CompanyAnthropic8 recent entries12 Oct 2026LongHarness: Advancing Agentic Reasoning over 100M-Token Corpora via Stateful Evidence ManagementarXiv:2610.13075v1 Announce Type: new Abstract: Corpus-level long-context reasoning requires agents to acquire and integrate evidence across document collections that exceed their context windows. Exi→12 Oct 2026Introducing DigitalOcean Signals and Simulations: see how your agents and models really behave in production, then test the fix before it shipsYou ship an agent. It mostly works. Then the feedback loop becomes a support ticket: a user got the wrong answer, a tool call looped four times, a refund went out that shouldn’t have. Standard observa
CompanyOpenAI8 recent entries11 Oct 2026Now you can grow Bonsai on your potatoNo more excuses for GPU-poor folks not to start LLMing! Full 27B-class reasoning in ternary transformer weights, for llama.cpp (CUDA, Metal, CPU) ~9.3x smaller than FP16 (ideal) | 98.2% of FP16 intell→11 Oct 2026Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less 'two groups of peo…Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less 'two groups of people speaking past each other' and more a sharp funnel. - Nap→12 Oct 2026Yes, and there is a case to be made that OpenAI and Anthropic will do the best job of figuring out how to optimize AI cost/intelligence with…Yes, and there is a case to be made that OpenAI and Anthropic will do the best job of figuring out how to optimize AI cost/intelligence with combinations of agents of different ability levels that hav→12 Oct 2026Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal cus…Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal custom models, driven by 10 years of experience training top mo→12 Oct 2026Meta says it plans to power its Muse AI agent with Wonder, starting with subscribers, and will develop specialized models it 'can bring to everyone using Muse' (Robert Hart/The Verge)Robert Hart / The Verge: Meta says it plans to power its Muse AI agent with Wonder, starting with subscribers, and will develop specialized models it “can bring to everyone using Muse” — Meta says the→12 Oct 2026Meta introduces Muse Wonder and Muse Wonder Full, saying they deliver state-of-the-art performance on personal and professional agentic tasks (Meta AI Research)Meta AI Research: Meta introduces Muse Wonder and Muse Wonder Full, saying they deliver state-of-the-art performance on personal and professional agentic tasks — Fourteen months ago, we began a ground→12 Oct 2026I tested GPT-5.6 and GPT-6 with Medium → Instant → Medium. Both models failed on Instant, both succeeded on Medium. Here's what I found.I've been investigating some serious ChatGPT reliability issues over the past several days, and my latest tests revealed something particularly interesting: Both GPT-5.6 and GPT-6 showed problems unde→13 Oct 2026Grok @Bot rocksGrok @Bot rocks I've been using Grok @Bot as my daily driver for a few weeks now and: - it has replaced 100% of my search-like queries on chatgpt / claude - it has replaced 100% of my Hermes usage & a
CompanyGoogle8 recent entries10 Oct 2026Benefits of using bigger models than Qwen 3.8 flash next?I recently started using local LLM for mostly coding tasks for my personal projects. I also have found local models responding much better for topics such as health, fitness, ergonomics etc. compared →10 Oct 2026AI solved open mathematical problems. But the biggest surprise came afterwards. A team at Google DeepMind has used AI to resolve 9 open Erdő…AI solved open mathematical problems. But the biggest surprise came afterwards. A team at Google DeepMind has used AI to resolve 9 open Erdős problems, including questions that had remained unsolved f→12 Oct 2026With only ~$1,000 of training compute, we trained 𝗳𝗿𝗼𝗺 𝘀𝗰𝗿𝗮𝘁𝗰𝗵 a 1.7B coding agent that beats Claude 3 Opus and GPT-4o on SWE-ben…With only ~$1,000 of training compute, we trained 𝗳𝗿𝗼𝗺 𝘀𝗰𝗿𝗮𝘁𝗰𝗵 a 1.7B coding agent that beats Claude 3 Opus and GPT-4o on SWE-bench Verified 🤯 At 25.5% pass@1, it sets a new record for nanoswe, our op→12 Oct 2026Trusted Data Apps for the Agentic Data Cloud, powered by LookerAs a business intelligence user, this probably sounds familiar: Most dashboards only provide you with a standardized canvas and a fixed library of charts, and the “analysis” consists of a CSV export t→12 Oct 2026People Making Conversation: Evaluating How Naturally Speech Models ConversearXiv:2610.12802v1 Announce Type: new Abstract: A conversational speech model has to decide, at every pause, whether to speak. Existing evaluations test boundary detection, policy adherence, or aggreg→12 Oct 2026Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal cus…Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal custom models, driven by 10 years of experience training top mo→12 Oct 2026Introducing DigitalOcean Signals and Simulations: see how your agents and models really behave in production, then test the fix before it shipsYou ship an agent. It mostly works. Then the feedback loop becomes a support ticket: a user got the wrong answer, a tool call looped four times, a refund went out that shouldn’t have. Standard observa→12 Oct 2026APEX-Harm: Evaluating Agent Safety in Shared Professional WorkspacesarXiv:2610.13623v1 Announce Type: cross Abstract: Professional agents increasingly work through command-line interfaces and multiple tools over shared workspaces containing files, messages, and busine
CompanyMeta8 recent entries12 Oct 2026Meta introduces Muse Wonder and Muse Wonder Full, saying they deliver state-of-the-art performance on personal and professional agentic tasks (Meta AI Research)Meta AI Research: Meta introduces Muse Wonder and Muse Wonder Full, saying they deliver state-of-the-art performance on personal and professional agentic tasks — Fourteen months ago, we began a ground→12 Oct 2026Meta has some Wonder Full new AI modelsMeta is making up for lost time in the AI race. After launching Muse Spark, the first model from its revamped Superintelligence Labs division, and buzzy AI agent Muse, it's now launching two new model→12 Oct 2026MENTOR: Learning from Failure with On-Policy Pedagogical InterventionarXiv:2610.13594v1 Announce Type: new Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) is a key driver for Large Reasoning Models, but it is vulnerable to 'zero-reward collapse', a trai→12 Oct 2026LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection ChallengearXiv:2506.09956v2 Announce Type: replace-cross Abstract: Indirect prompt injection attacks exploit a fundamental weakness of LLMs: executing unauthorized tasks from untrusted sources. Despite the pra→12 Oct 2026Let Large Language Models Judge Each Other: Multi-Agent Peer-Reviewed Reasoning for Medical Question AnsweringarXiv:2606.15419v2 Announce Type: replace-cross Abstract: Objective: To enhance the accuracy, interpretability, and robustness of large language models (LLMs) in medical question answering (MedQA). Me→12 Oct 2026In-Context Learning for System Identification: Probabilistic Formulation, Long-Sequence Handling, and Benchmark ValidationarXiv:2610.13411v1 Announce Type: cross Abstract: Traditional system identification typically involves two steps: initially, training data is processed to estimate a model of the system of interest; t→12 Oct 2026Hyper Algorithm Design Agent: Evolving Learnable Optimizer from ZeroarXiv:2609.35328v2 Announce Type: replace Abstract: Meta-Black-Box Optimization (MetaBBO) is one of the highlights in the recent AI for Optimization trend. This paradigm's bi-level workflow leverages →12 Oct 2026Byzantine-Resilient Federated Large Language Model via Hypergraph Message PassingarXiv:2610.12711v1 Announce Type: new Abstract: Federated Large Language Models (FedLLMs) are promising to deliver privacy-preserving, collaborative intelligence. The decentralized training process is
CompanyMistral8 recent entries7 Oct 2026The Ballon d'Or, legal division: On Harvey's Legal Agent Benchmark (LAB), Mistral Large 4 is the #1 oss model.MistralAI announced that its model **Mistral Large 4** ranked as the #1 open‑source (OSS) model on **Harvey’s Legal Agent Benchmark (LAB)**, an evaluation benchmark for legal AI agents. The tweet post→7 Oct 2026Mistral Large 4 runs general-purpose agents that gather information and produce finished deliverables across complex workflows.Mistral AI introduced **Mistral Large 4** in October 2026 as a general‑purpose agentic model capable of gathering information and producing final deliverables across complex workflows. The launch high→7 Oct 2026Gmail. Google Sheets. Slack. Salesforce. i.e. the four horsemen of Monday. On