[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-rl-solves-sequential-coupon-optimization-summary":3,"summaries-facets-categories":80,"summary-related-rl-solves-sequential-coupon-optimization-summary":5654},{"id":4,"title":5,"ai":6,"body":13,"categories":58,"created_at":60,"date_modified":60,"description":52,"extension":61,"faq":60,"featured":62,"kicker_label":60,"meta":63,"navigation":64,"path":65,"published_at":66,"question":60,"scraped_at":60,"seo":67,"sitemap":68,"source_id":69,"source_name":70,"source_type":71,"source_url":72,"stem":73,"tags":74,"thumbnail_url":60,"tldr":77,"tweet":60,"unknown_tags":78,"__hash__":79},"summaries\u002Fsummaries\u002Frl-solves-sequential-coupon-optimization-summary.md","RL Solves Sequential Coupon Optimization",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","x-ai\u002Fgrok-4.1-fast",3621,1225,15712,0.0008663,{"type":14,"value":15,"toc":51},"minimark",[16,21,25,28,32,35,38,42,45],[17,18,20],"h2",{"id":19},"coupon-decisions-demand-sequential-optimization","Coupon Decisions Demand Sequential Optimization",[22,23,24],"p",{},"E-commerce faces precise trade-offs: send coupons too weakly and lose sales; too strongly and erode margins. Timing matters—today's coupon shapes tomorrow's price sensitivity and buy-without-promo behavior. Short-term conversion focus trains customers to wait; long-term value focus misses immediate revenue. Add budget limits and fatigue, and it's a dynamic problem for each user.",[22,26,27],{},"This isn't static prediction (e.g., will they buy?). It's sequential: actions today alter future states like expectations and willingness to pay full price.",[17,29,31],{"id":30},"reinforcement-learning-fits-naturally","Reinforcement Learning Fits Naturally",[22,33,34],{},"RL models these as Markov decision processes: states (user history, behavior), actions (send coupon? strength?), rewards (blended conversion + margin + lifetime value). Unlike supervised ML, RL learns policies optimizing long-term cumulative rewards over episodes of user interactions.",[22,36,37],{},"Batch deep RL handles real data without full simulation, learning from historical logs.",[17,39,41],{"id":40},"evidence-from-production-scale-experiments","Evidence from Production-Scale Experiments",[22,43,44],{},"A Marketing Science paper showed batch deep RL outperforming baselines in large field experiments for dynamic coupon targeting. NeurIPS BCORLE paper extends this (details cut off in source). These confirm RL lifts outcomes where rules or simple ML fail due to sequential dynamics.",[22,46,47],{},[48,49,50],"em",{},"Note: Article introduces a quadratic-critic RL framework but provided excerpt ends abruptly after research refs—core method details unavailable.",{"title":52,"searchDepth":53,"depth":53,"links":54},"",2,[55,56,57],{"id":19,"depth":53,"text":20},{"id":30,"depth":53,"text":31},{"id":40,"depth":53,"text":41},[59],"Data Science & Visualization",null,"md",false,{},true,"\u002Fsummaries\u002Frl-solves-sequential-coupon-optimization-summary","2026-04-08 21:21:17",{"title":5,"description":52},{"loc":65},"e664545efdc9b9f0","Level Up Coding","article","https:\u002F\u002Funknown","summaries\u002Frl-solves-sequential-coupon-optimization-summary",[75,76],"machine-learning","reinforcement-learning","Treat coupon decisions (when, to whom, strength) as sequential problems with reinforcement learning to balance conversion, margins, budgets, and customer fatigue—backed by field experiments.",[76],"CEMrQdL7nyjA4QtgrQGK8JCcGy-5yP_2aGW8d1oDK28",[81,84,87,90,93,96,98,100,103,105,107,109,111,114,116,118,120,122,125,127,129,131,133,135,137,139,141,143,145,147,149,151,153,155,157,159,162,164,166,168,170,172,174,176,178,180,182,184,187,189,191,193,195,197,199,201,203,205,207,209,211,213,215,218,220,222,224,226,228,230,232,234,236,238,240,242,245,247,249,251,253,255,257,259,261,263,265,267,269,271,273,275,277,279,281,283,285,287,289,291,293,295,297,299,301,304,306,308,310,312,314,316,318,320,322,325,327,329,331,333,335,337,339,341,343,345,347,350,352,354,356,358,360,362,364,367,369,371,373,375,377,379,381,383,385,387,389,391,393,395,397,399,401,403,405,407,409,411,413,416,418,420,423,425,427,429,431,433,435,437,439,441,443,445,447,449,452,454,456,458,460,462,464,466,468,471,473,475,477,479,481,483,485,487,489,491,493,495,497,499,501,503,505,507,509,511,513,515,517,519,521,523,525,527,529,531,533,535,537,539,541,543,545,547,549,551,553,555,557,559,561,563,565,567,569,571,573,575,577,579,581,583,585,587,589,591,593,595,597,599,601,603,605,607,609,611,613,615,617,619,621,623,625,627,629,631,633,635,637,639,641,643,645,647,649,651,653,655,657,659,661,663,665,667,669,671,673,675,677,679,681,683,685,687,689,691,693,695,697,699,701,703,705,707,710,712,714,716,719,721,723,725,727,729,731,733,735,737,740,742,744,746,748,750,752,754,756,758,760,762,764,766,768,770,772,774,776,778,780,782,784,786,788,790,792,794,796,798,800,802,804,806,808,810,812,814,816,818,820,822,824,826,828,830,832,834,836,838,840,842,844,846,848,850,852,854,856,858,860,862,864,866,868,870,872,874,876,878,880,882,884,886,888,890,892,894,896,898,900,902,904,906,908,910,912,914,916,918,920,922,924,926,928,930,932,934,936,938,940,942,944,946,948,950,952,954,956,958,960,962,964,966,968,970,972,974,976,978,980,982,984,986,989,991,993,995,997,999,1001,1003,1005,1007,1009,1011,1013,1015,1017,1019,1021,1023,1025,1027,1029,1031,1033,1035,1037,1039,1041,1043,1045,1047,1049,1051,1053,1055,1057,1059,1061,1063,1065,1067,1069,1071,1073,1075,1077,1079,1081,1083,1085,1087,1089,1091,1093,1095,1097,1099,1101,1103,1105,1107,1109,1111,1113,1115,1117,1119,1121,1123,1125,1127,1129,1131,1133,1135,1137,1139,1141,1143,1146,1148,1150,1152,1154,1156,1158,1160,1162,1164,1166,1168,1170,1172,1174,1176,1178,1180,1182,1184,1186,1188,1190,1192,1194,1196,1198,1200,1202,1204,1206,1208,1210,1212,1214,1216,1218,1220,1222,1224,1226,1228,1230,1232,1234,1236,1238,1240,1242,1244,1246,1248,1250,1252,1254,1256,1259,1261,1263,1265,1267,1269,1271,1273,1275,1277,1279,1281,1283,1285,1287,1289,1291,1293,1295,1297,1299,1301,1303,1305,1307,1309,1311,1313,1315,1317,1319,1321,1323,1325,1327,1329,1331,1333,1335,1337,1339,1341,1343,1345,1347,1349,1351,1353,1355,1357,1359,1361,1363,1365,1367,1369,1371,1373,1375,1377,1379,1381,1384,1386,1388,1390,1392,1394,1396,1398,1400,1402,1404,1406,1408,1410,1412,1414,1416,1418,1420,1422,1424,1426,1428,1430,1432,1435,1437,1439,1441,1443,1445,1447,1449,1451,1453,1455,1457,1459,1461,1463,1465,1467,1469,1471,1473,1475,1477,1479,1481,1483,1485,1487,1489,1491,1493,1495,1497,1499,1501,1503,1505,1507,1509,1511,1513,1515,1517,1519,1521,1523,1525,1527,1529,1531,1533,1535,1537,1539,1541,1543,1545,1547,1549,1551,1553,1555,1557,1559,1561,1563,1565,1567,1569,1571,1573,1575,1577,1579,1581,1583,1585,1587,1589,1591,1593,1595,1597,1599,1601,1603,1605,1607,1609,1611,1613,1615,1617,1619,1621,1623,1625,1627,1629,1631,1633,1635,1637,1639,1641,1643,1645,1647,1649,1651,1653,1655,1657,1659,1661,1663,1665,1667,1669,1671,1673,1675,1677,1679,1681,1683,1685,1687,1689,1691,1693,1695,1697,1699,1701,1703,1705,1707,1709,1711,1713,1715,1717,1719,1721,1723,1725,1727,1729,1731,1733,1735,1737,1739,1741,1743,1745,1747,1749,1751,1753,1755,1757,1759,1761,1763,1765,1767,1769,1771,1773,1775,1777,1779,1782,1784,1786,1788,1790,1792,1794,1796,1798,1800,1802,1804,1806,1808,1810,1812,1814,1816,1818,1820,1822,1824,1826,1828,1830,1832,1834,1836,1838,1840,1842,1844,1846,1848,1850,1852,1854,1857,1859,1861,1863,1865,1867,1869,1871,1873,1875,1877,1879,1881,1883,1885,1887,1889,1891,1893,1895,1897,1899,1901,1903,1905,1907,1909,1911,1913,1915,1917,1919,1921,1923,1925,1927,1929,1931,1933,1935,1937,1939,1941,1943,1945,1947,1949,1951,1953,1956,1958,1960,1962,1964,1966,1968,1970,1972,1974,1976,1978,1980,1982,1984,1986,1988,1990,1993,1995,1997,1999,2001,2003,2005,2007,2009,2011,2013,2015,2017,2019,2021,2023,2025,2027,2029,2031,2033,2035,2037,2039,2041,2043,2045,2047,2049,2051,2053,2055,2057,2059,2061,2063,2065,2067,2069,2071,2073,2075,2077,2079,2081,2083,2085,2087,2089,2091,2093,2095,2097,2099,2101,2103,2105,2107,2109,2111,2113,2115,2117,2119,2121,2123,2125,2127,2129,2131,2133,2135,2137,2139,2141,2143,2145,2147,2149,2151,2153,2155,2157,2159,2161,2163,2165,2167,2169,2171,2173,2175,2177,2179,2181,2183,2185,2187,2189,2191,2193,2195,2197,2199,2201,2203,2205,2207,2209,2211,2213,2215,2217,2219,2221,2223,2225,2227,2229,2231,2233,2235,2237,2239,2241,2243,2245,2247,2249,2251,2253,2255,2257,2259,2261,2263,2265,2267,2269,2271,2273,2275,2277,2279,2281,2283,2285,2287,2289,2291,2293,2295,2297,2299,2301,2303,2305,2307,2309,2311,2313,2315,2317,2319,2321,2323,2325,2327,2329,2331,2333,2335,2337,2339,2341,2343,2345,2347,2349,2351,2353,2355,2357,2359,2361,2363,2365,2367,2369,2371,2373,2375,2377,2379,2381,2383,2385,2387,2389,2391,2393,2395,2397,2399,2401,2403,2405,2407,2409,2411,2413,2415,2417,2419,2421,2423,2425,2427,2429,2431,2433,2435,2437,2439,2441,2443,2445,2447,2449,2451,2453,2455,2457,2459,2461,2463,2465,2467,2469,2471,2473,2475,2477,2479,2481,2483,2485,2487,2489,2491,2493,2495,2497,2499,2501,2503,2505,2507,2509,2511,2514,2516,2518,2520,2522,2524,2526,2528,2530,2532,2534,2536,2538,2540,2542,2544,2546,2548,2550,2552,2554,2556,2558,2560,2562,2564,2566,2568,2570,2572,2574,2576,2578,2580,2582,2584,2586,2588,2590,2592,2594,2596,2598,2600,2602,2604,2606,2608,2611,2613,2615,2617,2619,2621,2623,2625,2627,2629,2631,2633,2635,2637,2639,2641,2643,2645,2647,2649,2651,2653,2655,2657,2659,2661,2663,2665,2667,2669,2671,2673,2675,2677,2679,2681,2683,2685,2687,2689,2691,2693,2695,2697,2699,2701,2703,2705,2707,2709,2711,2713,2715,2717,2719,2721,2723,2725,2727,2729,2731,2733,2735,2737,2739,2741,2743,2745,2747,2749,2751,2753,2755,2757,2759,2761,2763,2765,2767,2769,2771,2773,2775,2777,2779,2781,2783,2785,2787,2789,2791,2793,2795,2797,2799,2801,2803,2805,2807,2809,2811,2813,2815,2817,2819,2821,2823,2825,2827,2829,2831,2833,2835,2837,2839,2841,2843,2845,2847,2849,2851,2853,2855,2857,2859,2861,2863,2865,2867,2869,2871,2873,2875,2877,2879,2881,2883,2885,2887,2889,2891,2893,2895,2897,2899,2901,2903,2905,2907,2909,2911,2913,2915,2917,2919,2921,2923,2925,2927,2929,2931,2933,2935,2937,2939,2941,2943,2945,2947,2949,2951,2953,2955,2957,2959,2961,2963,2965,2967,2969,2971,2973,2975,2977,2979,2981,2983,2985,2987,2989,2991,2993,2995,2997,2999,3001,3003,3005,3007,3009,3011,3013,3015,3017,3019,3021,3023,3025,3027,3029,3031,3033,3035,3037,3039,3041,3043,3045,3047,3049,3051,3053,3055,3057,3059,3061,3063,3065,3067,3069,3071,3073,3075,3077,3079,3081,3083,3085,3087,3089,3091,3093,3095,3097,3099,3101,3103,3105,3107,3109,3111,3113,3115,3117,3119,3121,3123,3125,3127,3129,3131,3133,3135,3137,3139,3141,3143,3145,3147,3149,3151,3153,3155,3157,3159,3161,3163,3165,3167,3169,3171,3173,3175,3177,3179,3181,3183,3185,3187,3189,3191,3193,3195,3197,3199,3201,3203,3205,3207,3209,3211,3213,3215,3217,3219,3221,3223,3225,3227,3229,3231,3233,3235,3237,3239,3241,3243,3245,3247,3249,3251,3253,3255,3257,3259,3261,3263,3265,3267,3269,3271,3273,3275,3277,3279,3281,3283,3285,3287,3289,3291,3293,3295,3297,3299,3301,3303,3305,3307,3309,3311,3313,3315,3317,3319,3321,3323,3325,3327,3329,3331,3333,3335,3337,3339,3341,3343,3345,3347,3349,3351,3353,3355,3357,3359,3361,3363,3365,3367,3369,3371,3373,3375,3377,3379,3381,3383,3385,3387,3389,3391,3393,3395,3397,3399,3401,3403,3405,3407,3409,3411,3413,3415,3417,3419,3421,3423,3425,3427,3429,3431,3433,3435,3437,3439,3441,3443,3445,3447,3449,3451,3453,3455,3457,3459,3461,3463,3465,3467,3469,3471,3473,3475,3477,3479,3481,3483,3485,3487,3489,3491,3493,3495,3497,3499,3501,3503,3505,3507,3509,3511,3513,3515,3517,3519,3521,3523,3525,3527,3529,3531,3533,3535,3537,3539,3541,3543,3545,3547,3549,3551,3553,3555,3557,3559,3561,3563,3565,3567,3569,3571,3573,3575,3577,3579,3581,3583,3585,3587,3589,3591,3593,3595,3597,3599,3601,3603,3605,3607,3609,3611,3613,3615,3617,3619,3621,3623,3625,3627,3629,3631,3633,3635,3637,3639,3641,3644,3646,3648,3650,3652,3654,3656,3658,3660,3662,3664,3666,3668,3670,3672,3674,3676,3678,3680,3682,3684,3686,3688,3690,3692,3694,3696,3698,3700,3702,3704,3706,3708,3710,3712,3714,3716,3718,3720,3722,3724,3726,3728,3730,3732,3734,3736,3738,3740,3742,3744,3746,3748,3750,3752,3754,3756,3758,3760,3762,3764,3766,3768,3770,3772,3774,3776,3778,3780,3782,3784,3786,3788,3790,3792,3794,3796,3798,3800,3802,3804,3806,3808,3810,3812,3814,3816,3818,3820,3822,3824,3826,3828,3830,3832,3834,3836,3838,3840,3842,3844,3846,3848,3850,3852,3854,3856,3858,3860,3862,3864,3866,3868,3870,3872,3874,3876,3878,3880,3882,3884,3886,3888,3890,3892,3894,3896,3898,3900,3902,3904,3906,3908,3910,3912,3914,3916,3918,3920,3922,3924,3926,3928,3930,3932,3934,3936,3938,3940,3942,3944,3946,3948,3950,3952,3954,3956,3958,3960,3962,3964,3966,3968,3970,3972,3974,3976,3978,3980,3982,3984,3986,3988,3990,3992,3994,3996,3998,4000,4002,4004,4006,4008,4010,4012,4014,4016,4018,4020,4022,4024,4026,4028,4030