Anthropic is introducing the Model Hardware Standard (MHS), a new standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. MHS began as part of a beneficial deployments project with HHMI Janelia Research Campus and is evolving into a wider industry effort. It is now in research preview with select partners.
The most popular use case for Claude Tag by far -- on-call. Learn about how we drive Anthropic's on-call with Tag and set it up yourself so you don't get woken up by an alert at 3am that Claude could solve. https://claude.com/blog/ai-ci-cd-on-call
Augment Code introduces Cosmos Advisor, an expert that can answer product questions, configure agents, and deploy automations from a single conversation. The company says a company-specific agent can be set up in about ten minutes, without a handoff to an implementation team. Advisor draws on the current Cosmos knowledgebase and reusable expert designs, such as incident response, and it works within Object-Level Access Control.
Augment Code's two-engineer Cosmos Advisor team built a Feedback Triager agent to handle product feedback that grew to about 30 threads per week, which had consumed an estimated 90% of team time. The agent investigates each Slack report through root-cause analysis, answers questions, routes issues to other teams, files tickets, and hands clear fixes to a PR Author agent. Humans retain prioritization and product decisions.
Welcome the Ojai. New vehicle, same Waymo Driver.
Anthropic is building the Model Hardware Standard (MHS), a common way for AI models to connect to lab and manufacturing equipment and operate it with safety limits built into each device. MHS started as a collaboration between Anthropic and HHMI Janelia Research Campus and is launching as a research preview with partners across science, robotics, and manufacturing.
AIWhy it matters: The source describes a standard for connecting AI models to lab and manufacturing hardware, which matters for anyone building automated experimentation workflows.
To avoid this scenario where agents wipe everything out permanently, just branch your database, it's super easy to do on Neon Lakebase: 𝚗𝚎𝚘𝚗𝚌𝚝𝚕 𝚋𝚛𝚊𝚗𝚌𝚑𝚎𝚜 𝚌𝚛𝚎𝚊𝚝𝚎 --𝚗𝚊𝚖𝚎 𝚗𝚎𝚠𝚋𝚛𝚊𝚗𝚌𝚑
Anthropic and HHMI Janelia Research Campus developed the Model Hardware Standard (MHS), a standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. MHS is now in research preview with select partners, and the video describes how it was developed and how it can accelerate research.
Try it here: https://replicate.com/google/gemini-omni-1.1
Replicate announced that Gemini Omni 1.1 Flash from Google DeepMind is now live on its platform. The update adds scene extension, control of a shot's starting and ending frames, video input references, upscaling to 4K, and 360p fast prototyping.
Read full blog: https://www.lmsys.org/blog/2026-08-27-minimax-h3-h200
MiniMax-H3 on 8×H200 GPUs reaches 1.85–1.95x lossless speedup over Diffusers without approximation, with fixed prompts, seeds, resolution, FPS, and 50 denoising steps. Adding step reuse and sparse attention raises speedup to as much as 6.24x, but quality varies by workload, with SSIM from 0.76 to 0.91. Two presets trade off the two: a conservative Cache-DiT setting gives 2.99x at 0.90–0.98 SSIM, while a faster SubBlock 0.75 plus Cache-DiT stride gives 4.90–5.93x at 0.77–0.92.
We built https://vgpu.sh to ship shaders on https://vercel.com. Now it's open source. ▪︎ Minimal agent-first WebGPU library ▪︎ Run in the browser or headless Node.js ▪︎ Render in CPU sandboxes and CI tests ▪︎ Create reusable .wgsl modules
Unsloth says GLM-5.3-Flash can run locally, with a 3-bit GGUF version needing 128GB of RAM and the 1-bit version working on 102GB of RAM or VRAM. The guide's table lists memory needs from 100GB at 1-bit to 650GB at BF16, and reports that the 1-bit quant keeps 71% of top-1% accuracy while being 85% smaller than BF16.
AIWhy it matters: The guide gives concrete memory requirements for each quantization level, which helps readers judge whether the model fits their hardware.
