1584},[259],{"categories":1586},[65],{"categories":1588},[],{"categories":1590},[113],{"categories":1592},[116],{"categories":1594},[65],{"categories":1596},[224],{"categories":1598},[],{"categories":1600},[116],{"categories":1602},[116],{"categories":1604},[],{"categories":1606},[65],{"categories":1608},[65],{"categories":1610},[133],{"categories":1612},[],{"categories":1614},[],{"categories":1616},[],{"categories":1618},[],{"categories":1620},[65],{"categories":1622},[121],{"categories":1624},[259],{"categories":1626},[65],{"categories":1628},[113],{"categories":1630},[133],{"categories":1632},[65],{"categories":1634},[65],{"categories":1636},[133],{"categories":1638},[124],{"categories":1640},[65],{"categories":1642},[805],{"categories":1644},[65],{"categories":1646},[224],{"categories":1648},[133],{"categories":1650},[116],{"categories":1652},[65],{"categories":1654},[65],{"categories":1656},[196],{"categories":1658},[65],{"categories":1660},[65],{"categories":1662},[65],{"categories":1664},[121],{"categories":1666},[65,113],{"categories":1668},[414],{"categories":1670},[65],{"categories":1672},[65],{"categories":1674},[133],{"categories":1676},[133],{"categories":1678},[196],{"categories":1680},[121],{"categories":1682},[133],{"categories":1684},[65],{"categories":1686},[65],{"categories":1688},[],{"categories":1690},[],{"categories":1692},[65],{"categories":1694},[],{"categories":1696},[65],{"categories":1698},[133],{"categories":1700},[199],{"categories":1702},[155],{"categories":1704},[196],{"categories":1706},[65],{"categories":1708},[65],{"categories":1710},[133],{"categories":1712},[],{"categories":1714},[121],{"categories":1716},[65],{"categories":1718},[65],{"categories":1720},[65],{"categories":1722},[65],{"categories":1724},[],{"categories":1726},[121],{"categories":1728},[65],{"categories":1730},[65],{"categories":1732},[],{"categories":1734},[121],{"categories":1736},[65],{"categories":1738},[65],{"categories":1740},[116],{"categories":1742},[65],{"categories":1744},[],{"categories":1746},[113],{"categories":1748},[65],{"categories":1750},[65],{"categories":1752},[196],{"categories":1754},[133],{"categories":1756},[65],{"categories":1758},[113],{"categories":1760},[65],{"categories":1762},[133],{"categories":1764},[224],{"categories":1766},[121],{"categories":1768},[121],{"categories":1770},[65,196],{"categories":1772},[65],{"categories":1774},[155],{"categories":1776},[65],{"categories":1778},[155],{"categories":1780},[121],{"categories":1782},[196],{"categories":1784},[],{"categories":1786},[133],{"categories":1788},[259],{"categories":1790},[196],{"categories":1792},[133],{"categories":1794},[65],{"categories":1796},[124],{"categories":1798},[65],{"categories":1800},[121],{"categories":1802},[],{"categories":1804},[],{"categories":1806},[65],{"categories":1808},[],{"categories":1810},[],{"categories":1812},[124],{"categories":1814},[133],{"categories":1816},[65],{"categories":1818},[121],{"categories":1820},[121],{"categories":1822},[116],{"categories":1824},[121],{"categories":1826},[259],{"categories":1828},[65],{"categories":1830},[65],{"categories":1832},[144],{"categories":1834},[65],{"categories":1836},[65],{"categories":1838},[121],{"categories":1840},[65],{"categories":1842},[65],{"categories":1844},[368],{"categories":1846},[782],{"categories":1848},[],{"categories":1850},[196],{"categories":1852},[1560],{"categories":1854},[133],{"categories":1856},[],{"categories":1858},[],{"categories":1860},[121],{"categories":1862},[],{"categories":1864},[],{"categories":1866},[224],{"categories":1868},[65],{"categories":1870},[224],{"categories":1872},[121],{"categories":1874},[65],{"categories":1876},[133],{"categories":1878},[124],{"categories":1880},[],{"categories":1882},[65],{"categories":1884},[65],{"categories":1886},[133],{"categories":1888},[1507],{"categories":1890},[196],{"categories":1892},[196],{"categories":1894},[65],{"categories":1896},[121],{"categories":1898},[113],{"categories":1900},[65],{"categories":1902},[65],{"categories":1904},[65],{"categories":1906},[196],{"categories":1908},[196],{"categories":1910},[121],{"categories":1912},[121],{"categories":1914},[65],{"categories":1916},[65],{"categories":1918},[],{"categories":1920},[65],{"categories":1922},[],{"categories":1924},[1925],"Interaction & Product Design",{"categories":1927},[65],{"categories":1929},[121],{"categories":1931},[288],{"categories":1933},[155],{"categories":1935},[133],{"categories":1937},[65],{"categories":1939},[65],{"categories":1941},[133],{"categories":1943},[113],{"categories":1945},[121],{"categories":1947},[65],{"categories":1949},[],{"categories":1951},[121],{"categories":1953},[121],{"categories":1955},[],{"categories":1957},[133],{"categories":1959},[65],{"categories":1961},[113],{"categories":1963},[1925],{"categories":1965},[65],{"categories":1967},[113],{"categories":1969},[113],{"categories":1971},[],{"categories":1973},[133],{"categories":1975},[],{"categories":1977},[121],{"categories":1979},[155],{"categories":1981},[65],{"categories":1983},[121],{"categories":1985},[65],{"categories":1987},[121],{"categories":1989},[65],{"categories":1991},[65],{"categories":1993},[155],{"categories":1995},[199],{"categories":1997},[65],{"categories":1999},[124],{"categories":2001},[133],{"categories":2003},[2004],"Coding Agents & Dev Productivity",{"categories":2006},[155],{"categories":2008},[196],{"categories":2010},[65],{"categories":2012},[],{"categories":2014},[65],{"categories":2016},[782],{"categories":2018},[],{"categories":2020},[65],{"categories":2022},[259],{"categories":2024},[65],{"categories":2026},[155],{"categories":2028},[],{"categories":2030},[],{"categories":2032},[65],{"categories":2034},[],{"categories":2036},[121],{"categories":2038},[65],{"categories":2040},[],{"categories":2042},[133],{"categories":2044},[133],{"categories":2046},[65],{"categories":2048},[199],{"categories":2050},[],{"categories":2052},[65],{"categories":2054},[65],{"categories":2056},[65],{"categories":2058},[199],{"categories":2060},[133],{"categories":2062},[],{"categories":2064},[],{"categories":2066},[65],{"categories":2068},[65],{"categories":2070},[121],{"categories":2072},[121],{"categories":2074},[347],{"categories":2076},[133],{"categories":2078},[133],{"categories":2080},[121],{"categories":2082},[155],{"categories":2084},[155],{"categories":2086},[121],{"categories":2088},[121],{"categories":2090},[65],{"categories":2092},[113],{"categories":2094},[1925],{"categories":2096},[65,259],{"categories":2098},[199],{"categories":2100},[],{"categories":2102},[196],{"categories":2104},[133],{"categories":2106},[113],{"categories":2108},[65],{"categories":2110},[121],{"categories":2112},[2113],"The Designer's Role & Craft",{"categories":2115},[196],{"categories":2117},[],{"categories":2119},[121],{"categories":2121},[65],{"categories":2123},[121],{"categories":2125},[121],{"categories":2127},[65],{"categories":2129},[224],{"categories":2131},[65],{"categories":2133},[133],{"categories":2135},[196],{"categories":2137},[65],{"categories":2139},[],{"categories":2141},[121],{"categories":2143},[196],{"categories":2145},[65],{"categories":2147},[65],{"categories":2149},[2150],"AI UX Patterns",{"categories":2152},[121],{"categories":2154},[121],{"categories":2156},[121],{"categories":2158},[121],{"categories":2160},[224],{"categories":2162},[199],{"categories":2164},[65],{"categories":2166},[121],{"categories":2168},[65],{"categories":2170},[1076],{"categories":2172},[],{"categories":2174},[224],{"categories":2176},[121],{"categories":2178},[155],{"categories":2180},[133],{"categories":2182},[65],{"categories":2184},[121],{"categories":2186},[],{"categories":2188},[],{"categories":2190},[65],{"categories":2192},[121],{"categories":2194},[65],{"categories":2196},[121],{"categories":2198},[347],{"categories":2200},[196],{"categories":2202},[155],{"categories":2204},[133],{"categories":2206},[65],{"categories":2208},[121],{"categories":2210},[121],{"categories":2212},[],{"categories":2214},[65],{"categories":2216},[],{"categories":2218},[],{"categories":2220},[65],{"categories":2222},[65],{"categories":2224},[121],{"categories":2226},[133],{"categories":2228},[],{"categories":2230},[],{"categories":2232},[199],{"categories":2234},[144],{"categories":2236},[65],{"categories":2238},[199],{"categories":2240},[155],{"categories":2242},[65],{"categories":2244},[65],{"categories":2246},[121],{"categories":2248},[65],{"categories":2250},[121],{"categories":2252},[65],{"categories":2254},[65],{"categories":2256},[121],{"categories":2258},[],{"categories":2260},[],{"categories":2262},[65],{"categories":2264},[259],{"categories":2266},[65],{"categories":2268},[],{"categories":2270},[],{"categories":2272},[196],{"categories":2274},[805],{"categories":2276},[121],{"categories":2278},[113],{"categories":2280},[2113],{"categories":2282},[],{"categories":2284},[],{"categories":2286},[65],{"categories":2288},[],{"categories":2290},[],{"categories":2292},[133],{"categories":2294},[155],{"categories":2296},[224],{"categories":2298},[116],{"categories":2300},[65],{"categories":2302},[65],{"categories":2304},[116],{"categories":2306},[],{"categories":2308},[196],{"categories":2310},[65],{"categories":2312},[65],{"categories":2314},[121],{"categories":2316},[116],{"categories":2318},[65],{"categories":2320},[65],{"categories":2322},[113],{"categories":2324},[65],{"categories":2326},[],{"categories":2328