AutomationBench, Mistral Large 4 took on 657 business workflow…Gmail. Google Sheets. Slack. Salesforce. i.e. the four horsemen of Monday. On AutomationBench, Mistral Large 4 took on 657 business workflows across simulated workplace apps, all four included, finish→8 Oct 2026How Do Agentic LLMs Decide to Call Tools? A Tool-Call Vector Shaped by SuppressionarXiv:2610.09624v1 Announce Type: cross Abstract: Tool calling, invoking external tools on demand, is central to agentic LLMs, yet the mechanism that decides whether a model calls a tool or responds d→8 Oct 2026Document-Level Text Simplification in Estonian Using Large Language ModelsarXiv:2610.10378v1 Announce Type: new Abstract: Document-level text simplification involves transformations that go beyond sentence-internal edits, addressing discourse coherence, anaphora resolution,→9 Oct 2026Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RLarXiv:2607.16204v2 Announce Type: replace Abstract: Recent growth in reinforcement learning (RL) has surfaced a need for diverse, specialized training environments. Hand-curated environments with fixe→12 Oct 2026🇫🇷 Le Chonk joins the sudo L7 leaderboard 🇫🇷 We just added @MistralAI's Mistral Large 4 to sudo L7, our benchmark for staff-level softwa…🇫🇷 Le Chonk joins the sudo L7 leaderboard 🇫🇷 We just added @MistralAI's Mistral Large 4 to sudo L7, our benchmark for staff-level software engineering. Mistral Large 4 scores 13.3%, ahead of Muse Spar→12 Oct 2026Engineering drawings: Mistral Large 4 zooms, inspects, verifies. Until the answer is exact.Mistral AI demonstrated a tooling solution for engineering drawings that employs the **Mistral Large** model across **four zoom levels**, automatically inspecting and verifying plan details until an e
CompanyxAI8 recent entries9 Oct 2026WorldBench: Evaluating LLMs on Three.js Voxel World GenerationarXiv:2610.10622v1 Announce Type: cross Abstract: Large language models can now write complete, interactive 3D worlds as code, but grading those worlds automatically is unreliable. Existing judges tak→9 Oct 2026DGX Monarch - Dual Spark Rendering w/ ComfyUIFor those of you who have been wanting to utilize your dual Spark cluster for image/video gen with ComfyUI - today is your day. I started this personal project back in April of this year, and it’s at →12 Oct 2026Yes, and there is a case to be made that OpenAI and Anthropic will do the best job of figuring out how to optimize AI cost/intelligence with…Yes, and there is a case to be made that OpenAI and Anthropic will do the best job of figuring out how to optimize AI cost/intelligence with combinations of agents of different ability levels that hav→12 Oct 2026People Making Conversation: Evaluating How Naturally Speech Models ConversearXiv:2610.12802v1 Announce Type: new Abstract: A conversational speech model has to decide, at every pause, whether to speak. Existing evaluations test boundary detection, policy adherence, or aggreg→12 Oct 2026Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal cus…Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal custom models, driven by 10 years of experience training top mo→12 Oct 2026🇫🇷 Le Chonk joins the sudo L7 leaderboard 🇫🇷 We just added @MistralAI's Mistral Large 4 to sudo L7, our benchmark for staff-level softwa…🇫🇷 Le Chonk joins the sudo L7 leaderboard 🇫🇷 We just added @MistralAI's Mistral Large 4 to sudo L7, our benchmark for staff-level software engineering. Mistral Large 4 scores 13.3%, ahead of Muse Spar→13 Oct 2026It’s awesomeGeorge Hayworth shared a short message stating that he has started using **Grok Bot** and regards it as the best artificial‑intelligence agent he has used so far. He encourages others to try the bot, →13 Oct 2026Grok @Bot rocksGrok @Bot rocks I've been using Grok @Bot as my daily driver for a few weeks now and: - it has replaced 100% of my search-like queries on chatgpt / claude - it has replaced 100% of my Hermes usage & a
