Updated
Updated
AITri Dao congratulated the Etched team, calling it strong in both hardware design and kernels. The quoted Etched post says the company raised $300M in Series C funding at a $10.3B valuation to accelerate production of its inference clusters. It also opened an 80,000-sqft, 10-MW facility for production and prototyping.
AISequoia Capital is leading Etched's $300 million Series C at a $10 billion pre-money valuation, backing the startup's custom inference silicon. Etched says its first-generation chip taped out at TSMC on leading-edge nodes and that its first cluster ran a range of frontier models in 40 days, with early customers now getting access.
AICognition has signed a memorandum of understanding with the U.S. Department of Energy to join the Genesis Mission, a national AI initiative launched by executive order in November 2025. Cognition will contribute its Devin autonomous AI software engineer in four areas: software and data security, modernizing legacy scientific code, expanding scientific workforce capacity, and cloud modernization. Devin Desktop and CLI are listed as FedRAMP Class D (High) Authorized, and the company has offered in-kind code security scans for national laboratory codebases.
AILisa Su says AMD Helios will help power Anthropic's Claude at gigawatt scale. The quoted AMD announcement states the partnership expands to up to 2 GW of AMD Instinct MI450 Series GPUs in AMD Helios, with AMD committing up to $5B in strategic equity investment in Anthropic.
AIOpenAI is developing Project Camellia, a long-term AI infrastructure project in Effingham County, Georgia, and says it will pay all infrastructure and electric-service costs so existing ratepayers are not subsidizing it.
AIMistral announced an expanded global strategic partnership with Microsoft, backed by a multi-billion dollar commitment from Microsoft. The deal accelerates Mistral's AI infrastructure build-out in Europe and makes its open-weight models available to Microsoft customers in Copilot Studio, Azure Foundry, and Azure Local.
AIJetBrains Air now connects to ACP-compatible coding agents, including GitHub Copilot CLI, OpenCode, Pi, and Cline, through the Agent Client Protocol. The release also adds Beta Java and Kotlin navigation and diagnostics powered by the IntelliJ IDEA code engine, local model support through Ollama or LM Studio, and Docker-based agent tasks on Windows.
AIGoogle introduces Gemini 3.6 Flash as its workhorse model, with better coding, knowledge work, and multimodal performance while reducing token usage. It also launches Gemini 3.5 Flash-Lite, described as the fastest and most cost-effective 3.5-class model for high-throughput applications, and 3.5 Flash Cyber, a version of 3.5 Flash fine-tuned to find and fix cybersecurity vulnerabilities.
Why it matters: The post lists three distinct models, each aimed at a different job, so readers can map which one fits coding, high-volume, or security workloads.
AIJetBrains has launched JetBrains Context in early access, a repository intelligence layer that builds a semantic index so coding agents can retrieve relevant code without repeated searching. In tests on 205 SWE-bench tasks, 175 production-monorepo tasks, and 1,953 code-localization tasks, it reduced agent turns by up to 68%, latency by up to 59%, and execution cost by up to 48%. It works with Claude Code, Codex CLI, and Junie CLI at no additional cost for JetBrains AI subscribers, and it does not store source code on JetBrains Context servers.
Why it matters: The source gives benchmark figures for turns, latency, and cost, showing how repository indexing might change agent workflows on large codebases.
AIAt RAAIS, DeepMind VP of Research Raia Hadsell argued that the field focuses too much on language and should apply large-model training to worlds, robots, biology, and weather. The article cites DeepMind's DiffusionGemma, a 26-billion-parameter open text model that generates blocks by denoising rather than one token at a time, and the Genie-3 world model, which runs in real time for several minutes. It also describes world models as a source of synthetic training data for robots.
AISYNAPS-I, a multi-lab Genesis Mission project led by Lawrence Berkeley National Laboratory, uses Meta's open-source SAM 3 and DINOv3 models to segment X-ray and micro-CT scientific imagery. The fine-tuned pipeline, run on 300 A100 GPUs, reduced a grapevine xylem analysis from a month of expert annotation per time step to about 15 minutes. The team can deploy the open models inside secure national lab infrastructure, where research data must remain.
AIA security team found commercial frontier model APIs blocked their incident-response log analysis, which required submitting real attack commands and exploit payloads. They ran the forensic analysis on GLM 5.2, an open-weight model, on their own infrastructure, which also kept attacker data and referenced credentials inside their environment.