},[113],{"categories":2330},[65],{"categories":2332},[224],{"categories":2334},[121],{"categories":2336},[155],{"categories":2338},[65],{"categories":2340},[116],{"categories":2342},[65],{"categories":2344},[65],{"categories":2346},[65],{"categories":2348},[121],{"categories":2350},[],{"categories":2352},[65],{"categories":2354},[133],{"categories":2356},[113],{"categories":2358},[65],{"categories":2360},[65],{"categories":2362},[],{"categories":2364},[65],{"categories":2366},[414],{"categories":2368},[116],{"categories":2370},[155],{"categories":2372},[65],{"categories":2374},[65],{"categories":2376},[],{"categories":2378},[116],{"categories":2380},[116],{"categories":2382},[65],{"categories":2384},[65],{"categories":2386},[124],{"categories":2388},[65],{"categories":2390},[65],{"categories":2392},[65],{"categories":2394},[133],{"categories":2396},[133],{"categories":2398},[65],{"categories":2400},[],{"categories":2402},[133],{"categories":2404},[65],{"categories":2406},[133],{"categories":2408},[501],{"categories":2410},[],{"categories":2412},[],{"categories":2414},[65],{"categories":2416},[155],{"categories":2418},[],{"categories":2420},[259],{"categories":2422},[65],{"categories":2424},[65],{"categories":2426},[196],{"categories":2428},[771],{"categories":2430},[],{"categories":2432},[65],{"categories":2434},[65],{"categories":2436},[65],{"categories":2438},[133],{"categories":2440},[65],{"categories":2442},[65],{"categories":2444},[65,259],{"categories":2446},[65],{"categories":2448},[65],{"categories":2450},[196],{"categories":2452},[121],{"categories":2454},[],{"categories":2456},[121],{"categories":2458},[121],{"categories":2460},[65],{"categories":2462},[65],{"categories":2464},[65],{"categories":2466},[199],{"categories":2468},[65],{"categories":2470},[2150],{"categories":2472},[113],{"categories":2474},[199],{"categories":2476},[113],{"categories":2478},[133],{"categories":2480},[196],{"categories":2482},[121],{"categories":2484},[65],{"categories":2486},[],{"categories":2488},[65],{"categories":2490},[65],{"categories":2492},[155],{"categories":2494},[65],{"categories":2496},[121],{"categories":2498},[65],{"categories":2500},[65],{"categories":2502},[116],{"categories":2504},[],{"categories":2506},[259],{"categories":2508},[65],{"categories":2510},[347],{"categories":2512},[196],{"categories":2514},[196],{"categories":2516},[133],{"categories":2518},[121],{"categories":2520},[65],{"categories":2522},[116],{"categories":2524},[155],{"categories":2526},[65],{"categories":2528},[196],{"categories":2530},[121],{"categories":2532},[65],{"categories":2534},[65],{"categories":2536},[465],{"categories":2538},[],{"categories":2540},[65],{"categories":2542},[65],{"categories":2544},[65],{"categories":2546},[],{"categories":2548},[],{"categories":2550},[65],{"categories":2552},[65],{"categories":2554},[65],{"categories":2556},[65],{"categories":2558},[65],{"categories":2560},[133],{"categories":2562},[65],{"categories":2564},[65],{"categories":2566},[121],{"categories":2568},[65],{"categories":2570},[65],{"categories":2572},[65],{"categories":2574},[65],{"categories":2576},[65],{"categories":2578},[],{"categories":2580},[133],{"categories":2582},[199],{"categories":2584},[65],{"categories":2586},[121],{"categories":2588},[65],{"categories":2590},[],{"categories":2592},[],{"categories":2594},[65],{"categories":2596},[65],{"categories":2598},[65],{"categories":2600},[155],{"categories":2602},[],{"categories":2604},[65],{"categories":2606},[196],{"categories":2608},[65],{"categories":2610},[259],{"categories":2612},[1560],{"categories":2614},[155],{"categories":2616},[133],{"categories":2618},[133],{"categories":2620},[133],{"categories":2622},[155],{"categories":2624},[155],{"categories":2626},[259],{"categories":2628},[],{"categories":2630},[155],{"categories":2632},[65],{"categories":2634},[113],{"categories":2636},[133],{"categories":2638},[65],{"categories":2640},[155],{"categories":2642},[],{"categories":2644},[65],{"categories":2646},[133],{"categories":2648},[133],{"categories":2650},[199],{"categories":2652},[65],{"categories":2654},[155],{"categories":2656},[65],{"categories":2658},[133],{"categories":2660},[121],{"categories":2662},[155],{"categories":2664},[121],{"categories":2666},[259],{"categories":2668},[121],{"categories":2670},[65],{"categories":2672},[65],{"categories":2674},[133],{"categories":2676},[65],{"categories":2678},[],{"categories":2680},[121],{"categories":2682},[116],{"categories":2684},[133],{"categories":2686},[],{"categories":2688},[],{"categories":2690},[65],{"categories":2692},[121],{"categories":2694},[65],{"categories":2696},[2697],"Frameworks & Tooling",{"categories":2699},[65],{"categories":2701},[65],{"categories":2703},[133],{"categories":2705},[65],{"categories":2707},[65],{"categories":2709},[],{"categories":2711},[199],{"categories":2713},[199],{"categories":2715},[113],{"categories":2717},[121],{"categories":2719},[196],{"categories":2721},[],{"categories":2723},[1560],{"categories":2725},[65],{"categories":2727},[133],{"categories":2729},[65],{"categories":2731},[259],{"categories":2733},[259],{"categories":2735},[],{"categories":2737},[121],{"categories":2739},[155],{"categories":2741},[155],{"categories":2743},[65],{"categories":2745},[121],{"categories":2747},[],{"categories":2749},[196],{"categories":2751},[65],{"categories":2753},[65],{"categories":2755},[],{"categories":2757},[65],{"categories":2759},[65],{"categories":2761},[],{"categories":2763},[133],{"categories":2765},[65],{"categories":2767},[133],{"categories":2769},[259],{"categories":2771},[65],{"categories":2773},[133],{"categories":2775},[116],{"categories":2777},[65],{"categories":2779},[1560],{"categories":2781},[],{"categories":2783},[121],{"categories":2785},[113],{"categories":2787},[65],{"categories":2789},[113],{"categories":2791},[],{"categories":2793},[121],{"categories":2795},[65],{"categories":2797},[2798],"AI Design Tooling",{"categories":2800},[196],{"categories":2802},[65],{"categories":2804},[65],{"categories":2806},[133],{"categories":2808},[196],{"categories":2810},[65],{"categories":2812},[133],{"categories":2814},[155],{"categories":2816},[124],{"categories":2818},[133],{"categories":2820},[65],{"categories":2822},[121],{"categories":2824},[],{"categories":2826},[65],{"categories":2828},[65],{"categories":2830},[121],{"categories":2832},[65],{"categories":2834},[65],{"categories":2836},[65],{"categories":2838},[],{"categories":2840},[121],{"categories":2842},[2697],{"categories":2844},[65],{"categories":2846},[121],{"categories":2848},[121],{"categories":2850},[133],{"categories":2852},[133],{"categories":2854},[],{"categories":2856},[133],{"categories":2858},[65],{"categories":2860},[65],{"categories":2862},[121],{"categories":2864},[116],{"categories":2866},[65],{"categories":2868},[],{"categories":2870},[65],{"categories":2872},[65],{"categories":2874},[1925],{"categories":2876},[],{"categories":2878},[65],{"categories":2880},[65],{"categories":2882},[65],{"categories":2884},[],{"categories":2886},[65],{"categories":2888},[65],{"categories":2890},[65],{"categories":2892},[224],{"categories":2894},[155],{"categories":2896},[65],{"categories":2898},[65],{"categories":2900},[1560],{"categories":2902},[113],{"categories":2904},[65],{"categories":2906},[65],{"categories":2908},[199],{"categories":2910},[65],{"categories":2912},[155],{"categories":2914},[121],{"categories":2916},[],{"categories":2918},[65],{"categories":2920},[65],{"categories":2922},[196],{"categories":2924},[65],{"categories":2926},[224],{"categories":2928},[65],{"categories":2930},[121],{"categories":2932},[],{"categories":2934},[],{"categories":2936},[],{"categories":2938},[113],{"categories":2940},[155],{"categories":2942},[121],{"categories":2944},[65],{"categories":2946},[65],{"categories":2948},[65],{"categories":2950},[368],{"categories":2952},[196],{"categories":2954},[121],{"categories":2956},[65],{"categories":2958},[],{"categories":2960},[121],{"categories":2962},[121],{"categories":2964},[],{"categories":2966},[65],{"categories":2968},[121],{"categories":2970},[65],{"categories":2972},[],{"categories":2974},[65],{"categories":2976},[65],{"categories":2978},[155],{"categories":2980},[196],{"categories":2982},[121],{"categories":2984},[196],{"categories":2986},[121],{"categories":2988},[65],{"categories":2990},[116],{"categories":2992},[],{"categories":2994},[],{"categories":2996},[65],{"categories":2998},[65],{"categories":3000},[113],{"categories":3002},[121],{"categories":3004},[155],{"categories":3006},[],{"categories":3008},[196],{"categories":3010},[],{"categories":3012},[133],{"categories":3014},[65],{"categories":3016},[133],{"categories":3018},[196],{"categories":3020},[133],{"categories":3022},[65],{"categories":3024},[],{"categories":3026},[65],{"categories":3028},[65],{"categories":3030},[],{"categories":3032},[65],{"categories":3034},[224],{"categories":3036},[65],{"categories":3038},[259],{"categories":3040},[133],{"categories":3042},[],{"categories":3044},[121],{"categories":3046},[65],{"categories":3048},[113],{"categories":3050},[465],{"categories":3052},[65],{"categories":3054},[121],{"categories":3056},[121],{"categories":3058},[65],{"categories":3060},[65],{"categories":3062},[],{"categories":3064},[65],{"categories":3066},[113],{"categories":3068},[65],{"categories":3070},[116],{"categories":3072},[133],{"categories":3074},[196],{"categories":3076},[],