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Teacher-student distillation

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In Good Company with Nicolai Tangen 2026-10-21-2

Eric Schmidt: The Age of Agents, Superintelligence, and Why Europe Is Falling Behind

Schmidt says the gains are real but concentrated in software, cyber and math, where learning loops are fast, and biology lags on data. The effect he is most confident about is organizational: a friend's firm cut 20% of staff, the 'glue' planners, and an estimated 2,000 of 10,000 people at a large firm are unneeded. Read against deBoer's cancer example, displacement arrives first where the work is coordination, not where the problem is physical.

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in-good-companypodcastagentic-aiorg-designchange-managementeuropean-aieuropeai-regulationchina-aidistillationopen-modelsai-geopoliticsrecursive-self-improvementsuperintelligenceworkforce-dynamicsai-bubblesovereign-wealth-funds
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Recursive self-improvementTeacher-student distillationOrganizational absorption capacitySuperintelligenceAI regulatory risk
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ai-regulationai-bubble
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2026-05-27-22026-04-03-22026-03-13-w32026-04-10-12026-03-08-12026-04-12-32026-04-05-12026-05-01-32026-03-30-32026-04-17-w3
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VentureBeat · 2026-10-15 2026-10-16-w1

NVIDIA's new, open Nemotron 3.5 Super VL with post-training beats Claude Opus 5, GPT-6.1 Sol on specialized task benchmarks

Super VL, a 120B open base, went from about 28% to about 72% on medical claims after post-training, against about 38% for Claude Opus 5. The base model sat below Opus 5, so the gain came from the customer's data and tuning budget, and the comparison is tuned against untuned. Its Artificial Analysis index of 26 trails GLM-5.3-Flash (42) and Qwen3.8-Flash-Next (40), which says the weights are not what wins. For builders the buying decision moves from which model to who owns the evaluation set and the post-training pipeline. In the week's argument this is the lightest of Nvidia's levers: it gives away the part that is commoditizing and keeps buyers building on its stack, with Bolt E4B due Oct 23 as the next test.

# tags
benchmarkedge-aienterprise-aifine-tuninghugging-facehuggingfaceinference-economicslocal-llmmodel-licensingnvidiaopen-modelspost-trainingvendor-claimsventurebeat
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Ecosystem lock-in through integration breadthEnterprise AI adoptionOpen Source StrategyTeacher-student distillationVertical Integration
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inference-economics
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2026-10-15-32026-10-16-12026-10-16-22026-03-17-32026-03-13-12026-03-15-12026-03-14-32026-03-10-12026-05-27-32026-04-17-w22026-03-17-22026-05-07-12026-03-14-1
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VentureBeat 2026-10-15-3

NVIDIA's new, open Nemotron 3.5 Super VL with post-training beats Claude Opus 5, GPT-6.1 Sol on specialized task benchmarks

NVIDIA's Super VL, a 120B open base, went from about 28% to about 72% on medical claims after post-training, against about 38% for Claude Opus 5. The base model sat below Opus 5, so the gain came from the customer's data and tuning budget, and the comparison is tuned against untuned. Set beside Meta's Muse Spark Open, it suggests the weights are the commodity and the evaluation set and training pipeline are what a buyer should own.

# tags
nvidiaopen-modelspost-trainingfine-tuningenterprise-aivendor-claimsbenchmarkventurebeatmodel-licensinghugging-facehuggingfaceedge-ailocal-llminference-economics
◆ entities
Teacher-student distillationOpen Source StrategyEcosystem lock-in through integration breadthVertical IntegrationEnterprise AI adoption
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inference-economics
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2026-03-17-32026-03-13-12026-03-15-12026-03-14-32026-03-10-12026-05-27-32026-04-17-w22026-03-17-22026-05-07-12026-03-14-1
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