CompanyDeepSeek8 recent entries10 Oct 2026Best small model + setup together with qwen3.8-flash-nexthello, I currently use swift qwen3.8 gsq rco in iq3 xxs in strata. The model is only used for hermes agent. I have 64GB of ram + 32GB R9700 where the model runs on. But I also have an rx7800xt with 16→11 Oct 2026Qwen 3.8 27B Q5 vs Qwen 3.8 Next Q3_S for document analysisI have an app that processes ~500 different documents every day. An agent analyzes them, sorts them, tags them, extracts various legal nuances, creates descriptions, etc. So far I've been using Qwen 3→12 Oct 2026Taking Tokenization off the Host for Agentic LLM ServingarXiv:2610.13325v1 Announce Type: cross Abstract: Agentic workloads resend long contexts that barely change between calls. Prefix caching now skips most of their prefill, yet every request must still →12 Oct 2026Not All Correct Fixes Run Alike: An Empirical Study of Patch Performance in Repository-Level Issue ResolutionarXiv:2610.13563v1 Announce Type: cross Abstract: Repository-level issue-resolution benchmarks such as SWE-bench evaluate submitted patches primarily based on whether they pass the correctness tests, →12 Oct 2026MagicBeanStalk: Escaping the RLVR Zero Advantage Trap with Recursive Data SynthesisarXiv:2610.12659v1 Announce Type: new Abstract: Data-centric scaling of RLVR has focused on collecting or generating verifiable training problems. However, corpus size alone does not determine whether→12 Oct 2026Locate, Judge, Read: Role-Specialized Tool Agents over a Knowledge-Point Index for Open-Domain Multimodal Document QAarXiv:2610.13128v1 Announce Type: new Abstract: Question answering over large heterogeneous document collections requires first finding the right passages and then reading them, yet current retrieval-→12 Oct 2026Let Large Language Models Judge Each Other: Multi-Agent Peer-Reviewed Reasoning for Medical Question AnsweringarXiv:2606.15419v2 Announce Type: replace-cross Abstract: Objective: To enhance the accuracy, interpretability, and robustness of large language models (LLMs) in medical question answering (MedQA). Me→12 Oct 2026Improve my vibe-slopped pipelinetl;dr: Are there other models I should try? Is there something better than Kimi K3 for a code review? Is GLM-5.3 better at finding/patching security vulnerabilities? Are skills like https://github.com
CompanyNVIDIA8 recent entries11 Oct 2026'Strata' for GLM5.3 Flash is here for some! Project MayaI stumbled across this as I was currently having glm5.3 flash run only around 10tok/s basically unusable. With Maya i am running 30 tok/s now. GLM5.3 feels even with this low quant like a much more en→12 Oct 2026Taking Tokenization off the Host for Agentic LLM ServingarXiv:2610.13325v1 Announce Type: cross Abstract: Agentic workloads resend long contexts that barely change between calls. Prefix caching now skips most of their prefill, yet every request must still →12 Oct 2026Recommended NVIDIA paper on memory-efficient post-training RL. A very interesting technique for scaling RL for LLMs. The main takeaway is th…Recommended NVIDIA paper on memory-efficient post-training RL. A very interesting technique for scaling RL for LLMs. The main takeaway is that you can update all of a model's weights with RL and still→12 Oct 2026Nvidia tackles AI factory scaling bottlenecks with open rack designs and networking advancesNvidia Corp. today announced new partnerships and contributions to the open-source community at the Open Compute Project Global Summit in San Jose, aimed at laying the foundation for the future of age→12 Oct 2026Microsoft’s new AI chip makes it less reliant on Nvidia’s GPUsMicrosoft is announcing its third-generation Maia in-house AI chip today, designed to be the 'primary AI inference system' for Microsoft's products and services. Maia 300 not only improves the cost an→12 Oct 2026Microsoft debuts multichiplet Maia 300 inference acceleratorMicrosoft Corp. today pulled back the curtains on Maia 300, its newest internally developed artificial intelligence accelerator. The chip is optimized for inference. Microsoft estimates that it can pr→12 Oct 2026Lecture: Building a GPU Compiler From Scratch. Lowering PyTorch Graphs to CUDA via Multi-Level IRs (GPU_MODE video + article)https://preview.redd.it/3ekngxk224vh1.png?width=1080&format=png&auto=webp&s=9bfe5c92033e17d5b2fb4529f1320c99455a138b I built a GPU compiler and wrote an article about it, focusing on concepts shared b→12 Oct 2026Dell’s AI partner ecosystem adapts to Silicon Valley’s build-it-yourself buyersSilicon Valley’s AI partner ecosystem is changing as enterprises push artificial intelligence projects out of pilots and into production. In the region where much of the AI stack is invented, infrastr