{"categories":3078},[],{"categories":3080},[],{"categories":3082},[121],{"categories":3084},[133],{"categories":3086},[196],{"categories":3088},[155],{"categories":3090},[65],{"categories":3092},[155],{"categories":3094},[121],{"categories":3096},[196],{"categories":3098},[65],{"categories":3100},[],{"categories":3102},[65],{"categories":3104},[144],{"categories":3106},[121],{"categories":3108},[196],{"categories":3110},[155],{"categories":3112},[116],{"categories":3114},[133],{"categories":3116},[65],{"categories":3118},[65],{"categories":3120},[155],{"categories":3122},[224],{"categories":3124},[],{"categories":3126},[],{"categories":3128},[199],{"categories":3130},[414],{"categories":3132},[65],{"categories":3134},[121],{"categories":3136},[65,133],{"categories":3138},[155],{"categories":3140},[65],{"categories":3142},[65],{"categories":3144},[65],{"categories":3146},[65],{"categories":3148},[121],{"categories":3150},[65],{"categories":3152},[121],{"categories":3154},[65],{"categories":3156},[65],{"categories":3158},[],{"categories":3160},[65],{"categories":3162},[1076],{"categories":3164},[133],{"categories":3166},[196],{"categories":3168},[65],{"categories":3170},[65],{"categories":3172},[65],{"categories":3174},[199],{"categories":3176},[121],{"categories":3178},[224],{"categories":3180},[259],{"categories":3182},[],{"categories":3184},[65],{"categories":3186},[116],{"categories":3188},[121],{"categories":3190},[113],{"categories":3192},[121],{"categories":3194},[65],{"categories":3196},[121],{"categories":3198},[124],{"categories":3200},[133],{"categories":3202},[65],{"categories":3204},[65],{"categories":3206},[],{"categories":3208},[],{"categories":3210},[],{"categories":3212},[259],{"categories":3214},[65],{"categories":3216},[155],{"categories":3218},[65],{"categories":3220},[65],{"categories":3222},[65],{"categories":3224},[65],{"categories":3226},[],{"categories":3228},[199],{"categories":3230},[116],{"categories":3232},[121],{"categories":3234},[65],{"categories":3236},[],{"categories":3238},[65],{"categories":3240},[121],{"categories":3242},[65],{"categories":3244},[259],{"categories":3246},[],{"categories":3248},[196],{"categories":3250},[196],{"categories":3252},[],{"categories":3254},[133],{"categories":3256},[65],{"categories":3258},[196],{"categories":3260},[65],{"categories":3262},[116],{"categories":3264},[121],{"categories":3266},[65],{"categories":3268},[],{"categories":3270},[155],{"categories":3272},[65],{"categories":3274},[65],{"categories":3276},[65],{"categories":3278},[196],{"categories":3280},[121],{"categories":3282},[155],{"categories":3284},[],{"categories":3286},[121],{"categories":3288},[116],{"categories":3290},[121],{"categories":3292},[196],{"categories":3294},[65],{"categories":3296},[65],{"categories":3298},[65],{"categories":3300},[414],{"categories":3302},[65],{"categories":3304},[],{"categories":3306},[65],{"categories":3308},[65],{"categories":3310},[259],{"categories":3312},[155],{"categories":3314},[199],{"categories":3316},[501],{"categories":3318},[199],{"categories":3320},[65],{"categories":3322},[],{"categories":3324},[],{"categories":3326},[],{"categories":3328},[121],{"categories":3330},[121],{"categories":3332},[133],{"categories":3334},[65],{"categories":3336},[395],{"categories":3338},[133],{"categories":3340},[65],{"categories":3342},[65],{"categories":3344},[65],{"categories":3346},[65],{"categories":3348},[121],{"categories":3350},[],{"categories":3352},[],{"categories":3354},[65],{"categories":3356},[],{"categories":3358},[65],{"categories":3360},[121],{"categories":3362},[196],{"categories":3364},[65],{"categories":3366},[65],{"categories":3368},[],{"categories":3370},[121],{"categories":3372},[124],{"categories":3374},[65],{"categories":3376},[196],{"categories":3378},[65],{"categories":3380},[121],{"categories":3382},[116],{"categories":3384},[65],{"categories":3386},[224],{"categories":3388},[121],{"categories":3390},[65],{"categories":3392},[65],{"categories":3394},[771],{"categories":3396},[65],{"categories":3398},[121],{"categories":3400},[65],{"categories":3402},[133],{"categories":3404},[65],{"categories":3406},[465],{"categories":3408},[196],{"categories":3410},[],{"categories":3412},[155],{"categories":3414},[414],{"categories":3416},[121],{"categories":3418},[65],{"categories":3420},[],{"categories":3422},[155],{"categories":3424},[347],{"categories":3426},[121],{"categories":3428},[121],{"categories":3430},[65],{"categories":3432},[65],{"categories":3434},[121],{"categories":3436},[],{"categories":3438},[65],{"categories":3440},[116],{"categories":3442},[121],{"categories":3444},[],{"categories":3446},[133],{"categories":3448},[65],{"categories":3450},[65],{"categories":3452},[113],{"categories":3454},[155],{"categories":3456},[259],{"categories":3458},[144],{"categories":3460},[121],{"categories":3462},[121],{"categories":3464},[65],{"categories":3466},[121],{"categories":3468},[65],{"categories":3470},[113],{"categories":3472},[],{"categories":3474},[65],{"categories":3476},[65],{"categories":3478},[65],{"categories":3480},[],{"categories":3482},[],{"categories":3484},[196],{"categories":3486},[121],{"categories":3488},[65,116],{"categories":3490},[121],{"categories":3492},[65],{"categories":3494},[],{"categories":3496},[113],{"categories":3498},[199],{"categories":3500},[116],{"categories":3502},[65],{"categories":3504},[133],{"categories":3506},[65],{"categories":3508},[121],{"categories":3510},[65],{"categories":3512},[65],{"categories":3514},[65],{"categories":3516},[155],{"categories":3518},[1076],{"categories":3520},[121],{"categories":3522},[65],{"categories":3524},[],{"categories":3526},[],{"categories":3528},[65],{"categories":3530},[121],{"categories":3532},[65],{"categories":3534},[65],{"categories":3536},[259],{"categories":3538},[],{"categories":3540},[65],{"categories":3542},[121],{"categories":3544},[144],{"categories":3546},[121],{"categories":3548},[414],{"categories":3550},[],{"categories":3552},[368],{"categories":3554},[121],{"categories":3556},[65],{"categories":3558},[224],{"categories":3560},[65],{"categories":3562},[199],{"categories":3564},[121],{"categories":3566},[65],{"categories":3568},[414],{"categories":3570},[65],{"categories":3572},[259],{"categories":3574},[],{"categories":3576},[65],{"categories":3578},[224],{"categories":3580},[196],{"categories":3582},[65],{"categories":3584},[65],{"categories":3586},[65],{"categories":3588},[],{"categories":3590},[224],{"categories":3592},[155],{"categories":3594},[65],{"categories":3596},[65],{"categories":3598},[501],{"categories":3600},[113],{"categories":3602},[65],{"categories":3604},[],{"categories":3606},[],{"categories":3608},[196],{"categories":3610},[65],{"categories":3612},[199],{"categories":3614},[224],{"categories":3616},[121],{"categories":3618},[65],{"categories":3620},[224],{"categories":3622},[155],{"categories":3624},[],{"categories":3626},[65],{"categories":3628},[65],{"categories":3630},[],{"categories":3632},[65],{"categories":3634},[65],{"categories":3636},[524],{"categories":3638},[65],{"categories":3640},[65],{"categories":3642},[121],{"categories":3644},[133],{"categories":3646},[414],{"categories":3648},[65],{"categories":3650},[65],{"categories":3652},[65],{"categories":3654},[],{"categories":3656},[65,133],{"categories":3658},[155],{"categories":3660},[121],{"categories":3662},[133],{"categories":3664},[121],{"categories":3666},[805],{"categories":3668},[133],{"categories":3670},[65],{"categories":3672},[113],{"categories":3674},[],{"categories":3676},[],{"categories":3678},[121],{"categories":3680},[65],{"categories":3682},[133],{"categories":3684},[65],{"categories":3686},[113],{"categories":3688},[133],{"categories":3690},[133],{"categories":3692},[65],{"categories":3694},[224],{"categories":3696},[65],{"categories":3698},[133],{"categories":3700},[65],{"categories":3702},[],{"categories":3704},[65],{"categories":3706},[196,65],{"categories":3708},[259],{"categories":3710},[113],{"categories":3712},[],{"categories":3714},[65],{"categories":3716},[65],{"categories":3718},[116],{"categories":3720},[116],{"categories":3722},[65],{"categories":3724},[65],{"categories":3726},[347],{"categories":3728},[65],{"categories":3730},[133],{"categories":3732},[199],{"categories":3734},[121],{"categories":3736},[133],{"categories":3738},[65],{"categories":3740},[65],{"categories":3742},[155],{"categories":3744},[224],{"categories":3746},[196],{"categories":3748},[65],{"categories":3750},[65],{"categories":3752},[65],{"categories":3754},[65],{"categories":3756},[113],{"categories":3758},[65],{"categories":3760},[121],{"categories":3762},[121],{"categories":3764},[133],{"categories":3766},[155],{"categories":3768},[133],{"categories":3770},[133],{"categories":3772},[65],{"categories":3774},[],{"categories":3776},[],{"categories":3778},[199],{"categories":3780},[65],{"categories":3782},[133],{"categories":3784},[65],{"categories":3786},[196],{"categories":3788},[414],{"categories":3790},[368],{"categories":3792},[347],{"categories":3794},[65],{"categories":3796},[65],{"categories":3798},[65],{"categories":3800},[199],{"categories":3802},[65],{"categories":3804},[65],{"categories":3806},[65],{"categories":3808},[65],{"categories":3810},[65],{"categories":3812},[65],{"categories":3814},[121],{"categories":3816},[113],{"categories":3818},[121],{"categories":3820},[65,116],{"categories":3822},[],{"categories":3824},[196],{"categories":3826},[],{"categories":3828},[124],{"categories":3830},[65],{"categories":3832},[155],{"categories":3834},[113],{"categories":3836},[113],{"categories":3838},[121],{"categories":3840},[121],{"categories":3842},[121],{"categories":3844},[65],{"categories":3846},[65],{"categories":3848},[116],{"categories":3850},[121],{"categories":3852},[133],{"categories":3854},[224],{"categories":3856},[65],{"categories":3858},[],{"categories":3860},[155],{"categories":3862},[65],{"categories":3864},[65],{"categories":3866},[65],{"categories":3868},[65],{"categories":3870},[65],{"categories":3872},[133],{"categories":3874},[155],{"categories":3876},[133],{"categories":3878},[133],{"categories":3880},[65],{"categories":3882},[65],{"categories":3884},[65],{"categories":3886},[368],{"categories":3888},[65],{"categories":3890},[121],{"categories":3892},[155],{"categories":3894},[65],{"categories":3896},[65],{"categories":3898},[65],{"categories":3900},[121],{"categories":3902},[65],{"categories":3904},[65],{"categories":3906},[65],{"categories":3908},[2697],{"categories":3910},[3911],"Clinical