Hivemind released continuous learning for AI coding agents, collecting trajectories from Claude Code, Codex, Cursor, Hermes, and Pi, converting them into reusable skills stored in users’ cloud storage, with SkillOpt matching or leading all 52 test settings.

OpenBMB released the VoxCPM2 technical report, covering a 2B-parameter speech generation model trained on more than 2 million hours of multilingual speech data, with support for 30 languages and 9 Chinese dialects.

Google DeepMind published results from a pre-registered randomized controlled trial in Sierra Leone. Students using Guided Learning gained 0.258 standard deviations in math over the control group, equal to roughly 1.2 to 1.7 years of normal learning progress in eight weeks.

City University and Kuaishou Kling proposed VLM-as-Teacher, which uses VLM feedback to optimize VGM LoRA at test time, reporting a 16.7-point average gain and raising VBVR-Bench from 0.666 to 0.781.

Coinbase, Lindy, Harvey, and Cursor shifted workloads to cheaper models; Harvey reported Kimi 2.6 reached a 15% all-pass rate on Legal Agent Benchmark, versus Opus at 14%, with 100 tasks costing $84 versus $954.

Thousand Token Wood v2 uses four small models from different labs to drive agents in a financial simulation game, with vLLM 0.22.1’s CUDA toolkit dependency identified as the main serving friction, while a fine-tuned 0.5B Qwen reached 0% self-trading and 100% valid quotes.

Google released the Colab CLI, which lets developers and AI agents connect local terminals to remote Colab runtimes, request high-performance GPUs, run local Python scripts remotely, and retrieve artifacts such as logs or fine-tuned Gemma 3 adapters.

General Instinct open-sourced InstinctRazor, compressing Qwen3.5-122B-A10B from a roughly 245GB BF16 MoE model into a 48GiB GGUF, with a small-GPU mode that streams experts from system RAM and uses about 7.6–8GB peak VRAM at an 8k context window.

Xinzhiyuan cites a Yann Dubois interview saying OpenAI crossed a reliability threshold around last December, while Anthropic’s internal data says per-person quarterly code contribution reached 8× the Q1 2024 level by Q2 2026.

Microsoft announced seven in-house AI models at Build 2026, including its first reasoning model, one new tuning method, and one autonomous background AI agent; the RSS snippet does not disclose model names, benchmarks, or release dates.

The UK CMA requires Google to let website owners exclude content from AI Search features, including AI Overviews, and prevent that content from being used for fine-tuning Google’s AI models.

Junpeng Zhang and coauthors argue that SFT on highly homogeneous data has an effective window of only hundreds to about 1,000 training steps, and their interaction-based warning signal detects overfitting before loss gaps appear, saving roughly 30%–50% of training compute.

ReinforcedKnowledge analyzes ByteDance’s verl RLHF loop, covering DataProto plus rollout, reward, advantage, and update paths. The author stopped a private fork because near-daily upstream changes made sync cost exceed refactoring work, and describes an NCCL hang fixed on one node by setting NCCL_SOCKET_IFNAME=lo.

NVIDIA Cosmos 3 ranked first in Artificial Analysis’s open-weight text-to-image and image-to-video categories, with 16B Nano and 64B Super variants, and the release includes weights, code, curated datasets, and fine-tuning recipes under the OpenMDW 1.1 license.

OpenBMB, Tsinghua NLP, and Modelbest released two UltraData open datasets: Ultra-FineWeb-L3 contains 600B+ tokens, including 400B+ English and 200B+ Chinese tokens, while UltraData-SFT-2605 contains 15M+ SFT samples with thinking and non-thinking labels.

The author trained Mamba-Titan-1.4B-Reasoning on a 12GB RTX 3060: a frozen 1.4B Mamba-1 backbone with 8 trainable MoE arms, 2.54B total parameters, Top-2 routing at layers 24/25, and about 50% math accuracy.

Fudan University and Tongyi Lab introduced ToolCUA-8B, which reaches 46.85% accuracy on OSWorld-MCP after training with about 4k synthetic tools and 180k interleaved GUI-Tool trajectory steps.

CUHK and collaborators introduced Pion, an optimizer that preserves weight singular values through orthogonal equivalence transformations, and reported that it kept a 60M normalization-free LLaMA-like model stable for 9.6B training tokens while AdamW and Muon collapsed with NaNs.

FaceMind tested 100 languages and four core tasks, finding that, with semantics unchanged, prompts or fine-tuning text using higher-frequency expressions from pretraining data improves large language model performance.

FaceMind links low-frequency token degradation to two papers: SLoW appeared at EMNLP 2025, Adam's Law was accepted as an ACL 2026 Oral, and high-frequency rewriting raised DeepSeek-V3 math accuracy from 63.55% to 71.54%.

