Reasoning

Timothy Gowers tested ChatGPT 5.5 Pro on additive number theory problems, where it produced an optimal quadratic upper-bound construction in 17 minutes 5 seconds, then generated a LaTeX preprint in 47 minutes; the article says arXiv rejects AI-generated content, so the result remains on Gowers’s blog.

A five-week experiment tested about 1,400 daily work tasks, where local 35B models such as Qwen 3.6 35B handled about 50% and averaged 2.8-second responses, 2.1 times faster than Claude Opus 4.5, while the cloud model still led complex reasoning by about 20%.

A Science study reports that OpenAI o1 reached a 67% correct or near-correct diagnosis rate on real emergency department data, exceeding doctors at 50-55%, but the study did not cover long-term inpatient data or imaging diagnosis.

MachinaCheck runs Qwen 2.5 7B locally on AMD MI300X to analyze STEP files for CNC manufacturability, reducing drawing review for quote analysis from 30–60 minutes to 30 seconds while using 192GB HBM3 to keep customer design data on-premises.

Richard Sutton and coauthors proposed Intentional Updates, which derive the step size from the desired output change; Intentional AC approached SAC on MuJoCo under batch=1 streaming training without replay, while each update used about 1/140 of SAC’s FLOPs.

Ted Xiao divides nearly a decade of robot learning into three eras: Google’s team trained RT-1 on 87,000 teleoperation trajectories, then adapted 5B to 55B VLMs into VLA policies for RT-2.

East China Normal University and Fudan University researchers proposed Next-ToBE, a training objective that keeps standard autoregressive inference while adding a soft target over future-token windows, and the article reports the method ranked best in 35 of 36 experiments across Qwen2.5-Math-1.5B, Qwen2.5-Math-7B, and Llama3.1-8B-Instruct.

NVIDIA AI released Star Elastic, a single checkpoint that can zero-shot slice 30B, 23B, and 12B reasoning models in BF16, FP8, and NVFP4; when the 23B submodel handles thinking and the 30B model handles final answers, reported accuracy rises 16% and latency drops 1.9× on AIME-2025, GPQA, LiveCodeBench v5, and MMLU-Pro.

Anthropic’s patent describes the Computer Use training pipeline: it captures user actions, uses a transformer to infer action intent, and applies a stronger model for synthetic expansion, turning raw UI operations into reasoning data.

Anbeeld released BeeLlama.cpp, a llama.cpp fork that runs Qwen 3.6 27B Q5 with 200k context and vision on a single RTX 3090 or 4090; the title claims 2–3x faster than baseline and a 135 tps peak.

Baidu released ERNIE 5.1 with total parameters reduced to about one third of the original scale, active parameters to about one half, and pretraining cost to about 6% of same-scale models; the model is available on the ERNIE platform and Baidu AI Studio.

Baidu released ERNIE 5.1, saying it builds on ERNIE 5.0 pretraining and improves search, reasoning, knowledge QA, creative writing, and agent capabilities, with pretraining cost at about 6% of comparable models.

Google DeepMind released AI Co-Mathematician, an asynchronous agent workspace for math research, and answered 23 of 48 private FrontierMath Tier 4 problems, scoring 48% under 48-hour, no-token-limit conditions versus GPT-5.5 Pro at 39.6%.

DeepSeek is negotiating a $7.3 billion funding round at an estimated $51.5 billion valuation; Liang Wenfeng reportedly plans to contribute 40%, while Tencent and China’s RMB 60 billion national AI fund are also in talks.

OpenAI researcher Jiayi Weng proposes Heuristic Learning: codex gpt-5.4 reached a perfect 864 score on Breakout and generated 342 search trajectories across Atari 57, with updates applied to code, tests, replays, and memory rather than neural-network weights.

The speaker presented a physical AGI roadmap with six named components: video world models, WAM, EgoScale, dexterity scaling laws, physical reinforcement learning, and DreamDojo; the snippet also mentions a 2016 OpenAI DGX-1 signing story with Jensen and Elon.

RadixArk announced a $100 million seed round on May 5 at a $400 million post-money valuation, while its SGLang inference project has 27K+ GitHub stars and deployments across 400K+ GPUs.

BAIR’s post describes adaptive parallel reasoning, where ThreadWeaver and Multiverse dynamically control parallel threads for math and code reasoning; the RSS snippet does not disclose benchmark scores, latency reductions, or reproducible settings.

OpenAI released GPT-Realtime-2, GPT-Realtime-Translate, and GPT-Realtime-Whisper in the Realtime API, with GPT-Realtime-2 expanding context from 32K to 128K and scoring 96.6% on Artificial Analysis Big Bench Audio.

UC Santa Barbara and Apple researchers introduced LenVM, which models remaining generation length as a token-level value function; Qwen2.5-3B with a 1.5B LenVM scored 62.6 on LIFEBench length control, above GPT-5.4 at 37.4 and Claude-Opus-4-6 at 35.5.