AI",{"categories":3913},[196],{"categories":3915},[65],{"categories":3917},[65],{"categories":3919},[65],{"categories":3921},[259],{"categories":3923},[2150],{"categories":3925},[65],{"categories":3927},[124],{"categories":3929},[65],{"categories":3931},[121],{"categories":3933},[65],{"categories":3935},[65],{"categories":3937},[155],{"categories":3939},[65],{"categories":3941},[121],{"categories":3943},[133],{"categories":3945},[224],{"categories":3947},[65],{"categories":3949},[65],{"categories":3951},[116],{"categories":3953},[65],{"categories":3955},[65],{"categories":3957},[465],{"categories":3959},[65],{"categories":3961},[],{"categories":3963},[65],{"categories":3965},[133],{"categories":3967},[113],{"categories":3969},[65],{"categories":3971},[],{"categories":3973},[],{"categories":3975},[65],{"categories":3977},[],{"categories":3979},[116],{"categories":3981},[65],{"categories":3983},[121],{"categories":3985},[155],{"categories":3987},[155],{"categories":3989},[155],{"categories":3991},[155],{"categories":3993},[],{"categories":3995},[113],{"categories":3997},[121],{"categories":3999},[155],{"categories":4001},[65],{"categories":4003},[524],{"categories":4005},[124],{"categories":4007},[65],{"categories":4009},[113],{"categories":4011},[65],{"categories":4013},[121],{"categories":4015},[65],{"categories":4017},[65],{"categories":4019},[65,121],{"categories":4021},[121],{"categories":4023},[259],{"categories":4025},[155],{"categories":4027},[121],{"categories":4029},[155],{"categories":4031},[121],{"categories":4033},[65],{"categories":4035},[],{"categories":4037},[155],{"categories":4039},[224],{"categories":4041},[113],{"categories":4043},[65],{"categories":4045},[65],{"categories":4047},[],{"categories":4049},[133],{"categories":4051},[],{"categories":4053},[113],{"categories":4055},[121],{"categories":4057},[155],{"categories":4059},[65],{"categories":4061},[155],{"categories":4063},[113],{"categories":4065},[155],{"categories":4067},[155],{"categories":4069},[],{"categories":4071},[116],{"categories":4073},[121],{"categories":4075},[155],{"categories":4077},[155],{"categories":4079},[155],{"categories":4081},[155],{"categories":4083},[155],{"categories":4085},[155],{"categories":4087},[155],{"categories":4089},[155],{"categories":4091},[155],{"categories":4093},[155],{"categories":4095},[199],{"categories":4097},[113],{"categories":4099},[65],{"categories":4101},[65],{"categories":4103},[121],{"categories":4105},[121],{"categories":4107},[],{"categories":4109},[65,113],{"categories":4111},[],{"categories":4113},[121],{"categories":4115},[65],{"categories":4117},[155],{"categories":4119},[121],{"categories":4121},[805],{"categories":4123},[65],{"categories":4125},[65],{"categories":4127},[65],{"categories":4129},[65],{"categories":4131},[65],{"categories":4133},[347],{"categories":4135},[65],{"categories":4137},[121],{"categories":4139},[116],{"categories":4141},[121],{"categories":4143},[121],{"categories":4145},[],{"categories":4147},[121],{"categories":4149},[196],{"categories":4151},[155],{"categories":4153},[65],{"categories":4155},[],{"categories":4157},[124],{"categories":4159},[],{"categories":4161},[133],{"categories":4163},[121],{"categories":4165},[196],{"categories":4167},[65],{"categories":4169},[],{"categories":4171},[65],{"categories":4173},[],{"categories":4175},[224],{"categories":4177},[65],{"categories":4179},[],{"categories":4181},[],{"categories":4183},[155],{"categories":4185},[113],{"categories":4187},[65],{"categories":4189},[65],{"categories":4191},[116],{"categories":4193},[65],{"categories":4195},[65],{"categories":4197},[65],{"categories":4199},[116],{"categories":4201},[196],{"categories":4203},[],{"categories":4205},[65],{"categories":4207},[155],{"categories":4209},[],{"categories":4211},[65],{"categories":4213},[65],{"categories":4215},[196],{"categories":4217},[65],{"categories":4219},[224],{"categories":4221},[65],{"categories":4223},[259],{"categories":4225},[],{"categories":4227},[121],{"categories":4229},[224],{"categories":4231},[133],{"categories":4233},[],{"categories":4235},[65],{"categories":4237},[],{"categories":4239},[121],{"categories":4241},[196],{"categories":4243},[133],{"categories":4245},[],{"categories":4247},[2697],{"categories":4249},[116],{"categories":4251},[113],{"categories":4253},[65],{"categories":4255},[199],{"categories":4257},[121],{"categories":4259},[196],{"categories":4261},[133],{"categories":4263},[],{"categories":4265},[],{"categories":4267},[65],{"categories":4269},[113],{"categories":4271},[65],{"categories":4273},[224],{"categories":4275},[],{"categories":4277},[121],{"categories":4279},[121],{"categories":4281},[65],{"categories":4283},[121],{"categories":4285},[65],{"categories":4287},[155],{"categories":4289},[133],{"categories":4291},[65],{"categories":4293},[121],{"categories":4295},[124],{"categories":4297},[65],{"categories":4299},[65],{"categories":4301},[121],{"categories":4303},[65],{"categories":4305},[124],{"categories":4307},[224],{"categories":4309},[155],{"categories":4311},[],{"categories":4313},[224],{"categories":4315},[65],{"categories":4317},[],{"categories":4319},[133],{"categories":4321},[121],{"categories":4323},[],{"categories":4325},[65],{"categories":4327},[65],{"categories":4329},[65],{"categories":4331},[65],{"categories":4333},[121],{"categories":4335},[116],{"categories":4337},[113],{"categories":4339},[65],{"categories":4341},[196],{"categories":4343},[133],{"categories":4345},[133],{"categories":4347},[65],{"categories":4349},[199],{"categories":4351},[121],{"categories":4353},[65],{"categories":4355},[65],{"categories":4357},[121],{"categories":4359},[65],{"categories":4361},[116],{"categories":4363},[196],{"categories":4365},[133],{"categories":4367},[121],{"categories":4369},[65],{"categories":4371},[124],{"categories":4373},[65],{"categories":4375},[121],{"categories":4377},[65],{"categories":4379},[155],{"categories":4381},[],{"categories":4383},[113],{"categories":4385},[65],{"categories":4387},[65],{"categories":4389},[65],{"categories":4391},[133],{"categories":4393},[133],{"categories":4395},[65],{"categories":4397},[133],{"categories":4399},[65],{"categories":4401},[121],{"categories":4403},[65],{"categories":4405},[65],{"categories":4407},[65],{"categories":4409},[65],{"categories":4411},[65],{"categories":4413},[],{"categories":4415},[65],{"categories":4417},[196],{"categories":4419},[116],{"categories":4421},[155],{"categories":4423},[121],{"categories":4425},[65],{"categories":4427},[65],{"categories":4429},[196],{"categories":4431},[121],{"categories":4433},[65],{"categories":4435},[224],{"categories":4437},[65],{"categories":4439},[199],{"categories":4441},[65],{"categories":4443},[65],{"categories":4445},[155],{"categories":4447},[65],{"categories":4449},[65],{"categories":4451},[65],{"categories":4453},[121],{"categories":4455},[259],{"categories":4457},[65],{"categories":4459},[133],{"categories":4461},[121],{"categories":4463},[199],{"categories":4465},[],{"categories":4467},[121],{"categories":4469},[133],{"categories":4471},[65],{"categories":4473},[2004],{"categories":4475},[196],{"categories":4477},[288],{"categories":4479},[65],{"categories":4481},[65],{"categories":4483},[113],{"categories":4485},[133],{"categories":4487},[116],{"categories":4489},[133],{"categories":4491},[65],{"categories":4493},[],{"categories":4495},[121],{"categories":4497},[121],{"categories":4499},[65],{"categories":4501},[65],{"categories":4503},[199],{"categories":4505},[],{"categories":4507},[155],{"categories":4509},[],{"categories":4511},[155],{"categories":4513},[65],{"categories":4515},[65],{"categories":4517},[121],{"categories":4519},[65],{"categories":4521},[121],{"categories":4523},[121],{"categories":4525},[],{"categories":4527},[155],{"categories":4529},[65],{"categories":4531},[],{"categories":4533},[65],{"categories":4535},[65],{"categories":4537},[],{"categories":4539},[196],{"categories":4541},[133],{"categories":4543},[121],{"categories":4545},[65],{"categories":4547},[65],{"categories":4549},[224],{"categories":4551},[65],{"categories":4553},[65],{"categories":4555},[65],{"categories":4557},[113],{"categories":4559},[65],{"categories":4561},[],{"categories":4563},[65],{"categories":4565},[65],{"categories":4567},[],{"categories":4569},[113],{"categories":4571},[155],{"categories":4573},[133],{"categories":4575},[124],{"categories":4577},[414],{"categories":4579},[65],{"categories":4581},[65],{"categories":4583},[65],{"categories":4585},[133],{"categories":4587},[155],{"categories":4589},[196],{"categories":4591},[65],{"categories":4593},[65],{"categories":4595},[65],{"categories":4597},[155],{"categories":4599},[196],{"categories":4601},[65],{"categories":4603},[65],{"categories":4605},[155],{"categories":4607},[196],{"categories":4609},[65],{"categories":4611},[155],{"categories":4613},[121],{"categories":4615},[121],{"categories":4617},[121],{"categories":4619},[133],{"categories":4621},[155],{"categories":4623},[121],{"categories":4625},[121],{"categories":4627},[65],{"categories":4629},[133],{"categories":4631},[196],{"categories":4633},[65],{"categories":4635},[65],{"categories":4637},[],{"categories":4639},[121],{"categories":4641},[],{"categories":4643},[65],{"categories":4645},[65],{"categories":4647},[],{"categories":4649},[],{"categories":4651},[121],{"categories":4653},[116],{"categories":4655},[121],{"categories":4657},[4658],"Liability & Ethics",{"categories":4660},[65],{"categories":4662},[121],{"categories":4664},[113],{"categories":4666},[121],{"categories":4668},[116],{"categories":4670},[224],{"categories":4672},[121],{"categories":4674},[65],{"categories":4676},[],{"categories":4678},[501],{"categories":4680},[121],{"categories":4682},[],{"categories":4684},[113],{"categories":4686},[121],{"categories":4688},[],{"categories":4690},[121],{"categories":4692},[65],{"categories":4694},[65],{"categories":4696},[65],{"categories":4698},[155],{"categories":4700},[65],{"categories":4702},[65],{"categories":4704},[121],{"categories":4706},[65],{"categories":4708},[65],{"categories":4710},[65],{"categories":4712},[155],{"categories":4714},[121],{"categories":4716},[133],{"categories":4718},[196],{"categories":4720},[113],{"categories":4722},[65],{"categories":4724},[65],{"categories":4726},[],{"categories":4728},[121],{"categories":4730},[121],{"categories":4732},[414],{"categories":4734},[196],{"categories":4736},[259],{"categories":4738},[155],{"categories":4740},[65],{"categories":4742},[196],{"categories":4744},[65],{"categories":4746},[113],{"categories":4748},[],{"categories":4750},[121],{"categories":4752},[65],{"categories":4754},[65],{"categories":4756},[121],{"categories":4758},[65],{"categories":4760},[196],{"categories":4762},[],{"categories":4764},[121],{"categories":4766},[124],{"categories":4768},[155],{"categories":4770},[121],{"categories":4772},[116],{"categories":4774},[],{"categories":4776},[65],{"categories":4778},[124],{"categories":4780},[65],{"categories":4782},[121],{"categories":4784},[155],{"categories":4786},[113],{"categories":4788},[259],{"categories":4790},[65],{"categories":4792},[65],{"categories":4794},[65],{"categories":4796},[155],{"categories":4798},[116],{"categories":4800},[65],{"categories":4802},[196],{"categories":4804},[155],{"categories":4806},[259],{"categories":4808},[65],{"categories":4810},[121],{"categories":4812},[],{"categories":4814},[465],{"categories":4816},[],{"categories":4818},[65],{"categories":4820},[259],{"categories":4822},[199],{"categories":4824},[121],{"categories":4826},[121],{"categories":4828},[4829],"Design News & Tools",{"categories":4831},[65],{"categories":4833},[155],{"categories":4835},[65],{"categories":4837},[65],{"categories":4839},[113],{"categories":4841},[65],{"categories":4843},[196],{"categories":4845},[121],{"categories":4847},[121],{"categories":4849},[196],{"categories":4851},[65],{"categories":4853},[414],{"categories":4855},[121],{"categories":4857},[65],{"categories":4859},[65],{"categories":4861},[414],{"categories":4863},[65],{"categories":4865},[224],{"categories":4867},[65],{"categories":4869},[121],{"categories":4871},[],{"categories":4873},[65],{"categories":4875},[65],{"categories":4877},[65],{"categories":4879},[155],{"categories":4881},[113],{"categories":4883},[],{"categories":4885},[65],{"categories":4887},[65],{"categories":4889},[133],{"categories":4891},[524],{"categories":4893},[133],{"categories":4895},[196],{"categories":4897},[65],{"categories":4899},[65,121],{"categories":4901},[224,116],{"categories":4903},[65],{"categories":4905},[65],{"categories":4907},[65],{"categories":4909},[],{"categories":4911},[121],{"categories":4913},[],{"categories":4915},[133],{"categories":4917},[65],{"categories":4919},[133],{"categories":4921},[],{"categories":4923},[121],{"categories":4925},[65],{"categories":4927},[155],{"categories":4929},[65],{"categories":4931},[],{"categories":4933},[121],{"categories":4935},[65],{"categories":4937},[],{"categories":4939},[196],{"categories":4941},[65],{"categories":4943},[121],{"categories":4945},[65],{"categories":4947},[65],{"categories":4949},[113],{"categories":4951},[121],{"categories":4953},[65],{"categories":4955},[],{"categories":4957},[259],{"categories":4959},[224],{"categories":4961},[116],{"categories":4963},[116],{"categories":4965},[65],{"categories":4967},[113],{"categories":4969},[113],{"categories":4971},[65],{"categories":4973},[121],{"categories":4975},[65],{"categories":4977},[65],{"categories":4979},[65],{"categories":4981},[133],{"categories":4983},[65],{"categories":4985},[113],{"categories":4987},[65],{"categories":4989},[121],{"categories":4991},[65],{"categories":4993},[224],{"categories":4995},[65],{"categories":4997},[155],{"categories":4999},[65],{"categories":5001},[65],{"categories":5003},[121],{"categories":5005},[65],{"categories":5007},[],{"categories":5009},[133],{"categories":5011},[],{"categories":5013},[133],{"categories":5015},[121],{"categories":5017},[113],{"categories":5019},[],{"categories":5021},[199],{"categories":5023},[259],{"categories":5025},[65],{"categories":5027},[133],{"categories":5029},[65],{"categories":5031},[],{"categories":5033},[155],{"categories":5035},[121],{"categories":5037},[133],{"categories":5039},[196],{"categories":5041},[65],{"categories":5043},[65],{"categories":5045},[121],{"categories":5047},[133],{"categories":5049},[121],{"categories":5051},[155],{"categories":5053},[65],{"categories":5055},[124],{"categories":5057},[113],{"categories":5059},[124],{"categories":5061},[155],{"categories":5063},[133],{"categories":5065},[65],{"categories":5067},[196],{"categories":5069},[116],{"categories":5071},[65],{"categories":5073},[65],{"categories":5075},[65],{"categories":5077},[65],{"categories":5079},[65],{"categories":5081},[121],{"categories":5083},[65],{"categories":5085},[121],{"categories":5087},[65],{"categories":5089},[65],{"categories":5091},[113],{"categories":5093},[65],{"categories":5095},[121],{"categories":5097},[121],{"categories":5099},[196],{"categories":5101},[121],{"categories":5103},[121],{"categories":5105},[113],{"categories":5107},[121],{"categories":5109},[196],{"categories":5111},[],{"categories":5113},[65],{"categories":5115},[199],{"categories":5117},[414],{"categories":5119},[65],{"categories":5121},[65],{"categories":5123},[65],{"categories":5125},[133],{"categories":5127},[65],{"categories":5129},[],{"categories":5131},[121],{"categories":5133},[224],{"categories":5135},[65],{"categories":5137},[155],{"categories":5139},[121],{"categories":5141},[65],{"categories":5143},[224],{"categories":5145},[121],{"categories":5147},[116],{"categories":5149},[116],{"categories":5151},[65],{"categories":5153},[65],{"categories":5155},[65],{"categories":5157},[113],{"categories":5159},[],{"categories":5161},[65],{"categories":5163},[65],{"categories":5165},[121],{"categories":5167},[121],{"categories":5169},[65],{"categories":5171},[65],{"categories":5173},[65],{"categories":5175},[133],{"categories":5177},[],{"categories":5179},[113],{"categories":5181},[65],{"categories":5183},[65],{"categories":5185},[121],{"categories":5187},[121],{"categories":5189},[],{"categories":5191},[133],{"categories":5193},[133],{"categories":5195},[65],{"categories":5197},[224],{"categories":5199},[116],{"categories":5201},[196],{"categories":5203},[],{"categories":5205},[65],{"categories":5207},[121],{"categories":5209},[113],{"categories":5211},[65],{"categories":5213},[133],{"categories":5215},[113],{"categories":5217},[155],{"categories":5219},[199],{"categories":5221},[155],{"categories":5223},[121],{"categories":5225},[],{"categories":5227},[155],{"categories":5229},[121],{"categories":5231},[196],{"categories":5233},[199],{"categories":5235},[65],{"categories":5237},[],{"categories":5239},[121],{"categories":5241},[121],{"categories":5243},[2697],{"categories":5245},[155],{"categories":5247},[133],{"categories":5249},[65],{"categories":5251},[65],{"categories":5253},[65],{"categories":5255},[65],{"categories":5257},[116],{"categories":5259},[65],{"categories":5261},[113],{"categories":5263},[1560],{"categories":5265},[259],{"categories":5267},[113],{"categories":5269},[],{"categories":5271},[],{"categories":5273},[155],{"categories":5275},[121],{"categories":5277},[196],{"categories":5279},[65],{"categories":5281},[155],{"categories":5283},[],{"categories":5285},[121],{"categories":5287},[121],{"categories":5289},[121],{"categories":5291},[],{"categories":5293},[65],{"categories":5295},[],{"categories":5297},[155],{"categories":5299},[113],{"categories":5301},[196],{"categories":5303},[65],{"categories":5305},[121],{"categories":5307},[155],{"categories":5309},[65],{"categories":5311},[155],{"categories":5313},[],{"categories":5315},[155],{"categories":5317},[113],{"categories":5319},[414],{"categories":5321},[121],{"categories":5323},[65],{"categories":5325},[],{"categories":5327},[133],{"categories":5329},[121],{"categories":5331},[124],{"categories":5333},[121],{"categories":5335},[113],{"categories":5337},[],{"categories":5339},[],{"categories":5341},[],{"categories":5343},[196],{"categories":5345},[121],{"categories":5347},[65],{"categories":5349},[65],{"categories":5351},[],{"categories":5353},[],{"categories":5355},[],{"categories":5357},[196],{"categories":5359},[65],{"categories":5361},[],{"categories":5363},[121],{"categories":5365},[65],{"categories":5367},[113],{"categories":5369},[],{"categories":5371},[],{"categories":5373},[65],{"categories":5375},[196],{"categories":5377},[65],{"categories":5379},[155],{"categories":5381},[],{"categories":5383},[65],{"categories":5385},[224],{"categories":5387},[155],{"categories":5389},[224],{"categories":5391},[199],{"categories":5393},[65],{"categories":5395},[65],{"categories":5397},[],{"categories":5399},[],{"categories":5401},[121],{"categories":5403},[],{"categories":5405},[65],{"categories":5407},[414],{"categories":5409},[65],{"categories":5411},[65],{"categories":5413},[65],{"categories":5415},[65],{"categories":5417},[],{"categories":5419},[121],{"categories":5421},[65],{"categories":5423},[65],{"categories":5425},[],{"categories":5427},[121],{"categories":5429},[65],{"categories":5431},[155],{"categories":5433},[65],{"categories":5435},[224],{"categories":5437},[116],{"categories":5439},[65],{"categories":5441},[65],{"categories":5443},[121],{"categories":5445},[199],{"categories":5447},[121],{"categories":5449},[121],{"categories":5451},[],{"categories":5453},[121],{"categories":5455},[],{"categories":5457},[65],{"categories":5459},[],{"categories":5461},[155],{"categories":5463},[116],{"categories":5465},[],{"categories":5467},[65],{"categories":5469},[],{"categories":5471},[196],{"categories":5473},[113],{"categories":5475},[],{"categories":5477},[116],{"categories":5479},[224],{"categories":5481},[65],{"categories":5483},[133],{"categories":5485},[113],{"categories":5487},[199],{"categories":5489},[116],{"categories":5491},[133],{"categories":5493},[121],{"categories":5495},[133],{"categories":5497},[],{"categories":5499},[124],{"categories":5501},[65],{"categories":5503},[],{"categories":5505},[121],{"categories":5507},[113],{"categories":5509},[196],{"categories":5511},[65],{"categories":5513},[113],{"categories":5515},[121],{"categories":5517},[259],{"categories":5519},[65],{"categories":5521},[65],{"categories":5523},[65],{"categories":5525},[113],{"categories":5527},[199],{"categories":5529},[121],{"categories":5531},[],{"categories":5533},[65],{"categories":5535},[65],{"categories":5537},[133],{"categories":5539},[121],{"categories":5541},[155],{"categories":5543},[133],{"categories":5545},[65],{"categories":5547},[124],{"categories":5549},[],{"categories":5551},[196],{"categories":5553},[155],{"categories":5555},[113],{"categories":5557},[121],{"categories":5559},[65],{"categories":5561},[65],{"categories":5563},[121],{"categories":5565},[124],{"categories":5567},[65],{"categories":5569},[121],{"categories":5571},[65],{"categories":5573},[116],{"categories":5575},[121],{"categories":5577},[121,259],{"categories":5579},[65],{"categories":5581},[65],{"categories":5583},[121],{"categories":5585},[133],{"categories":5587},[65],{"categories":5589},[65],{"categories":5591},[199],{"categories":5593},[121],{"categories":5595},[224],{"categories":5597},[121],{"categories":5599},[116],{"categories":5601},[],{"categories":5603},[121],{"categories":5605},[65],{"categories":5607},[116],{"categories":5609},[],{"categories":5611},[],{"categories":5613},[133],{"categories":5615},[65],{"categories":5617},[65],{"categories":5619},[121],{"categories":5621},[199],{"categories":5623},[224],{"categories":5625},[65],{"categories":5627},[65],{"categories":5629},[121],{"categories":5631},[],{"categories":5633},[121],{"categories":5635},[155],{"categories":5637},[121],{"categories":5639},[],{"categories":5641},[155],{"categories":5643},[133],{"categories":5645},[2697],{"categories":5647},[113],{"categories":5649},[133],{"categories":5651},[65],{"categories":5653},[121],{"categories":5655},[65],{"categories":5657},[65],{"categories":5659},[224],{"categories":5661},[133],{"categories":5663},[],{"categories":5665},[155],{"categories":5667},[65],{"categories":5669},[],{"categories":5671},[121],{"categories":5673},[65],{"categories":5675},[65],{"categories":5677},[65],{"categories":5679},[65],{"categories":5681},[121],{"categories":5683},[65],{"categories":5685},[65],{"categories":5687},[124],{"categories":5689},[65],{"categories":5691},[121],{"categories":5693},[65],{"categories":5695},[65],{"categories":5697},[65],{"categories":5699},[65],{"categories":5701},[65],{"categories":5703},[65],{"categories":5705},[116],{"categories":5707},[],{"categories":5709},[124],{"categories":5711},[155],{"categories":5713},[121],{"categories":5715},[65],{"categories":5717},[133],{"categories":5719},[],{"categories":5721},[133],{"categories":5723},[133],{"categories":5725},[121],{"categories":5727},[133],{"categories":5729},[65],{"categories":5731},[65],{"categories":5733},[65],{"categories":5735},[121],{"categories":5737},[133],{"categories":5739},[65],{"categories":5741},[65],{"categories":5743},[121],{"categories":5745},[155],{"categories":5747},[65],{"categories":5749},[65],{"categories":5751},[65],{"categories":5753},[116],{"categories":5755},[65],{"categories":5757},[121],{"categories":5759},[196],{"categories":5761},[],{"categories":5763},[65],{"categories":5765},[199],{"categories":5767},[121],{"categories":5769},[65],{"categories":5771},[65],{"categories":5773},[],{"categories":5775},[65],{"categories":5777},[65],{"categories":5779},[155],{"categories":5781},[65],{"categories":5783},[65],{"categories":5785},[121],{"categories":5787},[224],{"categories":5789},[],{"categories":5791},[],{"categories":5793},[133],{"categories":5795},[65],{"categories":5797},[155],{"categories":5799},[133],{"categories":5801},[155],{"categories":5803},[65],{"categories":5805},[224],{"categories":5807},[199],{"categories":5809},[65],{"categories":5811},[113],{"categories":5813},[121],{"categories":5815},[65],{"categories":5817},[121],{"categories":5819},[121],{"categories":5821},[65],{"categories":5823},[116],{"categories":5825},[],{"categories":5827},[199],{"categories":5829},[65],{"categories":5831},[],{"categories":5833},[155],{"categories":5835},[65],{"categories":5837},[199],{"categories":5839},[65],{"categories":5841},[133],{"categories":5843},[133],{"categories":5845},[133],{"categories":5847},[121],{"categories":5849},[121],{"categories":5851},[121],{"categories":5853},[65],{"categories":5855},[65],{"categories":5857},[196],{"categories":5859},[199],{"categories":5861},[199],{"categories":5863},[],{"categories":5865},[155],{"categories":5867},[65],{"categories":5869},[65],{"categories":5871},[133],{"categories":5873},[],{"categories":5875},[155],{"categories":5877},[155],{"categories":5879},[155],{"categories":5881},[],{"categories":5883},[121],{"categories":5885},[65],{"categories":5887},[],{"categories":5889},[113],{"categories":5891},[116],{"categories":5893},[],{"categories":5895},[65],{"categories":5897},[65],{"categories":5899},[],{"categories":5901},[133],{"categories":5903},[],{"categories":5905},[],{"categories":5907},[],{"categories":5909},[],{"categories":5911},[65],{"categories":5913},[155],{"categories":5915},[],{"categories":5917},[],{"categories":5919},[65],{"categories":5921},[65],{"categories":5923},[65],{"categories":5925},[199],{"categories":5927},[65],{"categories":5929},[199],{"categories":5931},[],{"categories":5933},[199],{"categories":5935},[199],{"categories":5937},[259],{"categories":5939},[121],{"categories":5941},[133],{"categories":5943},[],{"categories":5945},[],{"categories":5947},[199],{"categories":5949},[133],{"categories":5951},[133],{"categories":5953},[133],{"categories":5955},[],{"categories":5957},[113],{"categories":5959},[133],{"categories":5961},[133],{"categories":5963},[113],{"categories":5965},[133],{"categories":5967},[116],{"categories":5969},[133],{"categories":5971},[133],{"categories":5973},[133],{"categories":5975},[199],{"categories":5977},[155],{"categories":5979},[155],{"categories":5981},[65],{"categories":5983},[133],{"categories":5985},[199],{"categories":5987},[259],{"categories":5989},[199],{"categories":5991},[199],{"categories":5993},[199],{"categories":5995},[],{"categories":5997},[116],{"categories":5999},[],{"categories":6001},[259],{"categories":6003},[133],{"categories":6005},[133],{"categories":6007},[133],{"categories":6009},[121],{"categories":6011},[155,116],{"categories":6013},[199],{"categories":6015},[],{"categories":6017},[],{"categories":6019},[199],{"categories":6021},[],{"categories":6023},[199],{"categories":6025},[155],{"categories":6027},[121],{"categories":6029},[],{"categories":6031},[133],{"categories":6033},[65],{"categories":6035},[196],{"categories":6037},[],{"categories":6039},[65],{"categories":6041},[],{"categories":6043},[155],{"categories":6045},[113],{"categories":6047},[199],{"categories":6049},[],{"categories":6051},[133],{"categories":6053},[155],[6055,6162,6237,6314],{"id":6056,"title":6057,"ai":6058,"body":6063,"categories":6131,"created_at":66,"date_modified":66,"description":59,"extension":67,"faq":66,"featured":68,"kicker_label":66,"meta":6132,"navigation":89,"path":6146,"published_at":6147,"question":66,"scraped_at":6148,"seo":6149,"sitemap":6150,"source_id":6151,"source_name":6152,"source_type":6153,"source_url":6154,"stem":6155,"tags":6156,"thumbnail_url":6157,"tldr":6158,"tweet":6159,"unknown_tags":6160,"__hash__":6161},"summaries\u002Fsummaries\u002F1a6b27682bc5657a-optimizing-video-diffusion-for-real-time-generatio-summary.md","Optimizing