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AI Economics

Frontier vs open-source AI gap analysis and metrics

Research tracking divergence between frontier and open-source AI capabilities, token cost decline rates, throughput improvements, and compute spending patterns over time to quantify competitive positioning.

5 posts · First seen 2026-02-23 · Last activity 2026-02-23
TimeAuthorPost
2026-02-23T21:38 @jeremyphoward An enormous amount of the work in all commercial AI labs comes from open source software. E.g the original LLM, ULMFiT, was open source, and led to the creation of GPT at OpenAI, where the Anthropic founding team was working at the time. Innovation happens through open research https://t.co/OGcLLYg0IY
2026-02-23T21:21 @emollick RT @tensor_rotator: I can finally publicly state one reason I’ve not been bullish on open source catching up and overtaking the frontier la…
2026-02-23T19:18 @chrisbarber things that could be interesting for epoch to do: - has the gap between frontier and open source been growing or shrinking over time - what is the true token cost decline rate - tok/s over time for same intelligence - context length forecasting - compute spend over time vs gross profit over time - something digging into what Dario said on Dwarkesh about buying compute vs avoiding bankruptcy - anything that digs into whether rl is generalizing and if so where and how far and if that’s changing over time etc what would you emphasize or add
2026-02-23T19:02 @mitsuhiko Distillation is great! We need more of it. https://t.co/FwGTRhW4xx
2026-02-23T18:30 @chatgpt21 @AnthropicAI @TheAhmadOsman all the open source models are down stream of Claude 😭 ↩ reply parent
@jeremyphoward 2026-02-23T21:38
@emollick 2026-02-23T21:21
@chrisbarber 2026-02-23T19:18
@mitsuhiko 2026-02-23T19:02
@chatgpt21 2026-02-23T18:30
↩ reply parent

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