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- NeurIPS 2026 paper reduces a dynamical-systems foundation model to its minimal parts, per a Reddit post
A post on r/MachineLearning shares a NeurIPS 2026 paper that strips a dynamical-systems foundation model down to the minimal ingredients needed for zero-shot reconstruction of long-term statistical and geometric properties.
- Anthropic details Claude text watermark research
Anthropic published research on Claude text watermarking on its site.
- Anthropic details Claude-discovered novel enzyme system
Anthropic published 'Claude discovers novel enzyme system' on its site, per the research page.
- Functional Gradient Descent with Adaptive Representations paper discussed
A paper on functional gradient descent with adaptive representations was discussed on r/MachineLearning.
- OpenAI works to fix its math breakthrough announcements, per The Verge
The Verge reports that in a chaotic few months OpenAI has made impressive mathematics breakthroughs while repeatedly mishandling the announcements, and is now trying to do better.
- ClashRoyaleAI: open-source deterministic Clash Royale simulator for RL
An open-source project released ClashRoyaleAI, a deterministic Clash Royale simulator for reinforcement learning with recurrent PPO and lookahead search.
- Google Research introduces AI video co-director with 4 agentic frameworks, per MarkTechPost
MarkTechPost reports Google Research introduced an AI video co-director for long-form video generation: four agentic frameworks that turn short clips into coherent minutes-long stories, targeting identity drift and cascading errors.
- OpenAI's Boris Power says 80% to 90% of its research targets GPT 7 and beyond, per The Decoder
The Decoder reports that Boris Power, OpenAI's head of applied research, said 80% to 90% of the company's research goes toward GPT 7, GPT 8 and beyond because most of the value comes from new generations. He described within-generation gains, such as GPT 5.1 to 5.2, as coming from specialized training data and deliberate short-term bets.
- AI was used in 96.5% of tasks building Atria Dawn Preview, but humans made the calls, per The Decoder
The Decoder reports on a study, by a team including Fudan University researchers, of 700+ task logs from 56 participants who developed the 744B MoE agent model Atria Dawn Preview. AI was used in 96.5% of tasks and 151 of 455 completed AI-assisted tasks were rated impossible without it, though the team cautions that a rising ratio of agent actions to human inputs does not mean more autonomy.
- Stanford and Caltech's HomeBody has GPT-6 Astra drive a Unitree G1 robot in an unfamiliar kitchen, per The Decoder
The Decoder reports that HomeBody drops the usual trained control layer and lets a swappable vision-language model, here GPT-6 Astra, call a skill library directly so a Unitree G1 can navigate, tidy up and fetch items in a kitchen it has not seen. Reported limits include Astra's latency, overheating finger servos and high compute cost; the code is on GitHub.
- Tauon optimizer claimed to outperform Muon on GPT-Mini
A Reddit post introduces Tauon, a new optimizer claimed to outperform Muon on GPT-Mini with lower loss and about 8.5% faster step time.