Video Diffusion for Real-Time Generation",{"provider":7,"model":8,"input_tokens":6059,"output_tokens":6060,"processing_time_ms":6061,"cost_usd":6062},7266,665,4888,0.002814,{"type":14,"value":6064,"toc":6126},[6065,6069,6072,6076,6115,6119],[17,6066,6068],{"id":6067},"the-path-to-real-time-diffusion","The Path to Real-Time Diffusion",[22,6070,6071],{},"Standard diffusion models typically require 20 to 50 denoising steps, creating significant latency that hinders real-time applications like robotics or interactive content. Achieving real-time performance requires an additive approach, stacking three primary optimization techniques: quantization, caching, and distillation.",[17,6073,6075],{"id":6074},"three-pillars-of-optimization","Three Pillars of Optimization",[39,6077,6078,6089,6095],{},[42,6079,6080,6083,6084,6088],{},[45,6081,6082],{},"Quantization:"," This is the lowest-hanging fruit. While diffusion models are attention-heavy and less sensitive to quantization than LLMs, dynamic quantization (computing ranges on the fly) effectively reduces memory footprint and improves throughput. NVIDIA’s ",[6085,6086,6087],"code",{},"TRTLM"," repository provides pre-quantized checkpoints to simplify deployment.",[42,6090,6091,6094],{},[45,6092,6093],{},"Caching:"," By identifying redundant computations between denoising steps, caching skips re-processing latent chunks that remain static. Modern approaches use chunk-based caching, which isolates dynamic elements (like a moving speaker) from static backgrounds, significantly reducing redundant GPU cycles.",[42,6096,6097,6100,6101],{},[45,6098,6099],{},"Step Distillation:"," The most impactful technique, distillation trains a 'student' model to match a 'teacher' model's output in significantly fewer steps (e.g., 4, 8, or even 1).\n",[39,6102,6103,6109],{},[42,6104,6105,6108],{},[45,6106,6107],{},"Trajectory-based:"," The student learns to mimic the teacher's exact denoising path.",[42,6110,6111,6114],{},[45,6112,6113],{},"Distribution-based:"," The student only learns to land on the same final output. This is currently the preferred, higher-quality method.",[17,6116,6118],{"id":6117},"implementation-strategy","Implementation Strategy",[22,6120,6121,6122,6125],{},"NVIDIA’s ",[6085,6123,6124],{},"FastGen"," repository provides the necessary infrastructure to handle the complexity of sharding large models (20B–40B+ parameters) across multiple GPUs. The process is incremental: start with quantization to see if performance meets requirements, then layer in caching, and finally apply distillation for the most significant speedups. While distillation is a post-training technique requiring specific data and compute, it does not require the massive resources needed for initial pre-training, making it accessible on standard enterprise hardware like H100s or B200s.",{"title":59,"searchDepth":60,"depth":60,"links":6127},[6128,6129,6130],{"id":6067,"depth":60,"text":6068},{"id":6074,"depth":60,"text":6075},{"id":6117,"depth":60,"text":6118},[65],{"content_references":6133,"triage":6142},[6134,6138],{"type":72,"title":6124,"author":6135,"url":6136,"context":6137},"NVIDIA Research","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FFastGen","recommended",{"type":72,"title":6139,"author":6140,"url":6141,"context":6137},"TRTLM (TensorRT-LLM)","NVIDIA","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FTensorRT-LLM",{"relevance":6143,"novelty":85,"quality":85,"actionability":85,"composite":6144,"reasoning":6145},5,4.35,"Category: AI & LLMs. The article provides a detailed approach to optimizing video diffusion models for real-time generation, addressing a specific pain point of latency in AI applications. It outlines practical techniques like quantization, caching, and step distillation, making it actionable for developers looking to implement these optimizations.","\u002Fsummaries\u002F1a6b27682bc5657a-optimizing-video-diffusion-for-real-time-generatio-summary","2026-06-16 13:00:06","2026-06-17 12:56:17",{"title":6057,"description":59},{"loc":6146},"1a6b27682bc5657a","AI Engineer","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=gHs5ZiY80PM","summaries\u002F1a6b27682bc5657a-optimizing-video-diffusion-for-real-time-generatio-summary",[102,101,103,104],"https:\u002F\u002Fi.ytimg.com\u002Fvi\u002FgHs5ZiY80PM\u002Fhqdefault.jpg","Achieve real-time video generation by stacking quantization, caching, and step distillation to reduce the standard 50-step denoising process to as few as 1-8 steps.","This presentation outlines three technical strategies for reducing the latency of diffusion models: dynamic quantization, latent caching, and step distillation. The speaker explains how these methods can be combined to achieve real-time generation, with implementation details and tools available in the [FastGen](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FTensorRT-LLM) repository.",[],"c1TOl0LiL8H8OotgeIMeRvn9YfVIGnuc9eEFEeoKjmg",{"id":6163,"title":6164,"ai":6165,"body":6170,"categories":6214,"created_at":66,"date_modified":66,"description":59,"extension":67,"faq":66,"featured":68,"kicker_label":66,"meta":6215,"navigation":89,"path":6226,"published_at":6227,"question":66,"scraped_at":6227,"seo":6228,"sitemap":6229,"source_id":6230,"source_name":6231,"source_type":97,"source_url":6221,"stem":6232,"tags":6233,"thumbnail_url":66,"tldr":6234,"tweet":66,"unknown_tags":6235,"__hash__":6236},"summaries\u002Fsummaries\u002Fd5c54c878ef99cc8-sim2schedule-simulator-guided-llm-framework-for-mi-summary.md","Sim2Schedule: Simulator-Guided LLM Framework for Mine Scheduling",{"provider":7,"model":8,"input_tokens":6166,"output_tokens":6167,"processing_time_ms":6168,"cost_usd":6169},4057,538,3287,0.00182125,{"type":14,"value":6171,"toc":6210},[6172,6176,6179,6183,6186,6207],[17,6173,6175],{"id":6174},"the-challenge-of-autonomous-mine-scheduling","The Challenge of Autonomous Mine Scheduling",[22,6177,6178],{},"Open-pit mine scheduling is a high-stakes, multi-objective optimization problem that requires balancing production targets, equipment constraints, and geological variability. Traditional mathematical optimization methods often struggle with the dynamic, non-linear nature of these environments, while pure LLM-based approaches lack the domain-specific grounding required to ensure safety and operational feasibility. Sim2Schedule bridges this gap by integrating Large Language Models (LLMs) with specialized simulation environments to create a closed-loop planning system.",[17,6180,6182],{"id":6181},"the-sim2schedule-framework","The Sim2Schedule Framework",[22,6184,6185],{},"Sim2Schedule functions as an iterative, simulator-guided agent. Instead of relying on a single-shot prompt to generate a schedule, the framework employs a multi-step process:",[6187,6188,6189,6195,6201],"ol",{},[42,6190,6191,6194],{},[45,6192,6193],{},"Reasoning & Planning",": The LLM acts as the central planner, translating high-level production goals into actionable scheduling sequences.",[42,6196,6197,6200],{},[45,6198,6199],{},"Simulator Feedback Loop",": The generated schedule is executed within a domain-specific simulator. This simulator acts as a 'reality check,' identifying violations of operational constraints (e.g., equipment capacity, slope stability, or material flow bottlenecks).",[42,6202,6203,6206],{},[45,6204,6205],{},"Iterative Refinement",": The simulator provides structured feedback to the LLM, detailing the specific failures or inefficiencies found in the current plan. The LLM then uses this feedback to adjust its strategy, iteratively improving the schedule until it meets performance criteria.",[22,6208,6209],{},"This approach effectively treats the simulator as a tool for verification, allowing the LLM to leverage its reasoning capabilities for complex decision-making while offloading the heavy lifting of constraint validation to a reliable, deterministic system.",{"title":59,"searchDepth":60,"depth":60,"links":6211},[6212,6213],{"id":6174,"depth":60,"text":6175},{"id":6181,"depth":60,"text":6182},[65],{"content_references":6216,"triage":6223},[6217],{"type":6218,"title":6219,"author":6220,"url":6221,"context":6222},"paper","Sim2Schedule: A Simulator-Guided LLM Framework for Autonomous Open-Pit Mine Scheduling","Not specified","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.10286","reviewed",{"relevance":6143,"novelty":85,"quality":85,"actionability":86,"composite":6224,"reasoning":6225},4.15,"Category: AI & LLMs. The article presents a novel framework that integrates LLMs with domain-specific simulators for mine scheduling, addressing a specific pain point in the optimization of complex environments. It provides a detailed description of the iterative process, but lacks specific actionable steps for implementation.","\u002Fsummaries\u002Fd5c54c878ef99cc8-sim2schedule-simulator-guided-llm-framework-for-mi-summary","2026-06-10 12:57:08",{"title":6164,"description":59},{"loc":6226},"d5c54c878ef99cc8","arXiv