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TOPIC · ENTITY #3706

o3

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RESEARCH · 1 SOURCE · WIRED AI

Thompson study: OpenAI GPT‑5 series and other models increasingly solve theoretical problems across sciences

A study by Neil Thompson with Gabriel Manso and Claudio Mayrink Verdun tested OpenAI models (o1, o3, GPT‑5, GPT‑5.1, GPT‑5.4, GPT‑5.5) on theory problems drawn from papers posted Dec 2025–May 2026; models were blocked from internet access and many ground‑truth solutions were published after the models' training cutoffs. The best models' success rate on problems in probability, statistics theory, economic theory, high‑energy theory, gravitation and cosmology, and quantum physics rose from roughly 2% in mid‑2024 to about 35% by mid‑2026.

8.0

RESEARCH · 1 SOURCE · The Decoder

Epoch AI: cost to reach fixed benchmark scores fell ~47% per quarter; MIT finds smaller algorithmic gains (~3x/yr)

Epoch AI reports that market prices to achieve fixed scores on five AI benchmarks fell about 47% per quarter (≈13x/year) since 2023, citing examples like OpenAI's o3 vs GPT-5.6; the group warns its sample is limited and measures market price per benchmark score rather than pure algorithmic progress. MIT researchers (Hans Gundlach et al.) using broader model pricing data find 5–10x annual declines in benchmark cost but estimate actual algorithmic efficiency gains of ~3x/year after removing hardware and competition effects, and note some improvements come from higher test‑time compute rather than efficiency.

8.0

RESEARCH · 1 SOURCE · arXiv cs.AI

arXiv paper introduces SAFE benchmark to test whether frontier models seek safety evidence before acting

The paper (arXiv:2609.17865v1) introduces SAFE, a controlled benchmark where models decide whether to retrieve optional safety-relevant evidence that varies in cost, probability, severity, and presentation. Evaluating GPT-5.5, o3, Claude Opus 4.8, and Claude Sonnet 4.6, the authors find distinct evidence-acquisition policies (Opus inspects by default, o3 skips most, GPT-5.5 and Sonnet intermediate), strong sensitivity to severity and retrieval cost, weaker sensitivity to probability, and a mismatch between stated rationales and actual causal influences.

7.0