This is the Star Wars future we deserve! Would you rather live in a world filled with the same faceless white humanoids or a world where robots come in all shapes, colours and capabilities?
DLSS 4.5 Ray Reconstruction is out! We built a second generation joint denoiser/superresolution model, and it has much better image quality for the same compute cost. AI keeps pushing the Pareto frontier of IQ and rendering cost. https://www.youtube.com/watch?v=9QyNSVNNduM
Cursor Cloud Agents no longer require a connected GitHub or other third-party SCM provider to begin work. Users select "Start from scratch" in the repo picker, and Cursor creates an Origin repo in the background that can be saved as a private or internal repo via "Create repo." Cursor also now port-forwards the cloud agent's live environment to the browser for previews, and a connected Vercel account lets users publish a live URL.
In an interview with Jiazi Guangnian, Renmin University information school dean Chai Yunpeng describes his team's social simulator, which runs over 13.5 million AI agents calibrated against the CGSS survey data. He argues that social world models are the missing piece for AI agents that must interact with people, and that the startup Jingtong Technology has raised two funding rounds in two months.
The Google Developers Blog post describes how deep learning can analyze the large, image-like sensor data from astroparticle observatories such as the Pierre Auger Observatory and IceCube. The author argues these methods could improve instrument sensitivity and reveal patterns in cosmic-ray and neutrino signals that traditional analysis techniques miss.
NVIDIA and AWS are expanding their partnership across GPUs, CPUs, networking, open models and software. The announcement cites 2 million additional NVIDIA GPUs across AWS infrastructure, the NVIDIA Vera CPU coming to AWS for agentic AI, NVLink Fusion with NVHBM memory, and 100,000 GPUs for U.S. government AI factories on secure AWS infrastructure.
Wan 3.0 Prime is now on Replicate. The accelerated variant of Wan 3.0 from @Alibaba_Wan for text-to-video, image-to-video, and reference-driven workflows. Generate clips up to 30 seconds long in one shot with integrated audio-visual generation.
Replit has made Intelligent Model Routing available to all users, automatically matching each task with a model based on quality, speed, and cost. In the company's testing, the feature delivered the same output quality at 65% lower cost than the previous version of Max Mode. Enterprise administrators can restrict routing to a company-approved set of models.
LM Studio announced that Z.ai's GLM-5.3-Flash, previously previewed as Ox Alpha, is available in LM Studio Bionic. The source says the model outperforms GLM-5.2 at 9-10x lower cost, supports image input, and is served from US-based servers with ZDR enabled by default.
Model page: https://lmstudio.ai/models/glm-5.3-flash
This is unfortunate, but this is why we're making cloud storage, databases, etc all branchable and recoverable at @neondatabase and @databricks! Agentic development will need a new kind of cloud infra.
Grok Bot is now available to all standard Grok and Cursor subscribers, with SuperGrok and Cursor Pro subscribers included. Cursor's Michael Truell says users are delegating tasks ranging from running small e-commerce businesses to testing production software. Weekly usage limits are also being reset for all users.
Say hello to Gemini 3.5 Transcribe! - Build apps that understand user speech / intent, even w/ multiple speakers! - Auto-detection of 85+ languages out of the box - Custom vocab adaptation for specialized jargon... SGTM:) API available now in @GoogleAIStudio and Gemini Enterprise, or try it in the Gemini app on macOS or Rambler on Android! More details: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-5-transcribe/
Use Grok Voice models in LiveKit to build useful voice agents with full support for ZDR
Z.ai released GLM-5.3-Flash, a 320B-A18B model, with day-0 support in SGLang, after appearing earlier as ox-alpha. The post calls it the first native multimodal model in the GLM-5 series and says it outperforms GLM-5.2 at one-tenth the cost, with stable 1M-token long-context performance.
AIWhy it matters: The post reports GLM-5.3-Flash's native multimodal design, its efficiency claims, and day-0 SGLang support, which bear on running it in practice.
