What if AI could see the world the way we do? That’s the idea we bet our weekend on at the Mistral Worldwide Hackathon. With @haaspierre_ and Arman Artola-Zanganeh, we built 𝗣𝗼𝗿𝘁:𝗪𝗼𝗿𝗹𝗱🌍, an open-source framework that lets anyone connect their Meta glasses to any AI system. Let me take you back to saturday morning. So before knowing it could work we needed the hardware. So I ran to Rue de Rivoli and bought €500 Meta glasses on the spot. If that’s not commitment, I don’t know what is (a true bet). We then built non-stop for 36 hours to make it usable. End-to-end. The glasses stream what you see → the AI makes sense of it → it answers back through the glasses’ speaker. And suddenly when we understood that it was going to work, the question changed. It was no longer “𝗜𝘀 𝘁𝗵𝗶𝘀 𝗱𝗼𝗮𝗯𝗹𝗲?” It became “𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝗽𝗲𝗼𝗽𝗹𝗲 𝗯𝘂𝗶𝗹𝗱 𝘄𝗶𝘁𝗵 𝘁𝗵𝗶𝘀?” - A plumber getting live assistance while repairing something. - A technician repairing industrial machinery. - A traveler exploring a new country. - A visually impaired person navigating space. At first, we were looking for the “right” use case. Then we realized something more interesting. If AI can share your perspective, continuously, the use cases are not ours to decide. That’s why 𝗣𝗼𝗿𝘁:𝗪𝗼𝗿𝗹𝗱🌍 is fully open source. If you want to connect your Meta glasses, plug in your own models, customize with your own prompts, your own MCP, your Openclaw… you can. Link to the open source repo (you can contribute and give it a little star ❤️): https://t.co/UueLnkMZpM Link to the demo video: https://t.co/qcTDqKGvax Huge thanks to the organizing team of the hackathon, it was truly great. @Jthmas404

+1 more

What if AI could see the world the way we do? That’s the idea we bet our weekend on at the Mistral Worldwide Hackathon. With @haaspierre_ and Arman Artola-Zanganeh, we built 𝗣𝗼𝗿𝘁:𝗪𝗼𝗿𝗹𝗱🌍, an open-source framework that lets anyone connect their Meta glasses to any AI system. Let me take you back to saturday morning. So before knowing it could work we needed the hardware. So I ran to Rue de Rivoli and bought €500 Meta glasses on the spot. If that’s not commitment, I don’t know what is (a true bet). We then built non-stop for 36 hours to make it usable. End-to-end. The glasses stream what you see → the AI makes sense of it → it answers back through the glasses’ speaker. And suddenly when we understood that it was going to work, the question changed. It was no longer “𝗜𝘀 𝘁𝗵𝗶𝘀 𝗱𝗼𝗮𝗯𝗹𝗲?” It became “𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝗽𝗲𝗼𝗽𝗹𝗲 𝗯𝘂𝗶𝗹𝗱 𝘄𝗶𝘁𝗵 𝘁𝗵𝗶𝘀?” - A plumber getting live assistance while repairing something. - A technician repairing industrial machinery. - A traveler exploring a new country. - A visually impaired person navigating space. At first, we were looking for the “right” use case. Then we realized something more interesting. If AI can share your perspective, continuously, the use cases are not ours to decide. That’s why 𝗣𝗼𝗿𝘁:𝗪𝗼𝗿𝗹𝗱🌍 is fully open source. If you want to connect your Meta glasses, plug in your own models, customize with your own prompts, your own MCP, your Openclaw… you can. Link to the open source repo (you can contribute and give it a little star ❤️): https://t.co/UueLnkMZpM Link to the demo video: https://t.co/qcTDqKGvax Huge thanks to the organizing team of the hackathon, it was truly great. @Jthmas404

dLLM Simple Diffusion Language Modeling https://t.co/8a3wDPMZiN

Enhancing Spatial Understanding in Image Generation via Reward Modeling https://t.co/3t4ylnDlTo

Mode Seeking meets Mean Seeking for Fast Long Video Generation paper: https://t.co/TFznQW57cC https://t.co/nfLMnHpp9b

@rkobylinski "Last year" very possible you're holding it wrong. UI: should be a lot more tractable with /chrome etc. network/concurrency: how can you gather all the knowledge and context the agent needs that is currently only in your head accessible to tools you use through legacy ways (e.g. web UIs)? how can you make the things you care about testable? observable? legible? the goal is to arrange the thing so that you can put agents into longer loops and remove yourself as the bottleneck. "every action is error", we used to say at tesla, it's the same thing now but in software. Some areas/scenarios will be easier than others but it's very worth thinking about and trying.

My new favorite tmux dev layout features @opencode (with Kimi K2.5 running on @FireworksAI_HQ) on top and Claude Code on the bottom. I start almost all agent tasks with Kimi (so fast!), then ask Claude if I need a second opinion/more advanced stuff. Great combo! https://t.co/cUxfPgHFlW

@WinterArc2125 Twitter doesn't allow Edit of replies :'( I meant longer documents* not computers. The agents can be a lot more verbose and nice when you ask for docs, summaries, etc. and I love it.

