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.

IBM Research published the Open Agent Leaderboard on Hugging Face to evaluate agents across language understanding, tool use, and multi-step reasoning tasks; the post does not disclose dataset size, model scores, or the evaluation date.

EvolveR lets agents distill reusable experience from successful and failed trajectories, maintain a scored experience library, and train retrieval behavior with GRPO; the paper reports the best average performance on seven complex QA benchmarks using Qwen2.5-3B and 7B.

Huawei GTS proposed EDCO, a dynamic curriculum method that selects fine-tuning samples by inference entropy; prefix entropy estimation cuts per-sample scoring time from 2.24 seconds to 0.37 seconds.

An independent author trained TIME with QLoRA on Qwen3 4B/8B/14B/32B to trigger short mid-response reasoning when context changes; the post says datasets, notebooks, scripts, curriculum, and TIMEBench are public, with 24GB VRAM enough for training up to 14B.

MiroMindAI released the MiroThinker-1.7-deepresearch and mini APIs, with the mini version using 30B total parameters and 3B active parameters, weights on HuggingFace, and context management based on sliding window K=5 plus episode restarts.

Mustafa Suleyman predicts AI will reach human-level performance within 18 months and automate most professional tasks, including accounting, law, marketing, and project management.

A Reddit user tested DeepSeek V4 on 45k, 180k, and 520k-token codebases and found 150k-250k tokens best for coding work. Past 300k tokens, line-number precision degraded; at 520k, outputs shifted toward architecture summaries and skipped implementation details.

C_Coffie published 55 local inference benchmark runs across Strix Halo, RTX 3090, RTX 5070, five backends, and 0.35B to 35B-A3B models; RTX 5070 beats RTX 3090 on models fitting 12GiB, while RTX 3090 leads in the 14–31B band that exceeds 12GiB but fits 24GiB.

Dwarkesh Patel argues that intelligence and power are being conflated: current AI systems improve through economically valuable tasks such as coding, while real-world power depends more on authority, trust, and large-scale cooperation than isolated strategic reasoning.

Dwarkesh argues that RLVR has a short-feedback weakness in scientific theory validation; the post says validation loops can span decades or centuries, and does not disclose experimental results or benchmark numbers.

Eric Jang spent several months implementing AlphaGo from scratch and says that in 2026, training a strong Go AI requires only a few thousand dollars in rented compute rather than DeepMind-scale resources.

AntLingAGI open-sourced Ring-2.6-1T and listed it on OpenRouter with a 75% discount through the end of May; the trillion-scale reasoning model targets agent workflows, including planning, tool use, context maintenance, and complex task execution, using Async RL and IcePop training methods.

Alibaba Health launched the medical AI product Qinglizi for China’s 5 million doctors, with access to ten years of content from 70 BMJ Group journals and an evidence workflow constrained by PICO, GRADE, and review from more than 300 clinical experts.

Orthrus-Qwen3-8B adds a trainable diffusion attention head to a frozen Qwen3-8B backbone, reaches up to 7.8× tokens per forward and about 6× wall-clock speedup on MATH-500, while training 16% of parameters with under 1B tokens over 24 hours on 8×H200 GPUs.

Yann LeCun discussed LLM limitations on the Unsupervised Learning podcast, covering his 2027 forecast, AMI’s bet on world models, his reasons for leaving Meta, and major disagreements with Geoffrey Hinton and Yoshua Bengio over Turing Award-era views.

Eric Jang uses AlphaGo to break down an intelligence system; the post only discloses three mechanisms: search, learning from experience, and self-play.

A developer released the keon/jepa teaching repository with five JEPA variants implemented as standalone PyTorch files, ranging from 160 to 278 lines, depending only on PyTorch and torchvision; the post reports iJEPA runs on CIFAR-10 for 100 epochs and reaches 52.7% linear-probe accuracy, while V-JEPA, C-JEPA, and LeWorldModel use toy or synthetic datasets.

Anthropic released Natural Language Autoencoder to translate Claude activation vectors into text; on Opus 4.6 it reached 60%-80% variance explained, and across 16 evaluations NLA detected unspoken evaluation awareness on 26% of SWE-bench Verified tasks.

