AnnCode Solutions @AnncodeHub

OpenJarvis: a local-first personal AI is now available to run with Ollama Built by Stanford’s @HazyResearch and Scaling Intelligence labs, as part of their “Intelligence Per Watt” research into efficient local AI. @Stanford Learn more in the blog post 👇👇👇

Windows users, this one’s for you. Computer use now works on Windows, so Codex can take action on your Windows computer. And with Windows support for Codex in the ChatGPT mobile app, you can start, review, and steer tasks on the go while work continues on your Windows machine. An early experience, but we’re working on more ways to keep your work moving, wherever you are.

Claude Opus 4.8 is now available for Max subscribers on Perplexity and Computer.

How powerful is Gemini 3.5 Flash? In a recent research preview, we pushed it to the extreme, powering 93 subagents across 15,314 model calls that wrote a custom kernel, filesystem, and drivers from scratch. 12 hours later, it booted Doom. 🖥️ This is just a glimpse of the model's reasoning depth and code generation capabilities. Full breakdown below 👇

OpenShell v0.0.41 🧩 agent-driven policy management 🎚️ sandbox resource flags in the CLI 🔒 custom CA support for OIDC TLS verification 📥 sandbox downloads with workspace-boundary checks 🔧 bug fixes and stability improvements Policy and resource control, directly from the shell. github.com/NVIDIA/OpenShe…

Case study time! Hirundo trained Gemma 4 E4B to resist adversarial overrides while overcoming the alignment tax: - Weight-level defense based on Gemma 4 architecture - Stronger security posture than models over 100x its size - Preserves utility across benchmarks

What is a claw? 🦞 It's the shift from AI that suggests → AI that acts. Autonomous agents that run 24/7, handling complex work in the background so you don't have to.

Claude Code weekly limits are increasing 50%, now through July 13. Live now for all Pro, Max, Team, and seat-based Enterprise users.

Batching for vision models is now available in Beta with our latest MLX engine update 👾 The updated engine also brings major improvements to caching for faster inference overall. Turn on Developer Mode, choose the beta runtime channel, and select LM Studio MLX v1.8.1.

Codex is getting easier to automate and customize around your code. 🪝 Hooks customize the Codex loop with scripts that run at key points in a task: • Run validators before or after work • Scan prompts for secrets • Log conversations to internal systems • Create memories or customize behavior by repo or directory ⚙️ Programmatic access tokens provide scoped credentials for Business and Enterprise teams: • Create tokens from ChatGPT workspace settings • Use them in CI, release workflows, and internal automations • Set expirations or revoke access when needed • Keep usage tied back to the workspace

We just added significantly more NVIDIA Blackwell GPUs to better serve GLM-5.1 model on Ollama's cloud. We have been adding more GPUs daily for all the other models. Claude Code: ollama launch claude --model glm-5.1:cloud Codex App: ollama launch codex-app Hermes Agent: ollama launch hermes --model glm-5.1:cloud Run the model: ollama run glm-5.1:cloud

You've been asking for this one... Now in preview: Codex in the ChatGPT mobile app. Start new work, review outputs, steer execution, and approve next steps, all from the ChatGPT mobile app. Codex will keep running on your laptop, Mac mini, or devbox.

You can now use GPT Image 2 on Manus Slides! 👉 Edit text or visuals with point-and-click precision 👉Swap elements or update imagery with a prompt 👉Add speaker notes — or let Manus write them 👉Export to Google Slides, PowerPoint, PDF, Drive, or OneDrive

🆕 Today, we're releasing the public preview of Workflows, the orchestration layer for enterprise AI. 🌎 Enterprise teams have capable models. What they don't have is a way to run them reliably in production. That's the gap Workflows fills. It takes AI-powered business processes from prototype to production, with the durability, observability, and fault tolerance that production actually requires. Leading organisations like ASML, ABANCA, CMA-CGM, France Travail, La Banque Postale, Moeve, and many others are already using Workflows to automate critical processes.

Earlier this year, OpenAI and @amazon partnered to bring OpenAI’s frontier capabilities to enterprises, startups, and customers around the world. We’re taking the next step: making our models, Codex, and Bedrock Managed Agents available to @awscloud customers, in limited preview. Making OpenAI available on AWS means enterprises can get AI into production faster - across software engineering and other professional workflows. We’re excited to see what gets built! openai.com/index/openai-o…

Offline vibe coding with Gemma 4. This open-source Electron app runs entirely on your Mac via Apple's MLX framework. No Wi-Fi required.

If you’re seeing this, you should be following @NVIDIAAI. Our developer team has moved next door to @NVIDIAAI. Join us there to stay up to date on the latest products, models, deep dives, and more. Thanks to everyone who’s been with us here. We hope to see soon 💚

Meet Nemotron 3 Nano Omni 👋 Our latest addition to the Nemotron family is the highest efficiency, open multimodal model with leading accuracy. 30B parameters. 256K context length. 🧵👇

Claude Code can now send push notifications to your phone when a long task finishes or Claude needs your input. Walk away from the terminal, we'll let you know when it's done.

🚀 Introducing FlashQLA: high-performance linear attention kernels built on TileLang. ⚡ 2–3× forward speedup. 2× backward speedup. 💻 Purpose-built for agentic AI on your personal devices. 💡Key insights: 1. Gate-driven automatic intra-card CP. 2. Hardware-friendly algebraic reformulation. 3. TileLang fused warp-specialized kernels. FlashQLA boosts SM utilization via automatic intra-device CP. The gains are especially pronounced for TP setups, small models, and long-context workloads. Instead of fusing the entire GDN flow into a single kernel, we split it into two kernels optimized for CP and backward efficiency. At large batch sizes this incurs extra memory I/O overhead vs. a fully fused approach, but it delivers better real-world performance on edge devices and long-context workloads. The backward pass was the hardest part: we built a 16-stage warp-specialized pipeline under extremely tight on-chip memory constraints, ultimately achieving 2×+ kernel-level speedups. We hope this is useful to the community!🫶🫶 Learn more: 📖 Blog: qwen.ai/blog?id=flashq… 💻 Code: github.com/QwenLM/FlashQLA