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OpenAI launched Codex, a new coding agent that builds features and fixes bugs autonomously It can work on many tasks in parallel, navigate codebases, implement changes, and propose pull requests for review Available for Pro, Enterprise, and Team users

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Significant progress in AI and Robotics this week. So, I summarized everything from OpenAI, Google, Tesla, Salesforce, Alibaba, Notion, Foundation Robotics, CMU Robotics, and more. Here's everything you need to know and how to make sense out of it:

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Google dropped AlphaEvolve, an AI that discovers algorithms for scientific and computational challenges —Uses Gemini models with auto-evaluation & iteration —Found the first improvement on 1969's Strassen's algorithm —Also boosting efficiency for Google

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Google also announced plans to expand Gemini to more platforms, including smartwatches, cars, and XR headsets. Plus, it debuted 'AI Futures Fund' to give startups early access to advanced models, funding, and technical expertise to boost development

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OpenAI also dropped multiple product updates, including: —GPT-4.1 and GPT 4.1-mini coding for ChatGPT free and paid users —PDF exports for reports generated via ChatGPT Deep Research —A new Safety Evaluations Hub showing models' safety levels

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The Tesla team behind Optimus shared a clip of the humanoid, showing its dance moves, using sim-to-real reinforcement learning Elon shared that Optimus is operational in the Tesla office, moving around unsupervised

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Salesforce released xGen-Small family of small AI models It includes two variants, 4B & 9B params, with the larger one proving competitive on long-context understanding up to 128K tokens Both also deliver strong performance on math + coding benchmarks

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Alibaba's Qwen team made Deep Research for Qwen Chat available for all users It's pretty much like ChatGPT's Deep Research, providing users the ability to prepare detailed reports on different subjects in a matter of minutes.

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Alibaba's Wan dropped Wan2.1-VACE, a unified AI for video creation and editing Available in 1.3B, 14B sizes, the model can handle reference-to-video generation, video-to-video editing, and masked video-to-video editing Open-sourced under Apache 2.0

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Notion launched an "AI for Work" suite for its business plan subscribers, offering: —AI meeting notes —Access to different AI models, including GPT-4.1 —Enterprise Search to find answers across different platforms —A research ode to draft docs

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California-based Foundation Robotics shipped its production humanoid to its first customer The company says it will be working over coming months to ensure the deployed fleet manages to "perform full shifts"

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Researchers at CMU Robotics presented DexWild, a data collection system to gather human hand data across environments In tests, it enabled AI policies to generalize in unseen scenes 3.8x better when compared to training with robot data only

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Tsinghua University researchers detailed HuB, a unified framework to help humanoids handle extreme balancing tasks It integrates reference motion refinement, balance-aware policy learning, and robustness training to improve sim-to-real consistency

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Stability AI open-sourced Stable Audio Open Small, a text-to-audio AI —341M-parameters —Generates 11s of audio, including drum loops, foley, riffs, and textures —Optimized for Arm-based consumer devices

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We're hiring for hundreds of roles @Figure_robot: > AI Engineers (many) > Staff Security Engineer > HMI Design Lead > System Integration & Test (many) > Legal (many) > Manufacturing (many) Apply here:

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That's it for this week's AI and Robotics breakdown. I share the latest research every week, so follow me @adcock_brett for more. If you found this valuable, consider a like/retweet to spread the word.

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API testing of interfaces is critical to determine if they meet requirements for functionality, reliability, performance, and security. Check out RTTS - the automated testing experts since 1996. #API #testautomation #integrationtest

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🚨 OpenAI just launched Codex, a brand-new autonomous coding agent that can build features and fix bugs on its own. We’ve been using it Every 📧 for a few days, and I’m impressed. I invited Alexander Embiricos (ben davies), a member of the product staff responsible for Codex, to demo Codex and talk about it live on a special edition of AI & I: What Codex is and how it works Codex is designed to be used by senior engineers—it performs coding tasks like adding features or fixing bugs autonomously. It's built to allow you to start many sessions at once, so you can have multiple agents working in parallel. Codex is built to have "taste" OpenAI trained Codex to have the taste of a senior software engineer. It knows how big codebases work, how to write a good PR, and uses clean, minimal code. Why an “abundance mindset” is best for interacting with agents Codex is designed to allow users to delegate many tasks at once without getting caught up in the details. This lets you point an abundance of agents at a specific task like a difficult bug—it’s worth it even if only one of them succeeds. How OpenAI is thinking about agents Codex is one piece of a unified super-assistant OpenAI wants to eventually build—an agent that helps users easily get things done by selecting the right tools for them behind the scenes. OpenAI’s vision for the future of programming In the future developers will probably spend less time writing routine code and more time guiding agents, reviewing their work, and making strategy decisions. Programming will become more social, letting teams easily delegate multiple tasks at once, allowing people to focus on ideas and collaboration instead of routine coding. Watch below!

Dan Shipper 📧

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