,4032,4034,4036,4038,4040,4042,4044,4046,4048,4050,4052,4054,4056,4058,4060,4062,4064,4066,4068,4070,4072,4074,4076,4078,4080,4082,4084,4086,4088,4090,4092,4094,4096,4098,4100,4102,4104,4106,4108,4110,4112,4114,4116,4118,4120,4122,4124,4126,4128,4130,4132,4134,4136,4138,4140,4142,4144,4146,4148,4150,4152,4154,4156,4158,4160,4162,4164,4166,4168,4170,4172,4174,4176,4178,4180,4182,4184,4186,4188,4190,4192,4194,4196,4198,4200,4202,4204,4206,4208,4210,4212,4214,4216,4218,4220,4222,4224,4226,4228,4230,4232,4234,4236,4238,4240,4242,4244,4246,4248,4250,4252,4254,4256,4258,4260,4262,4264,4266,4268,4270,4272,4274,4276,4278,4280,4282,4284,4286,4288,4290,4292,4294,4296,4298,4300,4302,4304,4306,4308,4310,4312,4314,4316,4318,4320,4322,4324,4326,4328,4330,4332,4334,4336,4338,4341,4343,4345,4347,4349,4351,4353,4355,4357,4359,4361,4363,4365,4367,4369,4371,4373,4375,4377,4379,4381,4383,4385,4387,4389,4391,4393,4395,4397,4399,4401,4403,4405,4407,4409,4411,4413,4415,4417,4419,4421,4423,4425,4427,4429,4431,4433,4435,4437,4439,4441,4443,4445,4447,4449,4451,4453,4455,4457,4459,4461,4463,4465,4467,4469,4471,4473,4475,4477,4479,4481,4483,4485,4487,4489,4491,4493,4495,4497,4499,4501,4504,4506,4508,4510,4512,4514,4516,4518,4520,4522,4524,4526,4528,4530,4532,4534,4536,4538,4540,4542,4544,4546,4548,4550,4552,4554,4556,4558,4560,4562,4564,4566,4568,4570,4572,4574,4576,4578,4580,4582,4584,4586,4588,4590,4592,4594,4596,4598,4600,4602,4604,4606,4608,4610,4612,4614,4616,4618,4620,4622,4624,4626,4628,4630,4632,4634,4636,4638,4640,4642,4644,4646,4648,4650,4652,4654,4656,4658,4660,4662,4664,4666,4668,4670,4672,4674,4676,4678,4680,4682,4684,4686,4688,4690,4692,4694,4696,4698,4700,4702,4704,4706,4708,4710,4712,4714,4716,4718,4720,4722,4724,4726,4728,4730,4732,4734,4736,4738,4740,4742,4744,4746,4748,4750,4752,4754,4756,4758,4760,4762,4764,4766,4768,4770,4772,4774,4776,4778,4780,4782,4784,4786,4788,4790,4792,4794,4796,4798,4800,4802,4804,4806,4808,4810,4812,4814,4816,4818,4820,4822,4824,4826,4828,4830,4832,4834,4836,4838,4840,4842,4844,4846,4848,4850,4852,4854,4856,4858,4860,4862,4864,4866,4868,4870,4872,4874,4876,4878,4880,4882,4884,4886,4888,4890,4892,4894,4896,4898,4900,4902,4904,4906,4908,4910,4912,4914,4916,4918,4920,4922,4924,4926,4928,4930,4932,4934,4936,4938,4940,4942,4944,4946,4948,4950,4952,4954,4956,4958,4960,4962,4964,4966,4968,4970,4972,4974,4976,4978,4980,4982,4984,4986,4988,4990,4992,4994,4996,4998,5000,5002,5004,5006,5008,5010,5012,5014,5016,5018,5020,5022,5024,5026,5028,5030,5032,5034,5036,5038,5040,5042,5044,5046,5048,5050,5052,5054,5056,5058,5060,5062,5064,5066,5068,5070,5072,5074,5076,5078,5080,5082,5084,5086,5088,5090,5092,5094,5096,5098,5100,5102,5104,5106,5108,5110,5112,5114,5116,5118,5120,5122,5124,5126,5128,5130,5132,5134,5136,5138,5140,5142,5144,5146,5148,5150,5152,5154,5156,5158,5160,5162,5164,5166,5168,5170,5172,5174,5176,5178,5180,5182,5184,5186,5188,5190,5192,5194,5196,5198,5200,5202,5204,5206,5208,5210,5212,5214,5216,5218,5220,5222,5224,5226,5228,5230,5232,5234,5236,5238,5240,5242,5244,5246,5248,5250,5252,5254,5256,5258,5260,5262,5264,5266,5268,5270,5272,5274,5276,5278,5280,5282,5284,5286,5288,5290,5292,5294,5296,5298,5300,5302,5304,5306,5308,5310,5312,5314,5316,5318,5320,5322,5324,5326,5328,5330,5332,5334,5336,5338,5340,5342,5344,5346,5348,5350,5352,5354,5356,5358,5360,5362,5364,5366,5368,5370,5372,5374,5376,5378,5380,5382,5384,5386,5388,5390,5392,5394,5396,5398,5400,5402,5404,5406,5408,5410,5412,5414,5416,5418,5420,5422,5424,5426,5428,5430,5432,5434,5436,5438,5440,5442,5444,5446,5448,5450,5452,5454,5456,5458,5460,5462,5464,5466,5468,5470,5472,5474,5476,5478,5480,5482,5484,5486,5488,5490,5492,5494,5496,5498,5500,5502,5504,5506,5508,5510,5512,5514,5516,5518,5520,5522,5524,5526,5528,5530,5532,5534,5536,5538,5540,5542,5544,5546,5548,5550,5552,5554,5556,5558,5560,5562,5564,5566,5568,5570,5572,5574,5576,5578,5580,5582,5584,5586,5588,5590,5592,5594,5596,5598,5600,5602,5604,5606,5608,5610,5612,5614,5616,5618,5620,5622,5624,5626,5628,5630,5632,5634,5636,5638,5640,5642,5644,5646,5648,5650,5652],{"categories":82},[83],"Developer Productivity",{"categories":85},[86],"Business & SaaS",{"categories":88},[89],"AI & LLMs",{"categories":91},[92],"AI Automation",{"categories":94},[95],"Product Strategy",{"categories":97},[89],{"categories":99},[83],{"categories":101},[102],"Software Engineering",{"categories":104},[89],{"categories":106},[86],{"categories":108},[],{"categories":110},[89],{"categories":112},[113],"Inference & Serving",{"categories":115},[89],{"categories":117},[89],{"categories":119},[92],{"categories":121},[],{"categories":123},[124],"AI News & Trends",{"categories":126},[92],{"categories":128},[89],{"categories":130},[86],{"categories":132},[89],{"categories":134},[92],{"categories":136},[124],{"categories":138},[92],{"categories":140},[92],{"categories":142},[89],{"categories":144},[92],{"categories":146},[89],{"categories":148},[89],{"categories":150},[89],{"categories":152},[124],{"categories":154},[89],{"categories":156},[89],{"categories":158},[],{"categories":160},[161],"Design & Frontend",{"categories":163},[59],{"categories":165},[124],{"categories":167},[89],{"categories":169},[89],{"categories":171},[],{"categories":173},[89],{"categories":175},[92],{"categories":177},[102],{"categories":179},[89],{"categories":181},[92],{"categories":183},[89],{"categories":185},[186],"Marketing & Growth",{"categories":188},[161],{"categories":190},[89],{"categories":192},[92],{"categories":194},[89],{"categories":196},[],{"categories":198},[],{"categories":200},[161],{"categories":202},[89],{"categories":204},[92],{"categories":206},[83],{"categories":208},[102],{"categories":210},[161],{"categories":212},[89],{"categories":214},[102],{"categories":216},[217],"DevOps & Cloud",{"categories":219},[92],{"categories":221},[95],{"categories":223},[124],{"categories":225},[89],{"categories":227},[],{"categories":229},[89],{"categories":231},[],{"categories":233},[92],{"categories":235},[102],{"categories":237},[],{"categories":239},[102],{"categories":241},[89],{"categories":243},[244],"Governance & Standards",{"categories":246},[86],{"categories":248},[],{"categories":250},[],{"categories":252},[89],{"categories":254},[89],{"categories":256},[92],{"categories":258},[89],{"categories":260},[89],{"categories":262},[92],{"categories":264},[89],{"categories":266},[89],{"categories":268},[89],{"categories":270},[],{"categories":272},[102],{"categories":274},[],{"categories":276},[],{"categories":278},[102],{"categories":280},[],{"categories":282},[102],{"categories":284},[89],{"categories":286},[89],{"categories":288},[186],{"categories":290},[89],{"categories":292},[161],{"categories":294},[161],{"categories":296},[89],{"categories":298},[102],{"categories":300},[92],{"categories":302},[303],"GovTech & Public-Sector Adoption",{"categories":305},[102],{"categories":307},[89],{"categories":309},[89],{"categories":311},[92],{"categories":313},[92],{"categories":315},[59],{"categories":317},[89],{"categories":319},[124],{"categories":321},[92],{"categories":323},[324],"Legal AI Tools",{"categories":326},[92],{"categories":328},[186],{"categories":330},[92],{"categories":332},[95],{"categories":334},[102],{"categories":336},[303],{"categories":338},[],{"categories":340},[92],{"categories":342},[],{"categories":344},[92],{"categories":346},[92],{"categories":348},[349],"RAG & Retrieval",{"categories":351},[86],{"categories":353},[89],{"categories":355},[102],{"categories":357},[217],{"categories":359},[161],{"categories":361},[89],{"categories":363},[],{"categories":365},[366],"Agents & Orchestration",{"categories":368},[102],{"categories":370},[89],{"categories":372},[],{"categories":374},[92],{"categories":376},[86],{"categories":378},[],{"categories":380},[89],{"categories":382},[],{"categories":384},[83],{"categories":386},[102],{"categories":388},[86],{"categories":390},[89],{"categories":392},[89],{"categories":394},[124],{"categories":396},[89],{"categories":398},[],{"categories":400},[89],{"categories":402},[],{"categories":404},[102],{"categories":406},[59],{"categories":408},[],{"categories":410},[89],{"categories":412},[161],{"categories":414},[415],"Models & Frontier Labs",{"categories":417},[],{"categories":419},[161],{"categories":421},[422],"Regulation & Governance of AI",{"categories":424},[92],{"categories":426},[],{"categories":428},[89],{"categories":430},[89],{"categories":432},[92],{"categories":434},[124],{"categories":436},[86],{"categories":438},[89],{"categories":440},[],{"categories":442},[102],{"categories":444},[92],{"categories":446},[89],{"categories":448},[95],{"categories":450},[451],"AI Policy & Regulation",{"categories":453},[],{"categories":455},[89],{"categories":457},[95],{"categories":459},[92],{"categories":461},[89],{"categories":463},[92],{"categories":465},[],{"categories":467},[59],{"categories":469},[470],"Evals & Reliability",{"categories":472},[89],{"categories":474},[],{"categories":476},[83],{"categories":478},[303],{"categories":480},[451],{"categories":482},[89],{"categories":484},[86],{"categories":486},[89],{"categories":488},[92],{"categories":490},[89],{"categories":492},[92],{"categories":494},[366],{"categories":496},[89],{"categories":498},[102],{"categories":500},[89],{"categories":502},[],{"categories":504},[],{"categories":506},[89],{"categories":508},[303],{"categories":510},[89],{"categories":512},[89],{"categories":514},[],{"categories":516},[161],{"categories":518},[],{"categories":520},[89],{"categories":522},[],{"categories":524},[92],{"categories":526},[89],{"categories":528},[161],{"categories":530},[],{"categories":532},[89],{"categories":534},[92],{"categories":536},[89],{"categories":538},[86],{"categories":540},[92],{"categories":542},[89],{"categories":544},[89],{"categories":546},[102],{"categories":548},[161],{"categories":550},[92],{"categories":552},[],{"categories":554},[102],{"categories":556},[92],{"categories":558},[],{"categories":560},[124],{"categories":562},[],{"categories":564},[89],{"categories":566},[89],{"categories":568},[86,186],{"categories":570},[],{"categories":572},[89],{"categories":574},[89],{"categories":576},[92],{"categories":578},[],{"categories":580},[],{"categories":582},[89],{"categories":584},[161],{"categories":586},[89],{"categories":588},[],{"categories":590},[89],{"categories":592},[217],{"categories":594},[],{"categories":596},[92],{"categories":598},[124],{"categories":600},[89],{"categories":602},[161],{"categories":604},[],{"categories":606},[124],{"categories":608},[89],{"categories":610},[113],{"categories":612},[89],{"categories":614},[92],{"categories":616},[124],{"categories":618},[415],{"categories":620},[89],{"categories":622},[186],{"categories":624},[],{"categories":626},[92],{"categories":628},[86],{"categories":630},[102],{"categories":632},[89],{"categories":634},[92],{"categories":636},[],{"categories":638},[89,217],{"categories":640},[89],{"categories":642},[89],{"categories":644},[89],{"categories":646},[92],{"categories":648},[89,102],{"categories":650},[59],{"categories":652},[89],{"categories":654},[89],{"categories":656},[102],{"categories":658},[92],{"categories":660},[451],{"categories":662},[186],{"categories":664},[89],{"categories":666},[92],{"categories":668},[89],{"categories":670},[89],{"categories":672},[92],{"categories":674},[],{"categories":676},[89],{"categories":678},[92],{"categories":680},[89],{"categories":682},[89,86],{"categories":684},[86],{"categories":686},[],{"categories":688},[161],{"categories":690},[161],{"categories":692},[89],{"categories":694},[],{"categories":696},[],{"categories":698},[124],{"categories":700},[],{"categories":702},[83],{"categories":704},[89],{"categories":706},[102],{"categories":708},[709],"Generative UI & Design-to-Code",{"categories":711},[89],{"categories":713},[161],{"categories":715},[89],{"categories":717},[718],"Algorithmic Accountability",{"categories":720},[92],{"categories":722},[102],{"categories":724},[124],{"categories":726},[161],{"categories":728},[],{"categories":730},[89],{"categories":732},[89],{"categories":734},[89],{"categories":736},[92],{"categories":738},[739],"MLOps & Infrastructure",{"categories":741},[89],{"categories":743},[89],{"categories":745},[89],{"categories":747},[89],{"categories":749},[124],{"categories":751},[83],{"categories":753},[89],{"categories":755},[92],{"categories":757},[217],{"categories":759},[89],{"categories":761},[161],{"categories":763},[89],{"categories":765},[92],{"categories":767},[],{"categories":769},[],{"categories":771},[113],{"categories":773},[161],{"categories":775},[124],{"categories":777},[59],{"categories":779},[],{"categories":781},[89],{"categories":783},[89],{"categories":785},[86],{"categories":787},[89],{"categories":789},[89],{"categories":791},[89],{"categories":793},[124],{"categories":795},[113],{"categories":797},[89],{"categories":799},[161],{"categories":801},[],{"categories":803},[92],{"categories":805},[102],{"categories":807},[],{"categories":809},[89],{"categories":811},[89],{"categories":813},[92],{"categories":815},[102],{"categories":817},[89],{"categories":819},[59],{"categories":821},[],{"categories":823},[89],{"categories":825},[],{"categories":827},[89],{"categories":829},[],{"categories":831},[95],{"categories":833},[86],{"categories":835},[92],{"categories":837},[92],{"categories":839},[],{"categories":841},[83],{"categories":843},[89],{"categories":845},[86],{"categories":847},[124],{"categories":849},[83],{"categories":851},[],{"categories":853},[89],{"categories":855},[],{"categories":857},[],{"categories":859},[124],{"categories":861},[124],{"categories":863},[],{"categories":865},[366],{"categories":867},[89],{"categories":869},[161],{"categories":871},[102],{"categories":873},[],{"categories":875},[324],{"categories":877},[86],{"categories":879},[],{"categories":881},[],{"categories":883},[83],{"categories":885},[59],{"categories":887},[],{"categories":889},[186],{"categories":891},[92],{"categories":893},[86],{"categories":895},[92],{"categories":897},[86],{"categories":899},[102],{"categories":901},[],{"categories":903},[113],{"categories":905},[95],{"categories":907},[89],{"categories":909},[161],{"categories":911},[102],{"categories":913},[86],{"categories":915},[89],{"categories":917},[92],{"categories":919},[86],{"categories":921},[89],{"categories":923},[89],{"categories":925},[],{"categories":927},[],{"categories":929},[102],{"categories":931},[59],{"categories":933},[95],{"categories":935},[89],{"categories":937},[92],{"categories":939},[89],{"categories":941},[],{"categories":943},[124],{"categories":945},[95],{"categories":947},[89],{"categories":949},[470],{"categories":951},[217],{"categories":953},[],{"categories":955},[92],{"categories":957},[],{"categories":959},[83],{"categories":961},[],{"categories":963},[89],{"categories":965},[89],{"categories":967},[161],{"categories":969},[186],{"categories":971},[102],{"categories":973},[92],{"categories":975},[],{"categories":977},[102],{"categories":979},[83],{"categories":981},[],{"categories":983},[124],{"categories":985},[89,217],{"categories":987},[988],"Design Systems for AI",{"categories":990},[89],{"categories":992},[124],{"categories":994},[89],{"categories":996},[89],{"categories":998},[86],{"categories":1000},[89],{"categories":1002},[],{"categories":1004},[89],{"categories":1006},[89],{"categories":1008},[86],{"categories":1010},[89],{"categories":1012},[],{"categories":1014},[92],{"categories":1016},[102],{"categories":1018},[102],{"categories":1020},[161],{"categories":1022},[124],{"categories":1024},[59],{"categories":1026},[89],{"categories":1028},[83],{"categories":1030},[451],{"categories":1032},[89],{"categories":1034},[92],{"categories":1036},[89],{"categories":1038},[102],{"categories":1040},[102],{"categories":1042},[],{"categories":1044},[],{"categories":1046},[92],{"categories":1048},[95],{"categories":1050},[],{"categories":1052},[89],{"categories":1054},[],{"categories":1056},[161],{"categories":1058},[92],{"categories":1060},[102],{"categories":1062},[161],{"categories":1064},[89],{"categories":1066},[161],{"categories":1068},[],{"categories":1070},[],{"categories":1072},[124],{"categories":1074},[92],{"categories":1076},[92],{"categories":1078},[89],{"categories":1080},[89],{"categories":1082},[89],{"categories":1084},[86],{"categories":1086},[89],{"categories":1088},[89],{"categories":1090},[],{"categories":1092},[102],{"categories":1094},[102],{"categories":1096},[89],{"categories":1098},[102],{"categories":1100},[86],{"categories":1102},[],{"categories":1104},[89],{"categories":1106},[89],{"categories":1108},[89],{"categories":1110},[92],{"categories":1112},[83],{"categories":1114},[86],{"categories":1116},[124],{"categories":1118},[92],{"categories":1120},[113],{"categories":1122},[186],{"categories":1124},[89],{"categories":1126},[92],{"categories":1128},[],{"categories":1130},[161],{"categories":1132},[],{"categories":1134},[89],{"categories":1136},[89],{"categories":1138},[],{"categories":1140},[102],{"categories":1142},[86],{"categories":1144},[1145],"Visual & Generative Media",{"categories":1147},[92],{"categories":1149},[],{"categories":1151},[89],{"categories":1153},[89],{"categories":1155},[217],{"categories":1157},[59],{"categories":1159},[451],{"categories":1161},[102],{"categories":1163},[186],{"categories":1165},[89],{"categories":1167},[161],{"categories":1169},[89],{"categories":1171},[102],{"categories":1173},[92],{"categories":1175},[],{"categories":1177},[],{"categories":1179},[92],{"categories":1181},[83],{"categories":1183},[92],{"categories":1185},[415],{"categories":1187},[89],{"categories":1189},[95],{"categories":1191},[86],{"categories":1193},[],{"categories":1195},[89],{"categories":1197},[95],{"categories":1199},[89],{"categories":1201},[89],{"categories":1203},[89],{"categories":1205},[89],{"categories":1207},[89],{"categories":1209},[186],{"categories":1211},[89],{"categories":1213},[366],{"categories":1215},[89],{"categories":1217},[89],{"categories":1219},[89],{"categories":1221},[89],{"categories":1223},[89],{"categories":1225},[161],{"categories":1227},[92],{"categories":1229},[],{"categories":1231},[92],{"categories":1233},[],{"categories":1235},[217],{"categories":1237},[102],{"categories":1239},[],{"categories":1241},[415],{"categories":1243},[92],{"categories":1245},[89],{"categories":1247},[161,89],{"categories":1249},[83],{"categories":1251},[],{"categories":1253},[89],{"categories":1255},[83],{"categories":1257},[1258],"Medical Imaging & Radiology",{"categories":1260},[161],{"categories":1262},[92],{"categories":1264},[102],{"categories":1266},[],{"categories":1268},[89],{"categories":1270},[89],{"categories":1272},[89],{"categories":1274},[],{"categories":1276},[],{"categories":1278},[89],{"categories":1280},[366],{"categories":1282},[89],{"categories":1284},[83],{"categories":1286},[89],{"categories":1288},[89],{"categories":1290},[],{"categories":1292},[92],{"categories":1294},[89],{"categories":1296},[95],{"categories":1298},[102],{"categories":1300},[89],{"categories":1302},[366],{"categories":1304},[89],{"categories":1306},[92],{"categories":1308},[89],{"categories":1310},[161],{"categories":1312},[92],{"categories":1314},[217],{"categories":1316},[161],{"categories":1318},[86],{"categories":1320},[92],{"categories":1322},[89],{"categories":1324},[89],{"categories":1326},[89],{"categories":1328},[89],{"categories":1330},[89],{"categories":1332},[92],{"categories":1334},[102],{"categories":1336},[89],{"categories":1338},[95],{"categories":1340},[],{"categories":1342},[124],{"categories":1344},[],{"categories":1346},[95],{"categories":1348},[92],{"categories":1350},[988],{"categories":1352},[988],{"categories":1354},[161],{"categories":1356},[89],{"categories":1358},[89],{"categories":1360},[92],{"categories":1362},[102],{"categories":1364},[161],{"categories":1366},[92],{"categories":1368},[124],{"categories":1370},[],{"categories":1372},[89],{"categories":1374},[],{"categories":1376},[89],{"categories":1378},[89],{"categories":1380},[89],{"categories":1382},[1383],"Contract Review & E-Discovery",{"categories":1385},[161],{"categories":1387},[89],{"categories":1389},[83],{"categories":1391},[124],{"categories":1393},[89],{"categories":1395},[89],{"categories":1397},[186],{"categories":1399},[102],{"categories":1401},[89],{"categories":1403},[89],{"categories":1405},[92],{"categories":1407},[92],{"categories":1409},[718],{"categories":1411},[92],{"categories":1413},[92],{"categories":1415},[89],{"categories":1417},[89],{"categories":1419},[92],{"categories":1421},[89],{"categories":1423},[366],{"categories":1425},[349],{"categories":1427},[89],{"categories":1429},[92],{"categories":1431},[89],{"categories":1433},[1434],"Law-Firm Practice & Adoption",{"categories":1436},[89],{"categories":1438},[92],{"categories":1440},[161],{"categories":1442},[89],{"categories":1444},[89],{"categories":1446},[],{"categories":1448},[],{"categories":1450},[102],{"categories":1452},[],{"categories":1454},[83],{"categories":1456},[217],{"categories":1458},[89],{"categories":1460},[],{"categories":1462},[83],{"categories":1464},[86],{"categories":1466},[89],{"categories":1468},[186],{"categories":1470},[],{"categories":1472},[86],{"categories":1474},[86],{"categories":1476},[],{"categories":1478},[89],{"categories":1480},[89],{"categories":1482},[102],{"categories":1484},[],{"categories":1486},[],{"categories":1488},[],{"categories":1490},[],{"categories":1492},[89],{"categories":1494},[92],{"categories":1496},[217],{"categories":1498},[89],{"categories":1500},[83],{"categories":1502},[102],{"categories":1504},[89],{"categories":1506},[89],{"categories":1508},[102],{"categories":1510},[95],{"categories":1512},[89],{"categories":1514},[739],{"categories":1516},[89],{"categories":1518},[186],{"categories":1520},[102],{"categories":1522},[86],{"categories":1524},[89],{"categories":1526},[89],{"categories":1528},[161],{"categories":1530},[89],{"categories":1532},[89],{"categories":1534},[89],{"categories":1536},[92],{"categories":1538},[89,83],{"categories":1540},[366],{"categories":1542},[89],{"categories":1544},[102],{"categories":1546},[102],{"categories":1548},[161],{"categories":1550},[92],{"categories":1552},[102],{"categories":1554},[89],{"categories":1556},[89],{"categories":1558},[],{"categories":1560},[],{"categories":1562},[89],{"categories":1564},[],{"categories":1566},[89],{"categories":1568},[102],{"categories":1570},[59],{"categories":1572},[124],{"categories":1574},[161],{"categories":1576},[89],{"categories":1578},[102],{"categories":1580},[],{"categories":1582},[92],{"categories":1584},[89],{"categories":1586},[89],{"categories":1588},[89],{"categories":1590},[89],{"categories":1592},[],{"categories":1594},[92],{"categories":1596},[89],{"categories":1598},[89],{"categories":1600},[],{"categories":1602},[92],{"categories":1604},[89],{"categories":1606},[89],{"categories":1608},[86],{"categories":1610},[89],{"categories":1612},[],{"categories":1614},[83],{"categories":1616},[89],{"categories":1618},[161],{"categories":1620},[102],{"categories":1622},[89],{"categories":1624},[83],{"categories":1626},[89],{"categories":1628},[102],{"categories":1630},[186],{"categories":1632},[92],{"categories":1634},[92],{"categories":1636},[89,161],{"categories":1638},[89],{"categories":1640},[124],{"categories":1642},[89],{"categories":1644},[124],{"categories":1646},[92],{"categories":1648},[161],{"categories":1650},[],{"categories":1652},[102],{"categories":1654},[217],{"categories":1656},[161],{"categories":1658},[102],{"categories":1660},[89],{"categories":1662},[95],{"categories":1664},[89],{"categories":1666},[92],{"categories":1668},[],{"categories":1670},[],{"categories":1672},[89],{"categories":1674},[],{"categories":1676},[],{"categories":1678},[95],{"categories":1680},[102],{"categories":1682},[89],{"categories":1684},[92],{"categories":1686},[92],{"categories":1688},[86],{"categories":1690},[92],{"categories":1692},[217],{"categories":1694},[89],{"categories":1696},[89],{"categories":1698},[113],{"categories":1700},[89],{"categories":1702},[89],{"categories":1704},[92],{"categories":1706},[89],{"categories":1708},[89],{"categories":1710},[324],{"categories":1712},[718],{"categories":1714},[],{"categories":1716},[161],{"categories":1718},[1434],{"categories":1720},[102],{"categories":1722},[],{"categories":1724},[],{"categories":1726},[92],{"categories":1728},[],{"categories":1730},[],{"categories":1732},[186],{"categories":1734},[186],{"categories":1736},[92],{"categories":1738},[102],{"categories":1740},[],{"categories":1742},[89],{"categories":1744},[89],{"categories":1746},[102],{"categories":1748},[1383],{"categories":1750},[161],{"categories":1752},[161],{"categories":1754},[89],{"categories":1756},[92],{"categories":1758},[83],{"categories":1760},[89],{"categories":1762},[89],{"categories":1764},[161],{"categories":1766},[161],{"categories":1768},[92],{"categories":1770},[92],{"categories":1772},[89],{"categories":1774},[],{"categories":1776},[89],{"categories":1778},[],{"categories":1780},[1781],"Interaction & Product Design",{"categories":1783},[89],{"categories":1785},[92],{"categories":1787},[244],{"categories":1789},[124],{"categories":1791},[102],{"categories":1793},[89],{"categories":1795},[89],{"categories":1797},[102],{"categories":1799},[83],{"categories":1801},[89],{"categories":1803},[],{"categories":1805},[92],{"categories":1807},[92],{"categories":1809},[],{"categories":1811},[102],{"categories":1813},[89],{"categories":1815},[83],{"categories":1817},[1781],{"categories":1819},[89],{"categories":1821},[83],{"categories":1823},[83],{"categories":1825},[],{"categories":1827},[102],{"categories":1829},[],{"categories":1831},[92],{"categories":1833},[124],{"categories":1835},[89],{"categories":1837},[92],{"categories":1839},[89],{"categories":1841},[92],{"categories":1843},[89],{"categories":1845},[124],{"categories":1847},[59],{"categories":1849},[89],{"categories":1851},[95],{"categories":1853},[102],{"categories":1855},[1856],"Coding