OpenAI, Broadcom Forge Multibillion-Dollar Chip-Development Deal (4 minute read) OpenAI and Broadcom will develop and deploy 10 gigawatts of custom AI chips and computing systems over the next four years. The new agreement, worth multiple billions of dollars, brings the total scale of computing capacity OpenAI has agreed to buy to 26 gigawatts. OpenAI plans to deploy custom GPUs starting in the second half of next year. It is aiming to build 250 gigawatts of new computing capacity by 2033. | Facebook's Job Board Returns as AI Threatens Entry-Level Work (2 minute read) Facebook is reviving its jobs board for US users on Android and iOS. The job listings will cater to young adults trying to find entry-level job opportunities. They will be public and visible to users 18 years and older. Users will be able to directly reach out to employees through Messenger to ask questions or schedule interviews. | | Science & Futuristic Technology | Starship's elementary era ends today with mega-rocket's 11th test flight (5 minute read) Starship lifted off from Starbase at around 6 PM last night for its eleventh flight test. Every major objective of the flight test was achieved. Starship successfully deployed eight Starlink simulators and executed the third in-space relight of a Raptor engine during the flight. It also successfully executed a landing flip, landing burn, and soft splashdown in the Indian Ocean. | Superpowers for Superheroes (3 minute read) Anduril's EagleEye puts mission command and AI directly into operators' helmets. It gives soldiers enhanced perception, lethal connectivity, and heightened survivability. The HUD overlays digital information onto the real world to deliver vital real-time insights. Anduril partnered with Meta, Oakley, Qualcomm, and Gentex to bring the best in AR, rugged eyewear, compute, sensing, and ballistic helmets to EagleEye. | | Programming, Design & Data Science | nanochat (3 minute read) nanochat is a minimal full-stack training/inference pipeline for large language models (LLMs) designed to run on a single 8XH100 node. It can train an LLM in as little as four hours. nanochat handles tokenization, pretraining, finetuning, evaluation, inference, and web serving. | Beads (GitHub Repo) Beads is a lightweight memory system for coding agents with a graph-based issue tracker. It helps agents be more organized and increases their ability to handle long tasks over multiple sessions. Beads enables agents to use issue tracking with proper epics, which makes it easier for them to reliably perform complex task streams in the right order. The issue tracker has a sophisticated audit trail, allowing agents to reconstruct complex operations. | | Why Signal's post-quantum makeover is an amazing engineering achievement (22 minute read) Signal's latest updates are a significant step towards the messaging platform becoming fully quantum-resistant. Nothing will change for users as the changes are all under-the-hood - the apps will behave almost exactly as they did before. Signal has documented in great depth about the new design along with mathematical proof verifying that the updated protocol provides the claimed security properties. This article provides an overview of how the updated protocol works. | | PG Linter (Website) PG Linter is a PostgreSQL extension that analyzes databases for potential issues, performance problems, and best practice violations. | Amplifier (GitHub Repo) Amplifier is a development system that supercharges AI assistants with discovered patterns, specialized expertise, and powerful automation. | | Love TLDR? Tell your friends and get rewards! | Share your referral link below with friends to get free TLDR swag! | | Track your referrals here. | Want to advertise in TLDR? π° If your company is interested in reaching an audience of tech executives, decision-makers and engineers, you may want to advertise with us. Want to work at TLDR? πΌ Apply here or send a friend's resume to jobs@tldr.tech and get $1k if we hire them! If you have any comments or feedback, just respond to this email! Thanks for reading, Dan Ni & Stephen Flanders | | | |
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