FUN BREAK: Wi-Fi frequencies can map your body and movements even while you're inside your home! 👀 This Chinese project (WiFi-DensePose) proves that physical privacy is dwindling. Amazing technology, but frightening if it falls into the wrong hands. https://t.co/X61AsdDXm4

FUN BREAK: Wi-Fi frequencies can map your body and movements even while you're inside your home! 👀 This Chinese project (WiFi-DensePose) proves that physical privacy is dwindling. Amazing technology, but frightening if it falls into the wrong hands. https://t.co/X61AsdDXm4

@phuctm97 The reality of AI agents is far from meeting your expectations. Leading AI labs, know full well that current models are unreliable, third-party tests show a staggering 97% failure rate on digital tasks. Pause and let that sink in. Silicon Valley has always lived in a bubble. Today, its recklessness threatens the entire economy, and our systems aren’t ready to cope. Brace yourself. Ask yourself: why do we take AI labs at their word about their own technology? Scrutiny isn’t anti-innovation, it’s pro-accountability. https://t.co/Ut4hpvUrTa

@geminicli Last week, during my two-day deep dive into Agentic AI at @confooca, a student introduced me to the Conductor extension. After reviewing the GitHub repository, I realized it relies on “soft execution”, a well-known anti-pattern where AI is used as a runtime engine. The issue? AI is inherently non-deterministic. That non-determinism can lead to context drift, unpredictable behavior, and silent failure modes that are difficult to detect and debug. In this blog post, I break down why you should be cautious when building CLI extensions, and why using AI as the primary state or workflow engine can introduce serious architectural risks if not handled carefully. cc: @geminicli @googleaidevs https://t.co/Sasob1M0xW

Last week, during my two-day deep dive into Agentic AI at @confooca, a student introduced me to the Conductor extension. After reviewing the GitHub repository, I realized it relies on “soft execution”, a well-known anti-pattern where AI is used as a runtime engine. The issue? AI is inherently non-deterministic. That non-determinism can lead to context drift, unpredictable behavior, and silent failure modes that are difficult to detect and debug. In this blog post, I break down why you should be cautious when building CLI extensions, and why using AI as the primary state or workflow engine can introduce serious architectural risks if not handled carefully. https://t.co/Sasob1M0xW #agenticai #antipattern #nondeterministic #geminicli #conductor

Ever wondered how AI can recognize who's speaking in an audio clip? Meet a powerful model that turns voices into unique signatures. It's a speaker embedding model, and it's changing how we analyze conversations. https://t.co/Fz8OHQH9Vj

If you’re building an AI product and want to test the market fast, ship the web version first. When you’re ready, use Pake to package it into native desktop apps for macOS, Windows, and Linux with a single command. Pake 3.10.0 is live. Turn any webpage into a desktop app. https://t.co/2OgMlll1lG Highlights: · Multi-window support via –multi-window, with Cmd+N on macOS and proper tray integration. · –internal-url-regex for fine-grained control over internal links, useful for complex AI dashboards and multi-route tools. · Improved Windows icon quality with prioritized 256px ICO entries. · Retina DMG background fix for cleaner macOS distribution builds. Build on the web, validate with users, then ship desktop when it matters. Keep the loop tight.

When you parse a document with LlamaParse, you also get access to layout data for figures, charts, etc. Parse the document, specify to save layout images, and access those images on the response! Each image will be a cropped screenshot of that specific layout element. https://t.co/IOQL8ksPX1

This Reddit thread is hitting 1,000+ developers right in the anxiety. A frontend engineer with a year of experience downloaded Cursor, got massive productivity gains, and now feels like they're "becoming an idiot." The line that's haunting people: "I can design an entire system using a concept I only kind of understand. If I switch to a normal editor or explain it to a coworker, I can't do it at the depth I should." Here's what's actually happening... The tools that autocomplete your code don't make you think through what you're building. They fill the silence with their best guess. You get the dopamine hit of seeing code appear, but you never had to hold the full picture in your head. That's not the tool's fault. That's what it was designed to do. BrainGrid works differently. It doesn't write code for you. It makes you answer the questions most people skip: What happens when a user does X? What's the edge case you're not seeing? What does done actually mean? You're forced to think through the architecture, the requirements, the constraints before anything gets built. By the time you hand that structure to your coding agent, you understand exactly what's being built and why. The developers who feel dumber after using AI are the ones who skipped the thinking part and went straight to the building part. BrainGrid puts the thinking part back in, and that's the part that makes you better. Try it free at https://t.co/uJPWvrpDxZ

Pokemon Cards as a Finance App, built by Perplexity Computer

I built my own sector rotation dashboard using Perplexity Computer. The Rotation Graph tells me what sectors are leading and leading at any given moment. For good measure, I added a trend leaders section, which helps me identify sector leaders in every major sector. Not too shabby for someone with 0 coding experience. 😂

If you ever want to see a really interesting AI thinking trace, push it really hard on literature or poetry suggestions. Here is Claude 4.6 Opus working through poetry when I asked it to find something that captures the feeling of AI while avoiding its usual favorites (eg Rilke) https://t.co/B0phEv3qIN

In this amazing multidisciplinary collaboration, we report our early experience with the @openclaw -> https://t.co/THXYyajfQB

@erusev @antoniostoilkov Still early — feedback welcome! Check out LlamaBarn at https://t.co/f5zVgNyf7X

I've started a company: https://t.co/jFknDoasSy From a fun side project just a few months ago, ggml has now become a useful library and framework for machine learning with a great open-source community

Introducing LM Link ✨ Connect to remote instances of LM Studio, securely. 🔐 End-to-end encrypted 📡 Load models locally, use them on the go 🖥️ Use local devices, LLM rigs, or cloud VMs Launching in partnership with @Tailscale Try it now: https://t.co/Vl2vr6HlF5