AICognition has acquired or welcomed the TierZero team, led by Anhang and Yun, to bring their work on automations into Devin. The goal is to help engineers spend less time handling incidents and more time building, with the source offering no further product details.
AIAMD and Microsoft Azure are expanding their partnership to deploy AMD Helios with MI455X GPUs, Venice CPUs, and Pensando networking. According to AMD's linked background, Microsoft will use Helios to power frontier model AI inference for itself, its AI customers, and Azure AI services.
AIThe article explains how reasoning models can offer multiple effort modes, separating training-time methods from inference-time controls such as system prompts and chat templates. It compares six open-weight models, including DeepSeek V4, Nemotron 3 Ultra, Kimi K2.5, GLM-5, Qwen3, and Inkling, noting that their reports disclose different levels of detail. It also shows how GPT-5.6's model selection and effort settings act as two separate scaling axes.
AISekhar and Katie Brandt built Foreguard, a free tool built with ChatGPT and Codex, to help families claim public benefits they are entitled to and plan private insurance coverage. The tool shows that modest budgets of $100 a month can create millions of dollars of day-one financial protection. The goal is to help families prepare earlier, before care decisions become urgent.
AIDeepLearning.AI has launched a short course, built with Cerebras, on building LLM applications that respond quickly using inference-optimized hardware. The course compares how GPUs, TPUs, and Cerebras' Wafer-Scale Engine handle the memory-to-compute bottleneck, which keeps model weights close to compute units to speed token generation. It covers real-time applications such as live translation and voice agents, plus habits for agentic coding.
AISkywork announced an upgrade to Skywork Video that adds an infinite canvas for mapping ideas, a storyboard for organizing scenes, and a video editor for refining the final video. The company says these tools keep planning, sequencing, and editing in one workflow.
AIRun upgraded Gemma 4 with llama.cpp (QAT + MTP)
AIBunkerhill Health's Carebricks platform lets health systems create and deploy AI agents across clinical and operational use cases using data hospitals already generate. Sequoia Capital backed the company at seed and is continuing to invest. At UTMB Health, Bunkerhill grew from one agent in production to more than twenty, consolidating multiple vendors' point solutions into one platform.
AIModal has trained a DFlash speculator that runs much faster than MTP, according to Soumith Chintala. The speculator is backed by Inkling by Thinking Machines, which Modal says delivers 67% higher throughput and interactivity on Modal Auto Endpoints with SGLang.
AIThinking Machines introduced Inkling, an open-weight model with 975B parameters that reasons across text, image, and audio. The full weights are available, with fine-tuning on Tinker and access through the Inkling Playground and Hugging Face and partners.
AIThinking Machines has launched Inkling and says it is eager to see what developers build with it. The post offers no further technical details, figures, or availability information.
AIThinking Machines thanked a group of partners, including Together AI, Fireworks AI, Databricks, Unsloth, Modal, and Baseten, for providing day-0 support across the open-source ecosystem. The post also credits Inferact for vLLM support and RadixArk for SGLang support. It does not name the model or release involved.
AIVishal, who lost a leg at age six, used ChatGPT to plan his cycling training, nutrition, recovery, and prosthetic design research. After one year of competitive racing, he qualified for elite competition and earned a chance to represent India at the 2026 Asian Para Road Cycling Championships in Saudi Arabia and the Para Cycling Road World Cup in Thailand.
AICognition says its one-year-old merger with Windsurf has produced a more capable Devin, which now manages other Devins at a mid-to-senior engineering level, and new SWE-1.7 model, described as its most capable and efficient to date. The company reports growing from 44 to 350 people and revenue run rate from $73M to $500M+ since merging the brands.
AIGeorgi Gerganov announced the 10,000th release of llama.cpp, marking a notable milestone for the open-source inference project. The post itself contains no further details about the release contents, features, or version number.
AIArvind Narayanan's ICML keynote argues that AI's labor impact will depend on slow organizational adaptation rather than a single lab milestone. He cites reliability measurements showing agent accuracy rose much faster than reliability over the last 24 months, and points to software engineering and past technologies like electricity and ATMs. He concludes that evaluation work and human judgment will become more central as building tasks are increasingly automated.