Agents & Dev Productivity",{"categories":1858},[124],{"categories":1860},[161],{"categories":1862},[],{"categories":1864},[89],{"categories":1866},[718],{"categories":1868},[],{"categories":1870},[89],{"categories":1872},[89],{"categories":1874},[124],{"categories":1876},[],{"categories":1878},[],{"categories":1880},[89],{"categories":1882},[],{"categories":1884},[92],{"categories":1886},[89],{"categories":1888},[],{"categories":1890},[102],{"categories":1892},[102],{"categories":1894},[89],{"categories":1896},[59],{"categories":1898},[],{"categories":1900},[89],{"categories":1902},[89],{"categories":1904},[89],{"categories":1906},[59],{"categories":1908},[102],{"categories":1910},[],{"categories":1912},[],{"categories":1914},[92],{"categories":1916},[92],{"categories":1918},[303],{"categories":1920},[102],{"categories":1922},[102],{"categories":1924},[92],{"categories":1926},[124],{"categories":1928},[124],{"categories":1930},[92],{"categories":1932},[92],{"categories":1934},[89],{"categories":1936},[83],{"categories":1938},[1781],{"categories":1940},[89,217],{"categories":1942},[],{"categories":1944},[161],{"categories":1946},[102],{"categories":1948},[83],{"categories":1950},[89],{"categories":1952},[92],{"categories":1954},[1955],"The Designer's Role & Craft",{"categories":1957},[161],{"categories":1959},[],{"categories":1961},[92],{"categories":1963},[89],{"categories":1965},[92],{"categories":1967},[92],{"categories":1969},[89],{"categories":1971},[186],{"categories":1973},[89],{"categories":1975},[102],{"categories":1977},[161],{"categories":1979},[89],{"categories":1981},[],{"categories":1983},[92],{"categories":1985},[161],{"categories":1987},[89],{"categories":1989},[89],{"categories":1991},[1992],"AI UX Patterns",{"categories":1994},[92],{"categories":1996},[92],{"categories":1998},[92],{"categories":2000},[92],{"categories":2002},[186],{"categories":2004},[59],{"categories":2006},[89],{"categories":2008},[92],{"categories":2010},[89],{"categories":2012},[988],{"categories":2014},[],{"categories":2016},[186],{"categories":2018},[124],{"categories":2020},[102],{"categories":2022},[89],{"categories":2024},[92],{"categories":2026},[],{"categories":2028},[],{"categories":2030},[89],{"categories":2032},[92],{"categories":2034},[89],{"categories":2036},[92],{"categories":2038},[303],{"categories":2040},[161],{"categories":2042},[124],{"categories":2044},[102],{"categories":2046},[89],{"categories":2048},[92],{"categories":2050},[92],{"categories":2052},[],{"categories":2054},[89],{"categories":2056},[],{"categories":2058},[],{"categories":2060},[89],{"categories":2062},[89],{"categories":2064},[92],{"categories":2066},[102],{"categories":2068},[],{"categories":2070},[],{"categories":2072},[59],{"categories":2074},[113],{"categories":2076},[89],{"categories":2078},[59],{"categories":2080},[124],{"categories":2082},[89],{"categories":2084},[89],{"categories":2086},[92],{"categories":2088},[92],{"categories":2090},[89],{"categories":2092},[92],{"categories":2094},[],{"categories":2096},[],{"categories":2098},[89],{"categories":2100},[217],{"categories":2102},[89],{"categories":2104},[],{"categories":2106},[],{"categories":2108},[161],{"categories":2110},[739],{"categories":2112},[92],{"categories":2114},[83],{"categories":2116},[1955],{"categories":2118},[],{"categories":2120},[],{"categories":2122},[89],{"categories":2124},[],{"categories":2126},[],{"categories":2128},[102],{"categories":2130},[124],{"categories":2132},[186],{"categories":2134},[86],{"categories":2136},[89],{"categories":2138},[89],{"categories":2140},[86],{"categories":2142},[],{"categories":2144},[161],{"categories":2146},[89],{"categories":2148},[92],{"categories":2150},[86],{"categories":2152},[89],{"categories":2154},[89],{"categories":2156},[83],{"categories":2158},[89],{"categories":2160},[],{"categories":2162},[83],{"categories":2164},[89],{"categories":2166},[186],{"categories":2168},[92],{"categories":2170},[124],{"categories":2172},[89],{"categories":2174},[86],{"categories":2176},[89],{"categories":2178},[89],{"categories":2180},[89],{"categories":2182},[92],{"categories":2184},[],{"categories":2186},[89],{"categories":2188},[102],{"categories":2190},[83],{"categories":2192},[89],{"categories":2194},[89],{"categories":2196},[],{"categories":2198},[366],{"categories":2200},[124],{"categories":2202},[89],{"categories":2204},[89],{"categories":2206},[],{"categories":2208},[86],{"categories":2210},[86],{"categories":2212},[89],{"categories":2214},[89],{"categories":2216},[95],{"categories":2218},[89],{"categories":2220},[89],{"categories":2222},[102],{"categories":2224},[102],{"categories":2226},[89],{"categories":2228},[],{"categories":2230},[102],{"categories":2232},[89],{"categories":2234},[102],{"categories":2236},[451],{"categories":2238},[],{"categories":2240},[],{"categories":2242},[89],{"categories":2244},[124],{"categories":2246},[],{"categories":2248},[217],{"categories":2250},[89],{"categories":2252},[89],{"categories":2254},[161],{"categories":2256},[709],{"categories":2258},[],{"categories":2260},[89],{"categories":2262},[89],{"categories":2264},[102],{"categories":2266},[89],{"categories":2268},[89],{"categories":2270},[89,217],{"categories":2272},[89],{"categories":2274},[89],{"categories":2276},[161],{"categories":2278},[92],{"categories":2280},[],{"categories":2282},[92],{"categories":2284},[92],{"categories":2286},[89],{"categories":2288},[89],{"categories":2290},[89],{"categories":2292},[59],{"categories":2294},[89],{"categories":2296},[1992],{"categories":2298},[83],{"categories":2300},[59],{"categories":2302},[83],{"categories":2304},[102],{"categories":2306},[161],{"categories":2308},[92],{"categories":2310},[89],{"categories":2312},[],{"categories":2314},[89],{"categories":2316},[124],{"categories":2318},[89],{"categories":2320},[92],{"categories":2322},[89],{"categories":2324},[89],{"categories":2326},[86],{"categories":2328},[],{"categories":2330},[217],{"categories":2332},[89],{"categories":2334},[303],{"categories":2336},[161],{"categories":2338},[161],{"categories":2340},[102],{"categories":2342},[92],{"categories":2344},[89],{"categories":2346},[86],{"categories":2348},[124],{"categories":2350},[89],{"categories":2352},[161],{"categories":2354},[92],{"categories":2356},[89],{"categories":2358},[89],{"categories":2360},[415],{"categories":2362},[],{"categories":2364},[89],{"categories":2366},[89],{"categories":2368},[89],{"categories":2370},[],{"categories":2372},[],{"categories":2374},[89],{"categories":2376},[89],{"categories":2378},[89],{"categories":2380},[89],{"categories":2382},[102],{"categories":2384},[89],{"categories":2386},[89],{"categories":2388},[92],{"categories":2390},[89],{"categories":2392},[89],{"categories":2394},[89],{"categories":2396},[89],{"categories":2398},[],{"categories":2400},[102],{"categories":2402},[59],{"categories":2404},[89],{"categories":2406},[92],{"categories":2408},[89],{"categories":2410},[],{"categories":2412},[],{"categories":2414},[89],{"categories":2416},[89],{"categories":2418},[89],{"categories":2420},[124],{"categories":2422},[],{"categories":2424},[89],{"categories":2426},[161],{"categories":2428},[89],{"categories":2430},[217],{"categories":2432},[1434],{"categories":2434},[124],{"categories":2436},[102],{"categories":2438},[102],{"categories":2440},[102],{"categories":2442},[124],{"categories":2444},[124],{"categories":2446},[217],{"categories":2448},[],{"categories":2450},[124],{"categories":2452},[89],{"categories":2454},[83],{"categories":2456},[102],{"categories":2458},[89],{"categories":2460},[124],{"categories":2462},[],{"categories":2464},[89],{"categories":2466},[102],{"categories":2468},[59],{"categories":2470},[89],{"categories":2472},[124],{"categories":2474},[89],{"categories":2476},[102],{"categories":2478},[92],{"categories":2480},[124],{"categories":2482},[92],{"categories":2484},[217],{"categories":2486},[92],{"categories":2488},[89],{"categories":2490},[89],{"categories":2492},[102],{"categories":2494},[89],{"categories":2496},[],{"categories":2498},[86],{"categories":2500},[102],{"categories":2502},[],{"categories":2504},[],{"categories":2506},[89],{"categories":2508},[92],{"categories":2510},[89],{"categories":2512},[2513],"Frameworks & Tooling",{"categories":2515},[89],{"categories":2517},[89],{"categories":2519},[102],{"categories":2521},[89],{"categories":2523},[89],{"categories":2525},[],{"categories":2527},[59],{"categories":2529},[59],{"categories":2531},[83],{"categories":2533},[92],{"categories":2535},[161],{"categories":2537},[],{"categories":2539},[1434],{"categories":2541},[89],{"categories":2543},[102],{"categories":2545},[89],{"categories":2547},[217],{"categories":2549},[217],{"categories":2551},[],{"categories":2553},[92],{"categories":2555},[124],{"categories":2557},[124],{"categories":2559},[89],{"categories":2561},[92],{"categories":2563},[],{"categories":2565},[161],{"categories":2567},[89],{"categories":2569},[89],{"categories":2571},[],{"categories":2573},[89],{"categories":2575},[],{"categories":2577},[102],{"categories":2579},[89],{"categories":2581},[102],{"categories":2583},[217],{"categories":2585},[89],{"categories":2587},[102],{"categories":2589},[86],{"categories":2591},[89],{"categories":2593},[1434],{"categories":2595},[],{"categories":2597},[92],{"categories":2599},[83],{"categories":2601},[83],{"categories":2603},[],{"categories":2605},[92],{"categories":2607},[89],{"categories":2609},[2610],"AI Design Tooling",{"categories":2612},[161],{"categories":2614},[89],{"categories":2616},[89],{"categories":2618},[102],{"categories":2620},[161],{"categories":2622},[89],{"categories":2624},[102],{"categories":2626},[124],{"categories":2628},[95],{"categories":2630},[102],{"categories":2632},[92],{"categories":2634},[],{"categories":2636},[89],{"categories":2638},[89],{"categories":2640},[92],{"categories":2642},[89],{"categories":2644},[89],{"categories":2646},[],{"categories":2648},[92],{"categories":2650},[2513],{"categories":2652},[89],{"categories":2654},[92],{"categories":2656},[92],{"categories":2658},[102],{"categories":2660},[102],{"categories":2662},[],{"categories":2664},[102],{"categories":2666},[89],{"categories":2668},[89],{"categories":2670},[92],{"categories":2672},[86],{"categories":2674},[89],{"categories":2676},[],{"categories":2678},[89],{"categories":2680},[1781],{"categories":2682},[],{"categories":2684},[89],{"categories":2686},[89],{"categories":2688},[],{"categories":2690},[89],{"categories":2692},[89],{"categories":2694},[89],{"categories":2696},[186],{"categories":2698},[124],{"categories":2700},[89],{"categories":2702},[89],{"categories":2704},[1434],{"categories":2706},[83],{"categories":2708},[89],{"categories":2710},[89],{"categories":2712},[59],{"categories":2714},[89],{"categories":2716},[124],{"categories":2718},[92],{"categories":2720},[],{"categories":2722},[89],{"categories":2724},[161],{"categories":2726},[89],{"categories":2728},[186],{"categories":2730},[89],{"categories":2732},[92],{"categories":2734},[],{"categories":2736},[],{"categories":2738},[],{"categories":2740},[83],{"categories":2742},[124],{"categories":2744},[92],{"categories":2746},[89],{"categories":2748},[89],{"categories":2750},[89],{"categories":2752},[324],{"categories":2754},[161],{"categories":2756},[92],{"categories":2758},[89],{"categories":2760},[],{"categories":2762},[92],{"categories":2764},[92],{"categories":2766},[],{"categories":2768},[89],{"categories":2770},[92],{"categories":2772},[89],{"categories":2774},[],{"categories":2776},[89],{"categories":2778},[89],{"categories":2780},[124],{"categories":2782},[161],{"categories":2784},[92],{"categories":2786},[161],{"categories":2788},[92],{"categories":2790},[86],{"categories":2792},[],{"categories":2794},[],{"categories":2796},[89],{"categories":2798},[89],{"categories":2800},[83],{"categories":2802},[92],{"categories":2804},[124],{"categories":2806},[],{"categories":2808},[161],{"categories":2810},[],{"categories":2812},[102],{"categories":2814},[102],{"categories":2816},[161],{"categories":2818},[102],{"categories":2820},[89],{"categories":2822},[],{"categories":2824},[89],{"categories":2826},[89],{"categories":2828},[],{"categories":2830},[186],{"categories":2832},[89],{"categories":2834},[217],{"categories":2836},[102],{"categories":2838},[],{"categories":2840},[92],{"categories":2842},[89],{"categories":2844},[83],{"categories":2846},[415],{"categories":2848},[92],{"categories":2850},[92],{"categories":2852},[89],{"categories":2854},[89],{"categories":2856},[],{"categories":2858},[83],{"categories":2860},[89],{"categories":2862},[86],{"categories":2864},[102],{"categories":2866},[161],{"categories":2868},[],{"categories":2870},[],{"categories":2872},[],{"categories":2874},[92],{"categories":2876},[102],{"categories":2878},[161],{"categories":2880},[124],{"categories":2882},[89],{"categories":2884},[124],{"categories":2886},[92],{"categories":2888},[161],{"categories":2890},[89],{"categories":2892},[],{"categories":2894},[89],{"categories":2896},[113],{"categories":2898},[92],{"categories":2900},[161],{"categories":2902},[124],{"categories":2904},[86],{"categories":2906},[102],{"categories":2908},[89],{"categories":2910},[124],{"categories":2912},[186],{"categories":2914},[],{"categories":2916},[],{"categories":2918},[59],{"categories":2920},[366],{"categories":2922},[89],{"categories":2924},[92],{"categories":2926},[89,102],{"categories":2928},[124],{"categories":2930},[89],{"categories":2932},[89],{"categories":2934},[92],{"categories":2936},[89],{"categories":2938},[92],{"categories":2940},[89],{"categories":2942},[89],{"categories":2944},[],{"categories":2946},[988],{"categories":2948},[102],{"categories":2950},[161],{"categories":2952},[89],{"categories":2954},[89],{"categories":2956},[89],{"categories":2958},[59],{"categories":2960},[92],{"categories":2962},[186],{"categories":2964},[217],{"categories":2966},[],{"categories":2968},[89],{"categories":2970},[86],{"categories":2972},[92],{"categories":2974},[83],{"categories":2976},[92],{"categories":2978},[89],{"categories":2980},[92],{"categories":2982},[95],{"categories":2984},[102],{"categories":2986},[89],{"categories":2988},[89],{"categories":2990},[],{"categories":2992},[],{"categories":2994},[],{"categories":2996},[217],{"categories":2998},[89],{"categories":3000},[124],{"categories":3002},[89],{"categories":3004},[89],{"categories":3006},[89],{"categories":3008},[89],{"categories":3010},[],{"categories":3012},[59],{"categories":3014},[86],{"categories":3016},[92],{"categories":3018},[89],{"categories":3020},[],{"categories":3022},[89],{"categories":3024},[92],{"categories":3026},[89],{"categories":3028},[217],{"categories":3030},[],{"categories":3032},[161],{"categories":3034},[161],{"categories":3036},[],{"categories":3038},[102],{"categories":3040},[89],{"categories":3042},[161],{"categories":3044},[89],{"categories":3046},[86],{"categories":3048},[92],{"categories":3050},[89],{"categories":3052},[],{"categories":3054},[124],{"categories":3056},[89],{"categories":3058},[89],{"categories":3060},[89],{"categories":3062},[161],{"categories":3064},[92],{"categories":3066},[124],{"categories":3068},[],{"categories":3070},[92],{"categories":3072},[92],{"categories":3074},[161],{"categories":3076},[89],{"categories":3078},[89],{"categories":3080},[89],{"categories":3082},[366],{"categories":3084},[89],{"categories":3086},[],{"categories":3088},[89],{"categories":3090},[89],{"categories":3092},[217],{"categories":3094},[124],{"categories":3096},[59],{"categories":3098},[451],{"categories":3100},[59],{"categories":3102},[],{"categories":3104},[],{"categories":3106},[],{"categories":3108},[92],{"categories":3110},[92],{"categories":3112},[102],{"categories":3114},[89],{"categories":3116},[349],{"categories":3118},[102],{"categories":3120},[89],{"categories":3122},[89],{"categories":3124},[89],{"categories":3126},[89],{"categories":3128},[92],{"categories":3130},[],{"categories":3132},[],{"categories":3134},[89],{"categories":3136},[],{"categories":3138},[89],{"categories":3140},[92],{"categories":3142},[161],{"categories":3144},[89],{"categories":3146},[89],{"categories":3148},[],{"categories":3150},[95],{"categories":3152},[89],{"categories":3154},[161],{"categories":3156},[89],{"categories":3158},[92],{"categories":3160},[86],{"categories":3162},[89],{"categories":3164},[186],{"categories":3166},[92],{"categories":3168},[89],{"categories":3170},[709],{"categories":3172},[89],{"categories":3174},[92],{"categories":3176},[89],{"categories":3178},[102],{"categories":3180},[89],{"categories":3182},[415],{"categories":3184},[161],{"categories":3186},[],{"categories":3188},[124],{"categories":3190},[366],{"categories":3192},[92],{"categories":3194},[89],{"categories":3196},[],{"categories":3198},[124],{"categories":3200},[303],{"categories":3202},[92],{"categories":3204},[92],{"categories":3206},[89],{"categories":3208},[89],{"categories":3210},[92],{"categories":3212},[],{"categories":3214},[86],{"categories":3216},[92],{"categories":3218},[],{"categories":3220},[102],{"categories":3222},[89],{"categories":3224},[83],{"categories":3226},[124],{"categories":3228},[217],{"categories":3230},[113],{"categories":3232},[92],{"categories":3234},[92],{"categories":3236},[89],{"categories":3238},[92],{"categories":3240},[83],{"categories":3242},[],{"categories":3244},[89],{"categories":3246},[89],{"categories":3248},[],{"categories":3250},[],{"categories":3252},[161],{"categories":3254},[89,86],{"categories":3256},[92],{"categories":3258},[89],{"categories":3260},[],{"categories":3262},[83],{"categories":3264},[59],{"categories":3266},[86],{"categories":3268},[89],{"categories":3270},[102],{"categories":3272},[89],{"categories":3274},[92],{"categories":3276},[89],{"categories":3278},[89],{"categories":3280},[89],{"categories":3282},[124],{"categories":3284},[988],{"categories":3286},[92],{"categories":3288},[89],{"categories":3290},[],{"categories":3292},[],{"categories":3294},[92],{"categories":3296},[89],{"categories":3298},[217],{"categories":3300},[],{"categories":3302},[89],{"categories":3304},[92],{"categories":3306},[113],{"categories":3308},[92],{"categories":3310},[366],{"categories":3312},[],{"categories":3314},[324],{"categories":3316},[92],{"categories":3318},[89],{"categories":3320},[186],{"categories":3322},[89],{"categories":3324},[59],{"categories":3326},[92],{"categories":3328},[89],{"categories":3330},[366],{"categories":3332},[89],{"categories":3334},[217],{"categories":3336},[],{"categories":3338},[89],{"categories":3340},[186],{"categories":3342},[161],{"categories":3344},[89],{"categories":3346},[89],{"categories":3348},[],{"categories":3350},[186],{"categories":3352},[124],{"categories":3354},[89],{"categories":3356},[89],{"categories":3358},[451],{"categories":3360},[83],{"categories":3362},[89],{"categories":3364},[],{"categories":3366},[],{"categories":3368},[161],{"categories":3370},[89],{"categories":3372},[59],{"categories":3374},[186],{"categories":3376},[92],{"categories":3378},[186],{"categories":3380},[124],{"categories":3382},[],{"categories":3384},[89],{"categories":3386},[],{"categories":3388},[89],{"categories":3390},[470],{"categories":3392},[89],{"categories":3394},[89],{"categories":3396},[92],{"categories":3398},[366],{"categories":3400},[89],{"categories":3402},[89],{"categories":3404},[89],{"categories":3406},[],{"categories":3408},[89,102],{"categories":3410},[124],{"categories":3412},[92],{"categories":3414},[102],{"categories":3416},[92],{"categories":3418},[739],{"categories":3420},[102],{"categories":3422},[89],{"categories":3424},[83],{"categories":3426},[],{"categories":3428},[],{"categories":3430},[92],{"categories":3432},[89],{"categories":3434},[102],{"categories":3436},[83],{"categories":3438},[102],{"categories":3440},[102],{"categories":3442},[89],{"categories":3444},[186],{"categories":3446},[89],{"categories":3448},[102],{"categories":3450},[],{"categories":3452},[89],{"categories":3454},[161,89],{"categories":3456},[217],{"categories":3458},[83],{"categories":3460},[],{"categories":3462},[89],{"categories":3464},[89],{"categories":3466},[86],{"categories":3468},[86],{"categories":3470},[89],{"categories":3472},[89],{"categories":3474},[303],{"categories":3476},[89],{"categories":3478},[102],{"categories":3480},[59],{"categories":3482},[92],{"categories":3484},[89],{"categories":3486},[89],{"categories":3488},[124],{"categories":3490},[186],{"categories":3492},[161],{"categories":3494},[89],{"categories":3496},[89],{"categories":3498},[89],{"categories":3500},[89],{"categories":3502},[83],{"categories":3504},[89],{"categories":3506},[92],{"categories":3508},[92],{"categories":3510},[102],{"categories":3512},[124],{"categories":3514},[102],{"categories":3516},[],{"categories":3518},[],{"categories":3520},[59],{"categories":3522},[89],{"categories":3524},[102],{"categories":3526},[89],{"categories":3528},[161],{"categories":3530},[366],{"categories":3532},[324],{"categories":3534},[303],{"categories":3536},[89],{"categories":3538},[89],{"categories":3540},[89],{"categories":3542},[59],{"categories":3544},[89],{"categories":3546},[89],{"categories":3548},[89],{"categories":3550},[92],{"categories":3552},[83],{"categories":3554},[92],{"categories":3556},[89,86],{"categories":3558},[],{"categories":3560},[161],{"categories":3562},[],{"categories":3564},[95],{"categories":3566},[89],{"categories":3568},[124],{"categories":3570},[83],{"categories":3572},[83],{"categories":3574},[92],{"categories":3576},[92],{"categories":3578},[92],{"categories":3580},[89],{"categories":3582},[89],{"categories":3584},[86],{"categories":3586},[102],{"categories":3588},[186],{"categories":3590},[89],{"categories":3592},[],{"categories":3594},[124],{"categories":3596},[89],{"categories":3598},[89],{"categories":3600},[89],{"categories":3602},[89],{"categories":3604},[89],{"categories":3606},[102],{"categories":3608},[124],{"categories":3610},[102],{"categories":3612},[102],{"categories":3614},[89],{"categories":3616},[89],{"categories":3618},[324],{"categories":3620},[89],{"categories":3622},[92],{"categories":3624},[124],{"categories":3626},[89],{"categories":3628},[89],{"categories":3630},[89],{"categories":3632},[92],{"categories":3634},[89],{"categories":3636},[89],{"categories":3638},[89],{"categories":3640},[2513],{"categories":3642},[3643],"Clinical AI",{"categories":3645},[161],{"categories":3647},[89],{"categories":3649},[89],{"categories":3651},[89],{"categories":3653},[217],{"categories":3655},[1992],{"categories":3657},[89],{"categories":3659},[95],{"categories":3661},[89],{"categories":3663},[92],{"categories":3665},[89],{"categories":3667},[89],{"categories":3669},[124],{"categories":3671},[89],{"categories":3673},[92],{"categories":3675},[186],{"categories":3677},[89],{"categories":3679},[89],{"categories":3681},[86],{"categories":3683},[89],{"categories":3685},[415],{"categories":3687},[89],{"categories":3689},[],{"categories":3691},[89],{"categories":3693},[102],{"categories":3695},[89],{"categories":3697},[],{"categories":3699},[],{"categories":3701},[89],{"categories":3703},[],{"categories":3705},[86],{"categories":3707},[89],{"categories":3709},[92],{"categories":3711},[124],{"categories":3713},[124],{"categories":3715},[124],{"categories":3717},[124],{"categories":3719},[],{"categories":3721},[83],{"categories":3723},[92],{"categories":3725},[124],{"categories":3727},[89],{"categories":3729},[470],{"categories":3731},[95],{"categories":3733},[89],{"categories":3735},[83],{"categories":3737},[92],{"categories":3739},[89],{"categories":3741},[89],{"categories":3743},[89,92],{"categories":3745},[92],{"categories":3747},[217],{"categories":3749},[124],{"categories":3751},[92],{"categories":3753},[124],{"categories":3755},[92],{"categories":3757},[89],{"categories":3759},[],{"categories":3761},[124],{"categories":3763},[186],{"categories":3765},[83],{"categories":3767},[89],{"categories":3769},[89],{"categories":3771},[],{"categories":3773},[102],{"categories":3775},[],{"categories":3777},[83],{"categories":3779},[92],{"categories":3781},[124],{"categories":3783},[89],{"categories":3785},[124],{"categories":3787},[83],{"categories":3789},[124],{"categories":3791},[124],{"categories":3793},[],{"categories":3795},[86],{"categories":3797},[92],{"categories":3799},[124],{"categories":3801},[124],{"categories":3803},[124],{"categories":3805},[124],{"categories":3807},[124],{"categories":3809},[124],{"categories":3811},[124],{"categories":3813},[124],{"categories":3815},[124],{"categories":3817},[124],{"categories":3819},[59],{"categories":3821},[83],{"categories":3823},[89],{"categories":3825},[89],{"categories":3827},[92],{"categories":3829},[92],{"categories":3831},[],{"categories":3833},[89,83],{"categories":3835},[],{"categories":3837},[92],{"categories":3839},[124],{"categories":3841},[92],{"categories":3843},[739],{"categories":3845},[89],{"categories":3847},[89],{"categories":3849},[89],{"categories":3851},[89],{"categories":3853},[303],{"categories":3855},[89],{"categories":3857},[92],{"categories":3859},[86],{"categories":3861},[92],{"categories":3863},[92],{"categories":3865},[],{"categories":3867},[92],{"categories":3869},[161],{"categories":3871},[124],{"categories":3873},[89],{"categories