QbitAI says DeepSeek V4 validated Ascend chip-model co-design, with CANN open-sourcing 65 repositories and supporting day-zero adaptation for more than 70 mainstream models, while AIGCode reported 65% MFU in MoE pretraining on Ascend.

X Square Robot open sourced Wall-OSS-0.5, a VLA model whose 400k pretraining checkpoint scored above 80 on 4 of 17 real-robot zero-shot tasks, with weights, code, training recipe, ablations, and a DMuon optimizer implementation released.

NVIDIA’s research team open-sourced Polar, an agent reinforcement learning framework that connects GRPO training at the model API boundary without rewriting Codex CLI, Claude Code, Qwen Code, or Pi; on Qwen3.5-4B, Polar raised Codex pass@1 on SWE-Bench Verified from 3.8% to 26.4%, while prefix_merging cut training steps from 1,185 to 218.

OwnerByDane released a 103.1B-token Usenet corpus covering 1980–2013, 408M posts, and 18,347 newsgroups, with free 5K-post-per-hierarchy samples and full-corpus licensing available.

Mistral 收购 Emmi AI，以推进面向工业工程的 Physics AI 基础研究，重点覆盖航空航天、汽车、半导体和能源等行业。其已发布成果包括 AB-UPT，可在单张 GPU 上处理 9M 表面和 140M 体积网格的原始几何数据而无需重新划分网格，以及面向大型多物理过程的端到端深度学习代理模型 NeuralDEM。

AMD and Penn State pretrained Llama 3.1-8B with MXFP4 on MI355X native FP4 hardware, achieving 9-10% end-to-end speedup over an FP8 baseline, while the paper identifies Wgrad quantization as the bottleneck that raises token overhead to 26-27% without deterministic Hadamard stabilization.

ModelBest, Tsinghua University, and OpenBMB open-sourced ForgeTrain, described as the first production-grade LLM training framework written entirely by AI with zero human code, and ModelBest used it to pretrain MiniCPM5-1B on Huawei Ascend chips.

Hugging Face merged TRL PR 5417 for delta weight sync, sending only changed weights as sparse safetensors via a Hugging Face Bucket; on Qwen3-0.6B, the per-step payload falls from 1.2GB to 20–35MB.

OpenSenseNova released the full SenseNova-U1 training code on GitHub under Apache-2.0, supporting an 8B dense model, an A3B MoE architecture, and multimodal tasks such as text-to-image generation, image editing, interleaved generation, and text-visual understanding.

Elon Musk said the 1.5T-parameter Grok V9-Medium has finished training, will enter reinforcement learning in a few days, and is planned for release in two to three weeks. Grok Build supports up to 8 parallel sub-agents, a 256K-token context window, Plan Mode, Arena Mode, MCP, and ACP.

A lawyer runs a local legal-drafting pipeline across 16 GPUs, with Qwen3.5-122B-A10B reaching about 50 tok/s on four V100s, while a verifier blocks ungrounded citations, dates, and Bates numbers before any final document is used.

The Financial Times used Heretic to remove guardrails from Meta Llama 3.3 in under 10 minutes; creator Philipp Emanuel Weidmann said the tool has created over 3,500 decensored models and those modified systems have reached 13 million downloads.

OpenBMB released BitCPM-CANN, a 1.58-bit QAT training stack on Ascend NPU with 0.5B, 1B, 3B, and 8B models trained from scratch, where the 1B to 8B variants retain 95.7%–97.2% of full-precision MiniCPM4 performance across 11 benchmarks.

Meta is pushing some post-layoff employees into new roles: some engineering managers are returning to IC work, while some Infra and AI engineers are being reassigned to data labeling; the article cites a manager-to-report ratio shift from 1:8 to 1:50 and says Meta holds a 49% stake in Scale AI.

Mistral AI said it has reached a definitive agreement to acquire Emmi AI, a physics AI pioneer, to strengthen its position as an AI transformation partner for industrial companies. Austria-based Emmi AI works on physics AI and large engineering models that speed up engineering workflows, replace multi-day computations with real-time simulation and build digital twins. Emmi's co-founders and more than 30 researchers and engineers will join Mistral's Science and Applied AI teams in May.

USTC researchers released MMEVOKE and KORE: MMEVOKE contains 9,422 samples across 159 subcategories, while KORE uses knowledge-tree augmentation and null-space constrained fine-tuning to reduce catastrophic forgetting during multimodal knowledge injection.

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.

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.

Sierra raised $950 million in May at a valuation above $15 billion, while Lingxi says it reached scaled profitability and positive cash flow in 2025; the article uses both companies to frame RaaS as charging for measurable business outcomes rather than tokens or subscriptions.

Cursor released Composer 2.5, claiming a 10x efficiency gain at comparable capability, with larger training scale, more complex reinforcement-learning environments, and a text-feedback mechanism.