Databricks made GPT-5.5 available through AI Unity Gateway for AgentBricks and Agent Supervisor API workflows; on OfficeQA Pro, it became the first model above 50% accuracy and reduced errors by 46% versus GPT-5.4.

xAI connects Grok subscription accounts to Nous Research’s open-source Hermes Agent across all subscription tiers, letting users run Grok 4.3 text chat and reasoning, generate spoken replies with text-to-speech, create images and videos with Grok Imagine, and connect the agent to WhatsApp or Discord.

Anthropic’s Mythos AI helped researchers find two previously unknown macOS kernel vulnerabilities in five days and chain them into a privilege-escalation exploit that bypassed Apple’s memory integrity protection, according to the Wall Street Journal snippet.

The author fine-tuned Qwen 2.5 7B base on self-mined mistake-correction pairs, raising HumanEval from 25/164 to 112/164; Qwen 2.5 14B used 100 pairs and a 95-minute H100 run costing $3.50.

Richard Socher’s new $650 million startup plans to build an AI system that can research and improve itself indefinitely, and the RSS snippet says it will ship products; the post does not disclose the technical mechanism, launch timeline, or product format.

MiroMind researchers released the MOOSE-Star collection with three 7B models and TOMATO-Star, a dataset of 108,717 NCBI papers. MS-IR-7B reaches 54.37% inspiration-retrieval accuracy, uses DeepSeek-R1-Distill-Qwen-7B as its base, runs at about 14GB fp16, and supports llama.cpp, vLLM, and SGLang.

inclusionAI released Ring-2.6-1T, a 1T-parameter reasoning model on Hugging Face; it supports high and xhigh reasoning effort levels, targets agent workflows and long-horizon tasks, and uses Async RL with the IcePop algorithm for reinforcement-learning training stability.

Li Mu’s team released the SenseNova U1 technical report and MoE-based weights; the snippet says it covers architecture and training methods, but the post does not disclose parameter size, license terms, or benchmark results.

MiMo V2.5 Pro placed third on the DesignArena overall leaderboard; its Thinking version rose 8 spots over MiMo-V2.5 and matched Claude Sonnet 4.6 performance on frontend coding tasks.

Recursive Superintelligence, founded by Yuandong Tian and seven other AI researchers, has a 25-person team, $650 million in funding, and a $4.65 billion valuation, with a stated goal to automate evaluation, data filtering, training, post-training, and research-direction selection.

Alibaba DAMO Academy introduced I²B-LPO, an RLVR post-training framework that branches rollouts at high-entropy nodes and filters them with an information-bottleneck self-reward, reporting up to 5.3% accuracy gains and 7.4% semantic-diversity gains on math benchmarks using Qwen2.5-7B and Qwen3-14B.

SenseNova published SenseNova-U1-A3B-MoT on Hugging Face; the post lists A3B MoT, 8B MoT, and 0.4B LoRA weight links, and says the NEO-unify architecture unifies multimodal understanding, reasoning, and generation in one model family.

AIDC-AI released Ovis2.6-80B-A3B, a multimodal MoE model with 80B total parameters and about 3B active parameters at inference, supporting a 64K-token context window and images up to 2880×2880 resolution.

Google Developers describes using ADK to build long-running agents for enterprise workflows lasting days or weeks, such as HR onboarding, with a persistent state machine, persistent session storage, event-driven webhooks, and multi-agent delegation to pause during idle time and resume after restarts without losing context.

The author describes installing OpenAI’s official Codex plugin in Claude Code via the plugin marketplace: add the repository, install the plugin, reload, and configure it, then use it to build a Skill where Claude Code handles reasoning and Codex acts as moderator.

OpenAI released GPT-Realtime-2 alongside Realtime-Translate and Realtime-Whisper, with a 128K context window, five reasoning-effort levels, and API pricing of $32 per million input tokens and $64 per million output tokens.

Shanghai AI Lab, Shanghai Jiao Tong University, and USTC tested Long-CoT SFT on Qwen3-14B-Base and found that cross-domain performance recovered and improved after 8 epochs, with generalization conditioned on optimization depth, data quality and structure, and base-model capability.