cs.AI","summaries\u002Fd5c54c878ef99cc8-sim2schedule-simulator-guided-llm-framework-for-mi-summary",[102,101,104,103],"Sim2Schedule addresses the complexity of open-pit mine scheduling by combining LLM reasoning with domain-specific simulators to iteratively refine production plans.",[],"SHbvAdHQgzicIPZrrxTErWZcrjbybOu2rnkGQc94IlM",{"id":6238,"title":6239,"ai":6240,"body":6245,"categories":6296,"created_at":66,"date_modified":66,"description":59,"extension":67,"faq":66,"featured":68,"kicker_label":66,"meta":6297,"navigation":89,"path":6304,"published_at":6305,"question":66,"scraped_at":6305,"seo":6306,"sitemap":6307,"source_id":6308,"source_name":6231,"source_type":97,"source_url":6301,"stem":6309,"tags":6310,"thumbnail_url":66,"tldr":6311,"tweet":66,"unknown_tags":6312,"__hash__":6313},"summaries\u002Fsummaries\u002F05fa720414a31c67-specprefetch-optimizing-sparse-moe-inference-via-e-summary.md","SpecPrefetch: Optimizing Sparse MoE Inference via Expert Prefetching",{"provider":7,"model":8,"input_tokens":6241,"output_tokens":6242,"processing_time_ms":6243,"cost_usd":6244},4027,523,2930,0.00179125,{"type":14,"value":6246,"toc":6291},[6247,6251,6254,6258,6261,6264,6284,6288],[17,6248,6250],{"id":6249},"addressing-the-moe-memory-bottleneck","Addressing the MoE Memory Bottleneck",[22,6252,6253],{},"Sparse Mixture-of-Experts (MoE) models offer high parameter counts with efficient compute, but they suffer from significant latency issues during inference due to the overhead of loading experts from off-chip memory. Because only a subset of experts is active for any given token, the system must frequently fetch weights from VRAM or system memory, creating a communication bottleneck that limits throughput.",[17,6255,6257],{"id":6256},"the-specprefetch-mechanism","The SpecPrefetch Mechanism",[22,6259,6260],{},"SpecPrefetch introduces a parameter-efficient approach to mitigate this by predicting which experts will be required for upcoming tokens before they are explicitly requested by the router. Instead of relying on reactive loading, the system uses a lightweight predictive model to 'prefetch' expert weights into high-speed cache or local memory.",[22,6262,6263],{},"Key technical components include:",[39,6265,6266,6272,6278],{},[42,6267,6268,6271],{},[45,6269,6270],{},"Predictive Expert Selection:"," A small, auxiliary model that operates in parallel with the main router to estimate future expert activation patterns.",[42,6273,6274,6277],{},[45,6275,6276],{},"Parameter Efficiency:"," By utilizing a compact architecture for the prefetcher, the method avoids adding significant memory overhead, ensuring that the performance gains from reduced latency are not offset by the cost of the prefetching mechanism itself.",[42,6279,6280,6283],{},[45,6281,6282],{},"Latency Hiding:"," By overlapping the data transfer of expert weights with the computation of current tokens, SpecPrefetch effectively hides the memory access latency, allowing for smoother execution of large-scale MoE models on hardware with limited bandwidth.",[17,6285,6287],{"id":6286},"performance-impact","Performance Impact",[22,6289,6290],{},"This approach demonstrates that intelligent data movement is as critical as model architecture in scaling MoE performance. By reducing the idle time spent waiting for expert weights, SpecPrefetch allows for higher utilization of compute units, making it a viable strategy for deploying massive MoE models in production environments where inference speed is a primary constraint.",{"title":59,"searchDepth":60,"depth":60,"links":6292},[6293,6294,6295],{"id":6249,"depth":60,"text":6250},{"id":6256,"depth":60,"text":6257},{"id":6286,"depth":60,"text":6287},[65],{"content_references":6298,"triage":6302},[6299],{"type":6218,"title":6300,"url":6301,"context":6222},"SpecPrefetch: Parameter-Efficient Expert Prefetching for Sparse MoE Foundation Models","https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.24787",{"relevance":85,"novelty":85,"quality":85,"actionability":86,"composite":87,"reasoning":6303},"Category: AI & LLMs. The article discusses a specific optimization technique for Sparse Mixture-of-Experts models, addressing a key pain point of latency during inference, which is relevant for AI product builders. It presents a novel approach to prefetching expert weights, which could inspire actionable strategies for developers working on AI-powered products.","\u002Fsummaries\u002F05fa720414a31c67-specprefetch-optimizing-sparse-moe-inference-via-e-summary","2026-07-30 03:13:55",{"title":6239,"description":59},{"loc":6304},"05fa720414a31c67","summaries\u002F05fa720414a31c67-specprefetch-optimizing-sparse-moe-inference-via-e-summary",[102,104,101],"SpecPrefetch improves Sparse Mixture-of-Experts (MoE) inference latency by using a parameter-efficient mechanism to predict and pre-load required experts into memory, reducing communication bottlenecks.",[],"x1GZCpL_BfrulG-eKyz0J6g1y9luvTw6Lsq2xVp7uMY",{"id":6315,"title":6316,"ai":6317,"body":6322,"categories":6350,"created_at":66,"date_modified":66,"description":59,"extension":67,"faq":66,"featured":68,"kicker_label":66,"meta":6351,"navigation":89,"path":6360,"published_at":6361,"question":66,"scraped_at":6361,"seo":6362,"sitemap":6363,"source_id":6364,"source_name":6231,"source_type":97,"source_url":6357,"stem":6365,"tags":6366,"thumbnail_url":66,"tldr":6367,"tweet":66,"unknown_tags":6368,"__hash__":6369},"summaries\u002Fsummaries\u002F2ee3d57a9a4ce9cd-groclm-leveraging-llms-for-e-commerce-grocery-cate-summary.md","GrocLM: Leveraging LLMs for E-Commerce Grocery Categorization",{"provider":7,"model":8,"input_tokens":6318,"output_tokens":6319,"processing_time_ms":6320,"cost_usd":6321},3993,520,2859,0.00177825,{"type":14,"value":6323,"toc":6345},[6324,6328,6331,6335,6338,6342],[17,6325,6327],{"id":6326},"the-challenge-of-grocery-categorization","The Challenge of Grocery Categorization",[22,6329,6330],{},"Grocery e-commerce presents a unique classification challenge due to the massive scale of product catalogs, high frequency of new item additions, and the inherent ambiguity in product naming conventions. Traditional machine learning approaches often struggle with these high-cardinality datasets, requiring frequent retraining and manual feature engineering to maintain accuracy. GrocLM addresses this by utilizing the semantic reasoning capabilities of Large Language Models (LLMs) to map unstructured product descriptions to hierarchical grocery categories.",[17,6332,6334],{"id":6333},"the-groclm-approach","The GrocLM Approach",[22,6336,6337],{},"Instead of relying on rigid, keyword-based classification, GrocLM treats category recommendation as a generative task. By fine-tuning LLMs on domain-specific grocery data, the model learns to interpret the nuances of product titles, brand names, and attributes. This allows the system to handle 'long-tail' products—items that appear infrequently or have non-standard naming—more effectively than traditional supervised models. The model leverages the pre-trained knowledge of the LLM to understand semantic relationships between products, even when explicit category labels are missing or inconsistent in the source data.",[17,6339,6341],{"id":6340},"performance-and-practical-impact","Performance and Practical Impact",[22,6343,6344],{},"The research indicates that LLM-based categorization provides superior generalization compared to standard classification architectures. By moving from a fixed-label classification head to a generative approach, the system becomes more resilient to changes in the product catalog. This reduces the operational overhead of maintaining a taxonomy, as the model can infer categories for new products based on their semantic similarity to existing items. The result is a more robust, scalable pipeline for e-commerce platforms looking to automate product organization and improve search relevance for end-users.",{"title":59,"searchDepth":60,"depth":60,"links":6346},[6347,6348,6349],{"id":6326,"depth":60,"text":6327},{"id":6333,"depth":60,"text":6334},{"id":6340,"depth":60,"text":6341},[65],{"content_references":6352,"triage":6358},[6353],{"type":6354,"title":6355,"author":6356,"url":6357,"context":6222},"other","GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models","Unknown","https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.24764",{"relevance":6143,"novelty":85,"quality":85,"actionability":86,"composite":6224,"reasoning":6359},"Category: AI & LLMs. The article directly addresses the application of LLMs in solving a specific problem in e-commerce, which is highly relevant for product builders. It presents a novel approach to grocery categorization that outperforms traditional methods, providing insights into practical implementation. However, while it offers a solid framework, it lacks detailed step-by-step guidance for immediate application.","\u002Fsummaries\u002F2ee3d57a9a4ce9cd-groclm-leveraging-llms-for-e-commerce-grocery-cate-summary","2026-07-30 03:13:52",{"title":6316,"description":59},{"loc":6360},"2ee3d57a9a4ce9cd","summaries\u002F2ee3d57a9a4ce9cd-groclm-leveraging-llms-for-e-commerce-grocery-cate-summary",[102,104,101],"GrocLM demonstrates how Large Language Models can be fine-tuned to solve the complex, high-cardinality problem of grocery product categorization in e-commerce, outperforming traditional classification methods.",[],"mzs7KFC6gnWqsK9CwfioMgiyTZJrRocfOFZhZkd9Tbg"]