Try all variations: v4 styles: https://replicate.com/recraft-ai/recraft-v4-styles v4 svg: https://replicate.com/recraft-ai/recraft-v4-styles-svg v4 styles pro: https://replicate.com/recraft-ai/recraft-v4-styles-pro v4 styles pro svg: https://replicate.com/recraft-ai/recraft-v4-styles-pro-svg
SGLang announced Day-0 support for Qwen3.8-Flash-Next, a 125B MoE model with 6B active parameters and 51B N-gram embeddings, in collaboration with Alibaba Qwen, NVIDIA, and AMD. The post reports 540 tok/s decode speed at BS=1 on NVIDIA B200 (TP4) with an NVFP4 checkpoint, and says N-gram host offloading saves 23.5 GiB VRAM per GPU and raises KV capacity by 78.5%.
Microsoft's Accelerating Frontier Transformation series says AI is helping organizations deliver more personalized engagement at scale and give staff time back for relationships. Examples include Lifeline Australia using AI for service insight, Brisbane Catholic Education personalizing curriculum for students with Copilot, and Uniting NSW.ACT's Buddy platform cutting some frontline tasks from 10 to 15 minutes to one to two.
Standard API Pricing for GLM-5.3-Flash (per 1M tokens) - Input: $0.15 - Output: $0.50 - Cached input: $0.03
DeepSeek V4 Pro 0813 scored 95.2% on SWE-Bench Verified, ahead of Kimi K3 at 92.6% and Fable 5 at 85.4%, in Fireworks AI's eval runs. It costs $0.309 per solved task on SWE-bench versus $0.808 for Fable 5, and it is available through Fireworks serverless and dedicated endpoints, with SFT, DPO, and RFT training support. Its 1M-token context window and native tool calling target long-horizon agentic workloads, though its Java accuracy on Aider Polyglot (48.9%) trails Fable 5 (74.5%).
DeepSeek V4 Pro 0813 recorded zero refusals across 840 adversarial security tasks in CyberGym testing, solving them at about half the cost per success of the top-scoring model tested, Kimi K3. In the 697-task common cohort, V4 Pro reached a 53.7% reward rate at $2.50 per solved task, versus 47.6% and $9.64 for GPT-5.5 and 5.9% and $33.28 for Claude Opus 4.8.
Google Cloud has added native TPU support to vLLM and engineered optimizations to serve the Qwen3-Embedding-8B model on Cloud TPU, targeting 4K+ token text and 15K+ token multimodal inputs. The work addresses tensor alignment, lazy-loading, compilation pre-warming, and long-context pooling, with a cosine similarity pass threshold of at least 0.999 for text and 0.995 for multimodal inputs against XPU reference vectors.
Z.ai has released GLM-5.3-Flash, a model with native visual capabilities that observe interfaces, rendering results, and interaction feedback across code, browsers, and GUIs. It uses a hybrid linear and sparse attention architecture with 320B total parameters and 18B activated, which the company says significantly reduces compute and KV-cache requirements. The release notes also describe support for office document and financial research workflows.
AIWhy it matters: The release notes give GLM-5.3-Flash's architecture, parameter counts, and cybersecurity findings, which make the model's scope concrete for comparison with earlier GLM releases.
Coding agents want 𝚎𝚟𝚊𝚕. Today they get 𝚛𝚞𝚗: • Hardened QuickJS sandbox • Expose only approved host functions • Pause for human approval, then resume • Runs anywhere Node.js runs https://vercel.com/blog/introducing-run
OpenWorker, an open source agent that completes tasks on a laptop, has released a new version with built-in cybersecurity agents. The agents scan code for vulnerabilities, scan dependencies for supply chain injections, and check cloud security configurations for attack surfaces. Users can run open weight models locally so sensitive code stays on their machine.
You can use Vercel Connect directly in v0 to securely connect your app to Slack, GitHub, Notion, Salesforce, and more. Learn more: https://v0.app/docs/vercel-connect