":3875},[],{"categories":3877},[],{"categories":3879},[92],{"categories":3881},[161],{"categories":3883},[89],{"categories":3885},[],{"categories":3887},[89],{"categories":3889},[],{"categories":3891},[186],{"categories":3893},[89],{"categories":3895},[],{"categories":3897},[],{"categories":3899},[124],{"categories":3901},[83],{"categories":3903},[89],{"categories":3905},[89],{"categories":3907},[86],{"categories":3909},[89],{"categories":3911},[89],{"categories":3913},[89],{"categories":3915},[86],{"categories":3917},[161],{"categories":3919},[],{"categories":3921},[89],{"categories":3923},[124],{"categories":3925},[],{"categories":3927},[89],{"categories":3929},[89],{"categories":3931},[161],{"categories":3933},[89],{"categories":3935},[186],{"categories":3937},[89],{"categories":3939},[217],{"categories":3941},[],{"categories":3943},[92],{"categories":3945},[186],{"categories":3947},[102],{"categories":3949},[],{"categories":3951},[89],{"categories":3953},[],{"categories":3955},[92],{"categories":3957},[161],{"categories":3959},[102],{"categories":3961},[],{"categories":3963},[2513],{"categories":3965},[86],{"categories":3967},[83],{"categories":3969},[59],{"categories":3971},[92],{"categories":3973},[161],{"categories":3975},[102],{"categories":3977},[],{"categories":3979},[],{"categories":3981},[89],{"categories":3983},[83],{"categories":3985},[89],{"categories":3987},[186],{"categories":3989},[],{"categories":3991},[92],{"categories":3993},[92],{"categories":3995},[92],{"categories":3997},[89],{"categories":3999},[124],{"categories":4001},[102],{"categories":4003},[89],{"categories":4005},[92],{"categories":4007},[95],{"categories":4009},[89],{"categories":4011},[92],{"categories":4013},[89],{"categories":4015},[95],{"categories":4017},[186],{"categories":4019},[124],{"categories":4021},[],{"categories":4023},[186],{"categories":4025},[],{"categories":4027},[102],{"categories":4029},[92],{"categories":4031},[],{"categories":4033},[89],{"categories":4035},[89],{"categories":4037},[89],{"categories":4039},[89],{"categories":4041},[92],{"categories":4043},[86],{"categories":4045},[83],{"categories":4047},[89],{"categories":4049},[161],{"categories":4051},[102],{"categories":4053},[102],{"categories":4055},[89],{"categories":4057},[59],{"categories":4059},[92],{"categories":4061},[89],{"categories":4063},[92],{"categories":4065},[89],{"categories":4067},[86],{"categories":4069},[161],{"categories":4071},[102],{"categories":4073},[92],{"categories":4075},[89],{"categories":4077},[95],{"categories":4079},[89],{"categories":4081},[92],{"categories":4083},[89],{"categories":4085},[124],{"categories":4087},[],{"categories":4089},[83],{"categories":4091},[89],{"categories":4093},[89],{"categories":4095},[89],{"categories":4097},[102],{"categories":4099},[89],{"categories":4101},[102],{"categories":4103},[89],{"categories":4105},[92],{"categories":4107},[89],{"categories":4109},[89],{"categories":4111},[89],{"categories":4113},[89],{"categories":4115},[],{"categories":4117},[89],{"categories":4119},[161],{"categories":4121},[86],{"categories":4123},[124],{"categories":4125},[92],{"categories":4127},[89],{"categories":4129},[89],{"categories":4131},[161],{"categories":4133},[92],{"categories":4135},[89],{"categories":4137},[186],{"categories":4139},[89],{"categories":4141},[59],{"categories":4143},[89],{"categories":4145},[89],{"categories":4147},[124],{"categories":4149},[89],{"categories":4151},[89],{"categories":4153},[92],{"categories":4155},[217],{"categories":4157},[89],{"categories":4159},[102],{"categories":4161},[92],{"categories":4163},[59],{"categories":4165},[],{"categories":4167},[92],{"categories":4169},[102],{"categories":4171},[89],{"categories":4173},[1856],{"categories":4175},[161],{"categories":4177},[244],{"categories":4179},[89],{"categories":4181},[83],{"categories":4183},[102],{"categories":4185},[86],{"categories":4187},[102],{"categories":4189},[89],{"categories":4191},[],{"categories":4193},[92],{"categories":4195},[92],{"categories":4197},[89],{"categories":4199},[89],{"categories":4201},[59],{"categories":4203},[],{"categories":4205},[124],{"categories":4207},[],{"categories":4209},[124],{"categories":4211},[89],{"categories":4213},[89],{"categories":4215},[92],{"categories":4217},[92],{"categories":4219},[92],{"categories":4221},[],{"categories":4223},[124],{"categories":4225},[89],{"categories":4227},[],{"categories":4229},[89],{"categories":4231},[89],{"categories":4233},[],{"categories":4235},[161],{"categories":4237},[102],{"categories":4239},[92],{"categories":4241},[89],{"categories":4243},[89],{"categories":4245},[186],{"categories":4247},[89],{"categories":4249},[89],{"categories":4251},[83],{"categories":4253},[],{"categories":4255},[89],{"categories":4257},[89],{"categories":4259},[],{"categories":4261},[83],{"categories":4263},[124],{"categories":4265},[102],{"categories":4267},[366],{"categories":4269},[89],{"categories":4271},[89],{"categories":4273},[89],{"categories":4275},[102],{"categories":4277},[124],{"categories":4279},[161],{"categories":4281},[89],{"categories":4283},[89],{"categories":4285},[89],{"categories":4287},[124],{"categories":4289},[161],{"categories":4291},[89],{"categories":4293},[124],{"categories":4295},[161],{"categories":4297},[89],{"categories":4299},[124],{"categories":4301},[92],{"categories":4303},[92],{"categories":4305},[92],{"categories":4307},[102],{"categories":4309},[124],{"categories":4311},[92],{"categories":4313},[92],{"categories":4315},[89],{"categories":4317},[102],{"categories":4319},[161],{"categories":4321},[89],{"categories":4323},[],{"categories":4325},[92],{"categories":4327},[],{"categories":4329},[],{"categories":4331},[],{"categories":4333},[92],{"categories":4335},[86],{"categories":4337},[92],{"categories":4339},[4340],"Liability & Ethics",{"categories":4342},[89],{"categories":4344},[92],{"categories":4346},[83],{"categories":4348},[92],{"categories":4350},[86],{"categories":4352},[186],{"categories":4354},[92],{"categories":4356},[],{"categories":4358},[451],{"categories":4360},[92],{"categories":4362},[],{"categories":4364},[83],{"categories":4366},[92],{"categories":4368},[],{"categories":4370},[92],{"categories":4372},[89],{"categories":4374},[89],{"categories":4376},[124],{"categories":4378},[89],{"categories":4380},[89],{"categories":4382},[92],{"categories":4384},[89],{"categories":4386},[89],{"categories":4388},[124],{"categories":4390},[92],{"categories":4392},[102],{"categories":4394},[161],{"categories":4396},[83],{"categories":4398},[89],{"categories":4400},[],{"categories":4402},[92],{"categories":4404},[92],{"categories":4406},[366],{"categories":4408},[161],{"categories":4410},[217],{"categories":4412},[124],{"categories":4414},[89],{"categories":4416},[161],{"categories":4418},[89],{"categories":4420},[83],{"categories":4422},[],{"categories":4424},[92],{"categories":4426},[89],{"categories":4428},[89],{"categories":4430},[92],{"categories":4432},[89],{"categories":4434},[161],{"categories":4436},[],{"categories":4438},[92],{"categories":4440},[95],{"categories":4442},[124],{"categories":4444},[92],{"categories":4446},[86],{"categories":4448},[],{"categories":4450},[89],{"categories":4452},[95],{"categories":4454},[89],{"categories":4456},[92],{"categories":4458},[124],{"categories":4460},[83],{"categories":4462},[217],{"categories":4464},[89],{"categories":4466},[89],{"categories":4468},[89],{"categories":4470},[124],{"categories":4472},[86],{"categories":4474},[89],{"categories":4476},[161],{"categories":4478},[124],{"categories":4480},[217],{"categories":4482},[89],{"categories":4484},[92],{"categories":4486},[],{"categories":4488},[415],{"categories":4490},[],{"categories":4492},[89],{"categories":4494},[217],{"categories":4496},[59],{"categories":4498},[92],{"categories":4500},[92],{"categories":4502},[4503],"Design News & Tools",{"categories":4505},[89],{"categories":4507},[124],{"categories":4509},[89],{"categories":4511},[83],{"categories":4513},[89],{"categories":4515},[161],{"categories":4517},[92],{"categories":4519},[92],{"categories":4521},[89],{"categories":4523},[366],{"categories":4525},[89],{"categories":4527},[366],{"categories":4529},[186],{"categories":4531},[89],{"categories":4533},[92],{"categories":4535},[],{"categories":4537},[89],{"categories":4539},[89],{"categories":4541},[89],{"categories":4543},[124],{"categories":4545},[83],{"categories":4547},[],{"categories":4549},[89],{"categories":4551},[89],{"categories":4553},[102],{"categories":4555},[470],{"categories":4557},[102],{"categories":4559},[161],{"categories":4561},[89],{"categories":4563},[89,92],{"categories":4565},[186,86],{"categories":4567},[89],{"categories":4569},[89],{"categories":4571},[89],{"categories":4573},[],{"categories":4575},[92],{"categories":4577},[],{"categories":4579},[102],{"categories":4581},[89],{"categories":4583},[102],{"categories":4585},[],{"categories":4587},[92],{"categories":4589},[89],{"categories":4591},[124],{"categories":4593},[89],{"categories":4595},[],{"categories":4597},[92],{"categories":4599},[89],{"categories":4601},[],{"categories":4603},[161],{"categories":4605},[89],{"categories":4607},[92],{"categories":4609},[89],{"categories":4611},[89],{"categories":4613},[83],{"categories":4615},[92],{"categories":4617},[89],{"categories":4619},[],{"categories":4621},[217],{"categories":4623},[186],{"categories":4625},[86],{"categories":4627},[86],{"categories":4629},[89],{"categories":4631},[83],{"categories":4633},[83],{"categories":4635},[89],{"categories":4637},[92],{"categories":4639},[89],{"categories":4641},[89],{"categories":4643},[89],{"categories":4645},[102],{"categories":4647},[89],{"categories":4649},[83],{"categories":4651},[92],{"categories":4653},[89],{"categories":4655},[186],{"categories":4657},[89],{"categories":4659},[124],{"categories":4661},[89],{"categories":4663},[89],{"categories":4665},[92],{"categories":4667},[89],{"categories":4669},[],{"categories":4671},[102],{"categories":4673},[],{"categories":4675},[102],{"categories":4677},[92],{"categories":4679},[83],{"categories":4681},[],{"categories":4683},[59],{"categories":4685},[217],{"categories":4687},[89],{"categories":4689},[102],{"categories":4691},[89],{"categories":4693},[],{"categories":4695},[124],{"categories":4697},[92],{"categories":4699},[102],{"categories":4701},[161],{"categories":4703},[89],{"categories":4705},[92],{"categories":4707},[102],{"categories":4709},[92],{"categories":4711},[124],{"categories":4713},[89],{"categories":4715},[83],{"categories":4717},[124],{"categories":4719},[102],{"categories":4721},[89],{"categories":4723},[161],{"categories":4725},[86],{"categories":4727},[89],{"categories":4729},[89],{"categories":4731},[89],{"categories":4733},[89],{"categories":4735},[89],{"categories":4737},[92],{"categories":4739},[89],{"categories":4741},[92],{"categories":4743},[89],{"categories":4745},[89],{"categories":4747},[83],{"categories":4749},[89],{"categories":4751},[92],{"categories":4753},[92],{"categories":4755},[161],{"categories":4757},[92],{"categories":4759},[92],{"categories":4761},[83],{"categories":4763},[92],{"categories":4765},[161],{"categories":4767},[],{"categories":4769},[89],{"categories":4771},[59],{"categories":4773},[366],{"categories":4775},[89],{"categories":4777},[89],{"categories":4779},[89],{"categories":4781},[102],{"categories":4783},[],{"categories":4785},[92],{"categories":4787},[186],{"categories":4789},[89],{"categories":4791},[124],{"categories":4793},[92],{"categories":4795},[89],{"categories":4797},[186],{"categories":4799},[92],{"categories":4801},[86],{"categories":4803},[86],{"categories":4805},[89],{"categories":4807},[89],{"categories":4809},[89],{"categories":4811},[83],{"categories":4813},[],{"categories":4815},[89],{"categories":4817},[92],{"categories":4819},[92],{"categories":4821},[89],{"categories":4823},[89],{"categories":4825},[89],{"categories":4827},[102],{"categories":4829},[],{"categories":4831},[83],{"categories":4833},[89],{"categories":4835},[89],{"categories":4837},[92],{"categories":4839},[92],{"categories":4841},[],{"categories":4843},[102],{"categories":4845},[102],{"categories":4847},[89],{"categories":4849},[186],{"categories":4851},[86],{"categories":4853},[161],{"categories":4855},[],{"categories":4857},[89],{"categories":4859},[92],{"categories":4861},[83],{"categories":4863},[89],{"categories":4865},[102],{"categories":4867},[83],{"categories":4869},[124],{"categories":4871},[59],{"categories":4873},[124],{"categories":4875},[92],{"categories":4877},[],{"categories":4879},[124],{"categories":4881},[92],{"categories":4883},[161],{"categories":4885},[59],{"categories":4887},[89],{"categories":4889},[],{"categories":4891},[92],{"categories":4893},[2513],{"categories":4895},[124],{"categories":4897},[102],{"categories":4899},[89],{"categories":4901},[89],{"categories":4903},[86],{"categories":4905},[89],{"categories":4907},[83],{"categories":4909},[1434],{"categories":4911},[217],{"categories":4913},[83],{"categories":4915},[],{"categories":4917},[],{"categories":4919},[124],{"categories":4921},[92],{"categories":4923},[124],{"categories":4925},[],{"categories":4927},[92],{"categories":4929},[92],{"categories":4931},[92],{"categories":4933},[],{"categories":4935},[89],{"categories":4937},[],{"categories":4939},[124],{"categories":4941},[83],{"categories":4943},[161],{"categories":4945},[89],{"categories":4947},[92],{"categories":4949},[124],{"categories":4951},[89],{"categories":4953},[124],{"categories":4955},[],{"categories":4957},[124],{"categories":4959},[83],{"categories":4961},[366],{"categories":4963},[92],{"categories":4965},[89],{"categories":4967},[],{"categories":4969},[102],{"categories":4971},[92],{"categories":4973},[95],{"categories":4975},[92],{"categories":4977},[83],{"categories":4979},[],{"categories":4981},[],{"categories":4983},[],{"categories":4985},[161],{"categories":4987},[92],{"categories":4989},[89],{"categories":4991},[89],{"categories":4993},[],{"categories":4995},[],{"categories":4997},[],{"categories":4999},[161],{"categories":5001},[89],{"categories":5003},[],{"categories":5005},[92],{"categories":5007},[89],{"categories":5009},[83],{"categories":5011},[],{"categories":5013},[],{"categories":5015},[161],{"categories":5017},[89],{"categories":5019},[124],{"categories":5021},[],{"categories":5023},[186],{"categories":5025},[124],{"categories":5027},[186],{"categories":5029},[59],{"categories":5031},[89],{"categories":5033},[89],{"categories":5035},[],{"categories":5037},[],{"categories":5039},[92],{"categories":5041},[],{"categories":5043},[89],{"categories":5045},[366],{"categories":5047},[89],{"categories":5049},[89],{"categories":5051},[89],{"categories":5053},[],{"categories":5055},[92],{"categories":5057},[89],{"categories":5059},[89],{"categories":5061},[],{"categories":5063},[92],{"categories":5065},[89],{"categories":5067},[124],{"categories":5069},[89],{"categories":5071},[186],{"categories":5073},[86],{"categories":5075},[89],{"categories":5077},[89],{"categories":5079},[92],{"categories":5081},[59],{"categories":5083},[92],{"categories":5085},[92],{"categories":5087},[],{"categories":5089},[],{"categories":5091},[89],{"categories":5093},[],{"categories":5095},[124],{"categories":5097},[86],{"categories":5099},[],{"categories":5101},[],{"categories":5103},[161],{"categories":5105},[83],{"categories":5107},[],{"categories":5109},[86],{"categories":5111},[186],{"categories":5113},[89],{"categories":5115},[102],{"categories":5117},[83],{"categories":5119},[59],{"categories":5121},[86],{"categories":5123},[102],{"categories":5125},[102],{"categories":5127},[],{"categories":5129},[89],{"categories":5131},[],{"categories":5133},[92],{"categories":5135},[83],{"categories":5137},[161],{"categories":5139},[89],{"categories":5141},[83],{"categories":5143},[92],{"categories":5145},[217],{"categories":5147},[89],{"categories":5149},[89],{"categories":5151},[89],{"categories":5153},[83],{"categories":5155},[59],{"categories":5157},[92],{"categories":5159},[],{"categories":5161},[89],{"categories":5163},[102],{"categories":5165},[124],{"categories":5167},[102],{"categories":5169},[89],{"categories":5171},[95],{"categories":5173},[],{"categories":5175},[161],{"categories":5177},[124],{"categories":5179},[83],{"categories":5181},[92],{"categories":5183},[89],{"categories":5185},[89],{"categories":5187},[92],{"categories":5189},[89],{"categories":5191},[89],{"categories":5193},[86],{"categories":5195},[92],{"categories":5197},[92,217],{"categories":5199},[92],{"categories":5201},[102],{"categories":5203},[89],{"categories":5205},[89],{"categories":5207},[59],{"categories":5209},[92],{"categories":5211},[186],{"categories":5213},[92],{"categories":5215},[86],{"categories":5217},[],{"categories":5219},[92],{"categories":5221},[89],{"categories":5223},[86],{"categories":5225},[],{"categories":5227},[],{"categories":5229},[102],{"categories":5231},[89],{"categories":5233},[89],{"categories":5235},[92],{"categories":5237},[59],{"categories":5239},[186],{"categories":5241},[89],{"categories":5243},[89],{"categories":5245},[92],{"categories":5247},[],{"categories":5249},[92],{"categories":5251},[124],{"categories":5253},[92],{"categories":5255},[],{"categories":5257},[124],{"categories":5259},[102],{"categories":5261},[2513],{"categories":5263},[83],{"categories":5265},[102],{"categories":5267},[89],{"categories":5269},[92],{"categories":5271},[89],{"categories":5273},[89],{"categories":5275},[186],{"categories":5277},[102],{"categories":5279},[],{"categories":5281},[124],{"categories":5283},[89],{"categories":5285},[],{"categories":5287},[92],{"categories":5289},[89],{"categories":5291},[89],{"categories":5293},[89],{"categories":5295},[92],{"categories":5297},[89],{"categories":5299},[89],{"categories":5301},[95],{"categories":5303},[92],{"categories":5305},[89],{"categories":5307},[89],{"categories":5309},[89],{"categories":5311},[89],{"categories":5313},[89],{"categories":5315},[89],{"categories":5317},[86],{"categories":5319},[],{"categories":5321},[95],{"categories":5323},[124],{"categories":5325},[92],{"categories":5327},[89],{"categories":5329},[102],{"categories":5331},[],{"categories":5333},[102],{"categories":5335},[102],{"categories":5337},[92],{"categories":5339},[102],{"categories":5341},[89],{"categories":5343},[89],{"categories":5345},[102],{"categories":5347},[89],{"categories":5349},[92],{"categories":5351},[124],{"categories":5353},[89],{"categories":5355},[89],{"categories":5357},[89],{"categories":5359},[86],{"categories":5361},[89],{"categories":5363},[92],{"categories":5365},[161],{"categories":5367},[],{"categories":5369},[89],{"categories":5371},[59],{"categories":5373},[92],{"categories":5375},[89],{"categories":5377},[],{"categories":5379},[89],{"categories":5381},[89],{"categories":5383},[124],{"categories":5385},[89],{"categories":5387},[89],{"categories":5389},[92],{"categories":5391},[186],{"categories":5393},[],{"categories":5395},[],{"categories":5397},[102],{"categories":5399},[124],{"categories":5401},[102],{"categories":5403},[124],{"categories":5405},[89],{"categories":5407},[186],{"categories":5409},[89],{"categories":5411},[83],{"categories":5413},[92],{"categories":5415},[89],{"categories":5417},[92],{"categories":5419},[92],{"categories":5421},[89],{"categories":5423},[86],{"categories":5425},[],{"categories":5427},[59],{"categories":5429},[89],{"categories":5431},[],{"categories":5433},[124],{"categories":5435},[89],{"categories":5437},[59],{"categories":5439},[89],{"categories":5441},[102],{"categories":5443},[102],{"categories":5445},[102],{"categories":5447},[92],{"categories":5449},[92],{"categories":5451},[92],{"categories":5453},[89],{"categories":5455},[89],{"categories":5457},[161],{"categories":5459},[59],{"categories":5461},[59],{"categories":5463},[],{"categories":5465},[124],{"categories":5467},[89],{"categories":5469},[89],{"categories":5471},[102],{"categories":5473},[],{"categories":5475},[124],{"categories":5477},[124],{"categories":5479},[124],{"categories":5481},[],{"categories":5483},[92],{"categories":5485},[89],{"categories":5487},[],{"categories":5489},[83],{"categories":5491},[86],{"categories":5493},[],{"categories":5495},[89],{"categories":5497},[89],{"categories":5499},[],{"categories":5501},[102],{"categories":5503},[],{"categories":5505},[],{"categories":5507},[],{"categories":5509},[],{"categories":5511},[89],{"categories":5513},[124],{"categories":5515},[],{"categories":5517},[],{"categories":5519},[89],{"categories":5521},[89],{"categories":5523},[89],{"categories":5525},[59],{"categories":5527},[89],{"categories":5529},[59],{"categories":5531},[],{"categories":5533},[59],{"categories":5535},[59],{"categories":5537},[217],{"categories":5539},[92],{"categories":5541},[102],{"categories":5543},[],{"categories":5545},[],{"categories":5547},[59],{"categories":5549},[102],{"categories":5551},[102],{"categories":5553},[102],{"categories":5555},[],{"categories":5557},[83],{"categories":5559},[102],{"categories":5561},[102],{"categories":5563},[83],{"categories":5565},[102],{"categories":5567},[86],{"categories":5569},[102],{"categories":5571},[102],{"categories":5573},[102],{"categories":5575},[59],{"categories":5577},[124],{"categories":5579},[124],{"categories":5581},[89],{"categories":5583},[102],{"categories":5585},[59],{"categories":5587},[217],{"categories":5589},[59],{"categories":5591},[59],{"categories":5593},[59],{"categories":5595},[],{"categories":5597},[86],{"categories":5599},[],{"categories":5601},[217],{"categories":5603},[102],{"categories":5605},[102],{"categories":5607},[102],{"categories":5609},[92],{"categories":5611},[124,86],{"categories":5613},[59],{"categories":5615},[],{"categories":5617},[],{"categories":5619},[59],{"categories":5621},[],{"categories":5623},[59],{"categories":5625},[124],{"categories":5627},[92],{"categories":5629},[],{"categories":5631},[102],{"categories":5633},[89],{"categories":5635},[161],{"categories":5637},[],{"categories":5639},[89],{"categories":5641},[],{"categories":5643},[124],{"categories":5645},[83],{"categories":5647},[59],{"categories":5649},[],{"categories":5651},[102],{"categories":5653},[124],[5655,5701,5778,5853],{"id":5656,"title":5657,"ai":5658,"body":5663,"categories":5688,"created_at":60,"date_modified":60,"description":52,"extension":61,"faq":60,"featured":62,"kicker_label":60,"meta":5689,"navigation":64,"path":5690,"published_at":5691,"question":60,"scraped_at":60,"seo":5692,"sitemap":5693,"source_id":5694,"source_name":5695,"source_type":71,"source_url":72,"stem":5696,"tags":5697,"thumbnail_url":60,"tldr":5698,"tweet":60,"unknown_tags":5699,"__hash__":5700},"summaries\u002Fsummaries\u002Frelative-slate-bandits-for-e-com-homepage-picks-summary.md","Relative Slate Bandits for E-com Homepage Picks",{"provider":7,"model":8,"input_tokens":5659,"output_tokens":5660,"processing_time_ms":5661,"cost_usd":5662},3602,907,8330,0.00088305,{"type":14,"value":5664,"toc":5684},[5665,5669,5672,5676,5679],[17,5666,5668],{"id":5667},"slate-selection-beats-item-picking-in-homepage-recs","Slate Selection Beats Item Picking in Homepage Recs",[22,5670,5671],{},"E-commerce homepages demand choosing one complete product slate (display plan) from candidates like recent browsing matches, promotions, high-margin pushes, or balanced mixes. This single first-screen decision drives clicks, add-to-carts, conversions, margins, and session behavior. Available context—user history, session signals, time\u002Fcampaign state, business metrics—enables compact modeling without needing full item-level predictions.",[17,5673,5675],{"id":5674},"bandit-rl-over-pure-prediction","Bandit RL Over Pure Prediction",[22,5677,5678],{},"Treating homepage recs as a contextual bandit problem captures sequential decision-making under uncertainty, where slates compete via relative quality (e.g., one outperforms others in A\u002FB tests). Policy gradient methods train efficiently on these group-relative rewards, avoiding expensive full-slate simulation or prediction of every item interaction. This scales to production where candidate slates are pre-generated.",[22,5680,5681],{},[48,5682,5683],{},"Note: Content truncates early, limiting deeper method details like exact policy gradient formulation.",{"title":52,"searchDepth":53,"depth":53,"links":5685},[5686,5687],{"id":5667,"depth":53,"text":5668},{"id":5674,"depth":53,"text":5675},[59],{},"\u002Fsummaries\u002Frelative-slate-bandits-for-e-com-homepage-picks-summary","2026-04-08 21:21:18",{"title":5657,"description":52},{"loc":5690},"e75eeddad9cbd6e6","Towards AI","summaries\u002Frelative-slate-bandits-for-e-com-homepage-picks-summary",[75,76],"Use group-relative contextual bandits to select optimal product slates for e-commerce homepages, leveraging relative quality signals for efficient RL over full prediction models.",[76],"wibqaN5w6Fdsw-Vjk5SMh4e0VHJnAL2RSSWvv47vAqE",{"id":5702,"title":5703,"ai":5704,"body":5710,"categories":5755,"created_at":60,"date_modified":60,"description":52,"extension":61,"faq":60,"featured":62,"kicker_label":60,"meta":5756,"navigation":64,"path":5764,"published_at":5765,"question":60,"scraped_at":5765,"seo":5766,"sitemap":5767,"source_id":5768,"source_name":5769,"source_type":71,"source_url":5770,"stem":5771,"tags":5772,"thumbnail_url":60,"tldr":5775,"tweet":60,"unknown_tags":5776,"__hash__":5777},"summaries\u002Fsummaries\u002F42301bcc08092f98-atod-hybrid-training-for-high-performance-ai-agent-summary.md","ATOD: Hybrid Training for High-Performance AI