AICognition found that Fable 5 led runs cost less than Opus 4.8 led runs on FrontierCode 1.1 when both used the same sidekick, $1.86 versus $2.04 per run. Fable 5 scored 60.7 against 54.6 for Opus 4.8 in those configurations, and it took fewer lead turns, delegated earlier, and rarely edited code itself. The post attributes the difference to delegation style rather than per-token price, and notes that the approach gives little benefit on short or serial debugging tasks.
Why it matters: The source compares lead-model delegation habits on a coding benchmark, showing how a pricier model can lower total agent cost through fewer turns and better handoffs.
AICognition's entire platform, including Devin Cloud, is now FedRAMP Class D (High) In-Process and listed on the FedRAMP Marketplace, extending FedRAMP High authorization beyond Devin Desktop (formerly Windsurf). Devin Desktop and CLI are already FedRAMP High Authorized for workloads with ITAR and DoW IL4, IL5, and IL6 requirements. The company says Devin Security Swarm can find and validate vulnerabilities and open remediation pull requests, and that fleets of Devins can upgrade legacy software 5-40x faster than humans alone.
AIEmma Dahl wanted a historically inspired wedding dress that incorporated pearls from her grandmother's necklace, so she used ChatGPT over months to troubleshoot niche sewing and corset construction. The chatbot also helped her choose a sewing machine upgrade, the shape of her veil, and how to pack and travel with the orchids for her bouquet.
AIPatrick Cheng used ChatGPT to redesign menus, optimize pricing, and improve marketing after acquiring a struggling restaurant in 2021. He reports more than 200% sales growth and a tripling of catering business, and is now launching NextGen, a nonprofit helping family-owned businesses adopt AI through education and micro-grants.
AIJohn Schulman says Thinking Machines, founded a year and a half ago, is revisiting its original instincts after major progress in agents. The company published a written statement of what it now believes about customizable models and humans working well with AI.
AIThe essay argues that AI labs selling model inference face commodity pricing pressure, but may achieve durable profits by moving into products, enterprise deployments, and switching-cost moats. It cites historical infrastructure industries and the Bertrand paradox to support the view that value capture depends on climbing the stack. The authors also warn that successful lock-in could raise enterprise costs and concentrate power, making early interoperability and portability standards important.
AITwo business owners, Mike and Mike, use ChatGPT in Rockaway Beach to forecast surf conditions, build instructor schedules, and manage payroll and inventory. They also rely on it to navigate permits and local regulations so they can focus on their core work.
AIZed v1.10 now includes proper support for llama.cpp as a model provider, according to Georgi Gerganov. Zed's own announcement credits Hugging Face with helping make the llama.cpp integration possible.
AIMeta Superintelligence Labs has introduced Muse Spark 1.1, a multimodal reasoning model aimed at agentic tasks, with gains in tool use, computer use, coding, and multimodal understanding. It supports a 1 million token context window and is available in Thinking mode in the Meta AI app and on meta.ai, with developers able to access it through a public preview of the Meta Model API.
Why it matters: The post specifies Muse Spark 1.1's agent, coding, and multimodal gains and its Meta Model API preview access, which helps developers judge its fit for their workflows.
AIAnthropic will host a live walkthrough at 10am PT tomorrow showing how Claude Code progressed to multiplayer Claude Tag. The session will cover how Claude Tag works, including monitoring channels, doing proactive work, letting the whole team steer it, and remembering prior instructions.
AICursor co-founder Michael Truell announced Grok 4.5, a model trained with SpaceXAI that the post calls Opus-class, fast, and low cost. He says it is a significant step up over Composer 2.5 and has become the daily driver for many on the Cursor team. A benchmark table shows Grok 4.5 at 83.3% on Terminal-Bench 2.1 and 78.0% on SWE-Bench Multilingual, with the post saying more releases will follow.
AICognition launched SWE-1.7, which it says reaches frontier-level coding performance at lower cost, trained from a Kimi K2.7 base. The post describes RL methods including top-p sampling replay to preserve entropy, compressed weight deltas across multi-cluster training, and self-compaction for rollouts up to six hours. SWE-1.7 is available in Devin via Cerebras at 1000 TPS.
Why it matters: The post details entropy preservation, multi-cluster weight sync, and self-compaction, offering concrete RL training techniques for long-horizon coding agents to compare against one's own pipeline.