Reasoning

The title says DeepSeek’s founder declared an AGI goal and that a $10 billion funding round is advancing; the post does not disclose the founder’s statement, financing terms, investors, or timeline.

Meta AI and the Chinese University of Hong Kong proposed ATLAS, a visual reasoning method that uses one Functional Token to connect Agentic and Latent Visual Reasoning, with ATLAS-178K, a two-stage SFT+RL pipeline, and LA-GRPO to train sparse visual-operation tokens.

An OpenAI general-purpose reasoning model refuted Erdős’s 1946 unit distance conjecture in the plane; the post says the model was not specially trained for mathematics, and Tim Gowers said he would recommend it to Annals of Mathematics.

NVIDIA won four COMPUTEX 2026 Best Choice Awards for Vera Rubin NVL72, Jetson Thor, and Alpamayo; Vera Rubin NVL72 connects 36 Vera CPUs and 72 Rubin GPUs, and NVIDIA says it delivers up to 10x higher inference performance per watt and 10x lower cost per token.

Sapientinc released HRM-Text 1B Base and its training code, and the paper claims competitive performance against 2–7B open models while using 100–900x fewer training tokens and 96–432x less estimated compute, with training on 16 H100 GPUs taking about 46 hours and costing about $1,472.

OpenAI said an internal general-purpose reasoning model disproved the 1946 Erdős planar unit distance problem by finding a new family of constructions; the reasoning summary reportedly spans about 125 pages, while outside observers speculate the run used under 32 hours or under $1,000.

An OpenAI AI model solved the plane unit distance problem proposed in 1946, using Golod-Shafarevich theory to produce a family of more efficient constructions.

OpenAI says its reasoning model disproved a geometry conjecture unsolved since 1946, and the snippet says mathematicians who challenged its previous claim now back it; the post does not disclose the model name, proof details, or verification process.

The chat group daily says Karpathy joined Anthropic's pretraining team, and cites Stainless shutting down hosted services after acquisition plus Google I/O announcing Gemini 3.5 Flash and a $100 subscription tier.

An OpenAI model solved the 80-year-old unit distance problem and disproved a major conjecture in discrete geometry; the post does not disclose the model name, proof mechanism, or reproducibility conditions.

Google launched an AI search box based on Gemini 3.5, combining AI Overviews and AI Mode into one AI search experience that supports multimodal multi-turn queries across text, images, files, and video, with global availability on desktop and mobile.

Google launched Gemini Omni video generation for global AI Plus, Pro, and Ultra subscribers, integrating it with Gemini app, Google Flow, and YouTube Shorts, while the RSS snippet says the model combines intuitive physical reasoning with Gemini’s historical, scientific, and cultural knowledge.

Google AI Developers announced the Gemini 3.5 model family, saying it combines intelligence with action capabilities; the post does not disclose parameters, benchmarks, pricing, availability, or context window details.

Google showed a redesigned Search box at I/O 2026, using Gemini 3.5 Flash to connect AI Overviews with AI Mode; the RSS snippet says natural-language queries will reliably show AI Overviews, but the post does not disclose rollout timing.

Google released Gemini 3.5 Flash and calls it its best model so far for fast, efficient task completion. The post does not disclose pricing, context window size, benchmark scores, or API availability conditions.

Andrej Karpathy joined Anthropic’s pre-training team, which runs large-scale training for Claude’s core knowledge and capabilities; the RSS snippet does not disclose his title, reporting line, or start date.

Andrej Karpathy has joined Anthropic to return to frontline LLM research; the post identifies him as a former OpenAI core team member and Tesla Autopilot architect, but does not disclose his team, title, or specific research projects.

Sapient Intelligence released HRM-Text 1B, a 1B-parameter model trained from scratch on 16 GPUs for 1.9 days with 40B tokens and a reported ~$1,000 budget; its self-reported chart shows MATH 56.2 and DROP 82.2, while independent evaluation remains pending.

The chat group daily says AI21 Labs cut 60% of staff and stopped selling model access, and cites a University of Waterloo paper where GPT-5.4 accuracy dropped from 100% to 23% after false peer-consensus injection; the snippet also mentions Meta layoff talk at 10%, but does not disclose source details or confirmation conditions.

JD and CAS IIE released three Self-Taught RLVR papers covering RLSD, NPO, and CoPD; RLSD reports that 200 training steps on Qwen3-VL-8B-Instruct exceed GRPO at 400 steps across 8 benchmarks.