Agents",{"provider":7,"model":5705,"input_tokens":5706,"output_tokens":5707,"processing_time_ms":5708,"cost_usd":5709},"google\u002Fgemini-3.1-flash-lite",5992,562,3445,0.002341,{"type":14,"value":5711,"toc":5750},[5712,5716,5719,5723,5726,5743,5747],[17,5713,5715],{"id":5714},"the-hybrid-training-challenge","The Hybrid Training Challenge",[22,5717,5718],{},"Training small language-model agents for long-horizon tasks faces a fundamental trade-off between imitation learning and reinforcement learning (RL). On-policy distillation (OPD) provides dense, efficient guidance from a teacher model, leading to rapid early gains. However, this approach hits a performance ceiling once the student model mimics the teacher's behavior. Conversely, RL allows for exploration and improvement beyond the teacher's capabilities but suffers from sparse, delayed feedback, making early-stage training inefficient.",[17,5720,5722],{"id":5721},"the-atod-approach","The ATOD Approach",[22,5724,5725],{},"ATOD (Annealed Turn-aware On-policy Distillation) addresses this by integrating both methods into a unified pipeline. The algorithm employs two primary mechanisms:",[5727,5728,5729,5737],"ul",{},[5730,5731,5732,5736],"li",{},[5733,5734,5735],"strong",{},"Annealed OPD-RL Schedule:"," Instead of choosing one method, ATOD shifts the training focus over time. It starts with OPD to quickly align the student with the teacher's baseline behavior, then gradually transitions to RL. This allows the model to leverage teacher guidance for stability early on, while shifting to reward-driven exploration to surpass the teacher's performance later in the training process.",[5730,5738,5739,5742],{},[5733,5740,5741],{},"Turn-level Disagreement-Uncertainty Reweighting (T-DUR):"," To handle the complexity of long-horizon tasks, ATOD introduces T-DUR. This mechanism identifies and amplifies high-utility turns—moments where the student's actions are most critical or uncertain—ensuring the model receives dense, meaningful supervision throughout the entire trajectory rather than just at the final outcome.",[17,5744,5746],{"id":5745},"performance-gains","Performance Gains",[22,5748,5749],{},"Experimental results across benchmarks including ALFWorld, WebShop, and Search-QA demonstrate that ATOD consistently outperforms standard post-training baselines. Across various student model sizes, ATOD achieved an average success rate improvement of 3.03 points over traditional OPD and 23.62 points over GRPO. Notably, the method enabled student models to surpass their own teacher models by an average of 2.16 points, validating the effectiveness of the hybrid approach in breaking through the imitation ceiling.",{"title":52,"searchDepth":53,"depth":53,"links":5751},[5752,5753,5754],{"id":5714,"depth":53,"text":5715},{"id":5721,"depth":53,"text":5722},{"id":5745,"depth":53,"text":5746},[89],{"content_references":5757,"triage":5758},[],{"relevance":5759,"novelty":5760,"quality":5760,"actionability":5761,"composite":5762,"reasoning":5763},5,4,3,4.15,"Category: AI & LLMs. The article presents a novel approach to training AI agents that combines imitation learning and reinforcement learning, addressing a specific pain point in AI model training. It provides experimental results that demonstrate the effectiveness of the ATOD method, making it relevant and actionable for developers looking to implement advanced training techniques.","\u002Fsummaries\u002F42301bcc08092f98-atod-hybrid-training-for-high-performance-ai-agent-summary","2026-06-29 12:57:30",{"title":5703,"description":52},{"loc":5764},"42301bcc08092f98","arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.27814","summaries\u002F42301bcc08092f98-atod-hybrid-training-for-high-performance-ai-agent-summary",[5773,75,5774,76],"agents","ai-llms","ATOD combines on-policy distillation with reinforcement learning to overcome the performance ceiling of imitation learning, using an annealed schedule and turn-level reweighting to improve long-horizon agent training.",[5774,76],"GwB0Vj9zhSkCae7UhEiaVAbJyA6xeAB8vCXLNf5U2SY",{"id":5779,"title":5780,"ai":5781,"body":5786,"categories":5831,"created_at":60,"date_modified":60,"description":52,"extension":61,"faq":60,"featured":62,"kicker_label":60,"meta":5832,"navigation":64,"path":5841,"published_at":5842,"question":60,"scraped_at":5842,"seo":5843,"sitemap":5844,"source_id":5845,"source_name":5769,"source_type":71,"source_url":5846,"stem":5847,"tags":5848,"thumbnail_url":60,"tldr":5850,"tweet":60,"unknown_tags":5851,"__hash__":5852},"summaries\u002Fsummaries\u002F350b76fe51697974-breaking-filter-bubbles-with-semantic-pareto-dqn-summary.md","Breaking Filter Bubbles with Semantic Pareto-DQN",{"provider":7,"model":5705,"input_tokens":5782,"output_tokens":5783,"processing_time_ms":5784,"cost_usd":5785},5961,489,2545,0.00222375,{"type":14,"value":5787,"toc":5826},[5788,5792,5795,5799,5802,5805,5819,5823],[17,5789,5791],{"id":5790},"moving-beyond-monolithic-reward-optimization","Moving Beyond Monolithic Reward Optimization",[22,5793,5794],{},"Traditional recommender systems often rely on single-objective optimization, typically focusing on immediate user engagement. This approach leads to \"semantic homogenization\" and the creation of filter bubbles, where the system narrows the user's content horizon to maximize short-term clicks. The authors argue that standard Deep Q-Networks (DQN) are insufficient for modern requirements because they struggle to balance engagement with critical societal values like information diversity and provider fairness.",[17,5796,5798],{"id":5797},"the-semantic-pareto-dqn-framework","The Semantic Pareto-DQN Framework",[22,5800,5801],{},"To solve this, the researchers introduce a multi-objective reinforcement learning framework that treats recommendation as a semantic multi-objective Markov decision process. Instead of forcing different goals into a single, static reward scalar, the Pareto-DQN agent treats engagement, diversity, and fairness as distinct reward signals.",[22,5803,5804],{},"Key technical components include:",[5727,5806,5807,5813],{},[5730,5808,5809,5812],{},[5733,5810,5811],{},"High-Fidelity Semantic Embeddings:"," Used to capture the nuance of content, allowing the model to understand the semantic distance between items rather than relying on simple interaction counts.",[5730,5814,5815,5818],{},[5733,5816,5817],{},"Hypervolume-Based Action Selection:"," The agent maps the Pareto frontier—the set of optimal trade-offs between competing objectives—rather than converging on a single point. This allows the system to maintain high state-trajectory variance, preventing the feedback loops that cause semantic collapse.",[17,5820,5822],{"id":5821},"empirical-outcomes","Empirical Outcomes",[22,5824,5825],{},"Evaluations on the MovieLens small dataset demonstrate that this approach effectively disrupts the feedback loops responsible for filter bubbles. The framework achieves significant gains in auxiliary societal objectives (diversity and fairness) with only marginal impacts on engagement metrics. This suggests a viable path for building intrinsically aligned recommender systems that prioritize long-term user health and platform responsibility without sacrificing core business performance.",{"title":52,"searchDepth":53,"depth":53,"links":5827},[5828,5829,5830],{"id":5790,"depth":53,"text":5791},{"id":5797,"depth":53,"text":5798},{"id":5821,"depth":53,"text":5822},[89],{"content_references":5833,"triage":5838},[5834],{"type":5835,"title":5836,"context":5837},"dataset","MovieLens small dataset","mentioned",{"relevance":5760,"novelty":5760,"quality":5760,"actionability":5761,"composite":5839,"reasoning":5840},3.8,"Category: AI & LLMs. The article discusses a novel reinforcement learning framework for recommender systems, addressing a specific pain point of filter bubbles and engagement versus diversity. It presents new insights into multi-objective optimization in AI, but while it offers a theoretical framework, it lacks detailed actionable steps for implementation.","\u002Fsummaries\u002F350b76fe51697974-breaking-filter-bubbles-with-semantic-pareto-dqn-summary","2026-06-24 12:56:40",{"title":5780,"description":52},{"loc":5841},"350b76fe51697974","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.24042","summaries\u002F350b76fe51697974-breaking-filter-bubbles-with-semantic-pareto-dqn-summary",[75,5774,76,5849],"recommender-systems","A new reinforcement learning framework for recommender systems that treats engagement, diversity, and fairness as distinct, non-aggregable rewards to prevent semantic homogenization.",[5774,76,5849],"PVdo6_lHedjaDmp_kQFHOC9b97WudnwC0dgqbcRKV40",{"id":5854,"title":5855,"ai":5856,"body":5861,"categories":5889,"created_at":60,"date_modified":60,"description":52,"extension":61,"faq":60,"featured":62,"kicker_label":60,"meta":5890,"navigation":64,"path":5901,"published_at":5902,"question":60,"scraped_at":5902,"seo":5903,"sitemap":5904,"source_id":5905,"source_name":5769,"source_type":71,"source_url":5896,"stem":5906,"tags":5907,"thumbnail_url":60,"tldr":5910,"tweet":60,"unknown_tags":5911,"__hash__":5912},"summaries\u002Fsummaries\u002F778bfd017115b992-svot-enhancing-spatial-reasoning-via-state-aware-v-summary.md","SVoT: Enhancing Spatial Reasoning via State-Aware Visualization",{"provider":7,"model":5705,"input_tokens":5857,"output_tokens":5858,"processing_time_ms":5859,"cost_usd":5860},4061,492,2998,0.00175325,{"type":14,"value":5862,"toc":5884},[5863,5867,5870,5874,5877,5881],[17,5864,5866],{"id":5865},"the-limitation-of-text-only-reasoning","The Limitation of Text-Only Reasoning",[22,5868,5869],{},"Standard Chain-of-Thought (CoT) prompting often struggles with spatial reasoning because text is inherently linear and lacks the structural grounding required to represent 2D or 3D environments. When models rely solely on linguistic tokens to track spatial coordinates or object relationships, they frequently suffer from 'drift' or logical inconsistencies as the sequence length increases.",[17,5871,5873],{"id":5872},"state-aware-visualization-of-thought-svot","State-Aware Visualization-of-Thought (SVoT)",[22,5875,5876],{},"SVoT introduces a novel framework that bridges the gap between linguistic reasoning and spatial awareness. Instead of forcing the model to describe spatial states purely through text, SVoT forces the model to generate a 'visualized' state representation at each step of the reasoning process. This approach treats the spatial layout as a dynamic state that must be updated and verified throughout the inference chain.",[17,5878,5880],{"id":5879},"reinforcement-learning-for-spatial-accuracy","Reinforcement Learning for Spatial Accuracy",[22,5882,5883],{},"The core innovation of SVoT is the use of Reinforcement Learning (RL) to train the model to produce these visual state representations. By rewarding the model for maintaining spatial consistency and logical accuracy across its 'thought' steps, the system learns to ground its reasoning in a structured spatial map. This prevents the model from hallucinating object positions or invalid movements, as the visual state acts as a persistent memory buffer that the model must reconcile with its next textual action. The result is a significant reduction in spatial errors compared to traditional CoT methods, as the model is effectively forced to 'see' the environment it is reasoning about.",{"title":52,"searchDepth":53,"depth":53,"links":5885},[5886,5887,5888],{"id":5865,"depth":53,"text":5866},{"id":5872,"depth":53,"text":5873},{"id":5879,"depth":53,"text":5880},[89],{"content_references":5891,"triage":5898},[5892],{"type":5893,"title":5894,"author":5895,"url":5896,"context":5897},"paper","SVoT: State-aware Visualization-of-Thought for Spatial Reasoning via Reinforcement Learning","Unknown","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.11770","cited",{"relevance":5761,"novelty":5760,"quality":5760,"actionability":53,"composite":5899,"reasoning":5900},3.25,"Category: AI & LLMs. The article discusses a novel framework (SVoT) that enhances spatial reasoning in LLMs, addressing a specific limitation of text-only reasoning. However, while it presents new insights into the use of reinforcement learning for spatial accuracy, it lacks practical steps for implementation that the audience could directly act upon.","\u002Fsummaries\u002F778bfd017115b992-svot-enhancing-spatial-reasoning-via-state-aware-v-summary","2026-06-11 12:57:20",{"title":5855,"description":52},{"loc":5901},"778bfd017115b992","summaries\u002F778bfd017115b992-svot-enhancing-spatial-reasoning-via-state-aware-v-summary",[5908,75,5909,76],"llm","spatial-reasoning","SVoT improves spatial reasoning in LLMs by using reinforcement learning to generate state-aware visual representations of thought, allowing models to track complex spatial relationships more accurately than text-only chain-of-thought.",[5909,76],"4I2cTchJrNX04sbDTy_vPmMoVe19ZsfQNXrOGy6HZU4"]