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<div style="display: none; max-height: 0px; overflow: hidden;">Meta has agreed to acquire Manus, a Singapore-based company that conducts deep research and performs tasks for paying users </div>
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<h1><strong>TLDR <span id="date">2025-12-30</span></strong></h1>
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<strong>Meta Buys AI Startup Manus for More Than $2 Billion (4 minute read)</strong>
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Meta has agreed to acquire Manus, a Singapore-based company that conducts deep research and performs tasks for paying users. Meta will continue to operate and sell Manus' services while integrating it into its suite of social media products. The deal will help Meta cement its position in the product segment of AI agents. It is one of the first times a major US tech company has bought a startup with Chinese roots.
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<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.theregister.com%2F2025%2F12%2F29%2Fnvidia_intel_5_billion%2F%3Futm_source=tldrnewsletter/1/0100019b6efb0d82-60c7e19b-cfaf-4e24-9b15-b6c70dd40f3b-000000/kqm1KpKI8D7q2I6WWE55mDvaRmM3HJ4n2lY3810lli8=437">
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<strong>Nvidia spends $5B on Intel bailout, instantly gets $2.5B richer (4 minute read)</strong>
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Nvidia locked in a purchase price of $23.28 per share for Intel when the companies struck a deal in September. The deal had been under scrutiny by the US Federal Trade Commission, but was then greenlighted on December 18. The purchase of 214 million shares closed on December 26, and Intel shares closed Monday at $36.68, making Nvidia's $5 billion purchase worth $7.58 billion. The deal will involve the companies jointly developing multiple generations of chips for datacenters and PCs.
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<strong>Researchers make “neuromorphic” artificial skin for robots (5 minute read)</strong>
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Chinese researchers have created an artificial robotic skin that can sense pressure and locate input and injuries. The neuromorphic robotic e-skin (NRE-skin) is assembled from a collection of segments that snap together using magnetic interlocks, automatically linking up any necessary wiring. Each segment broadcasts a unique identity code, so it is relatively easy to pop out the damaged segment and replace it with fresh hardware if the system identifies damage.
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<strong>Clinic-in-the-Loop (16 minute read)</strong>
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Biomedical progress has become less productive for the last several years despite staggering advances in basic science. One of the reasons for this is that institutional bureaucracy has become harder to overcome. Increasing the number and efficiency of clinical trials would help create a faster feedback loop and result in better data to inform models and ideas. This could help decrease the cost of bringing new drugs to market and break a trend that has held since the 1950s.
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<strong>Why we are leaving restrictive diets in 2025 (Sponsor)</strong>
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Pressure. Extreme diets. All-or-nothing mindset. This doesn't need to be you on 01/01. <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fsimple.life%2Fsurvey%3Futm_source=affiliateemail%26utm_medium=affiliate%26utm_campaign=tldr%26adgroup_id=newsletter%26safe=true/2/0100019b6efb0d82-60c7e19b-cfaf-4e24-9b15-b6c70dd40f3b-000000/cs9vzwZNJF7O9uxBAvQibNP72yUAVE3VQz6DimQBy84=437" rel="noopener noreferrer nofollow" target="_blank"><span>There is a clinically proven weight loss tool</span></a> that's helped users lose over 18 million pounds. Take a quick quiz and get a science-backed plan built just for you—plus Blinky, a Tamagotchi-style accountability buddy that keeps you on track. It's crazy effective. Get your <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fsimple.life%2Fsurvey%3Futm_source=affiliateemail%26utm_medium=affiliate%26utm_campaign=tldr%26adgroup_id=newsletter%26safe=true/3/0100019b6efb0d82-60c7e19b-cfaf-4e24-9b15-b6c70dd40f3b-000000/DdgfuPsd-s44QfrjjKry1FToY8BQPoVer6DI46Oqh-c=437" rel="noopener noreferrer nofollow" target="_blank"><span>personalized plan for at least <strong>50% off</strong></span></a>.
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<strong>Welcome to the Machine, a guide to building infra software for AI agents (20 minute read)</strong>
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The primary users of infrastructure software are rapidly shifting from developers to AI agents. AI uses systems very differently from how developers do, and it changes many long-held assumptions about how databases should be used. Many things developers took for granted need rethinking. The focus of engineers is shifting from perfected individual systems to designing foundational capabilities that AI can use at scale, iterate on, and run cheaply.
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<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fdenislavgavrilov.com%2Fp%2Fclopus-watcher-an-autonomous-monitoring%3Futm_source=tldrnewsletter/1/0100019b6efb0d82-60c7e19b-cfaf-4e24-9b15-b6c70dd40f3b-000000/ksMQPLGNPt4YSXP0vOoauOCXhdYYYK0aMR-GXmxvESw=437">
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<strong>Clopus-Watcher: An autonomous monitoring agent (8 minute read)</strong>
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AI will likely make 24/7 on-call a thing of the past. 24/7 monitoring is a lot simpler than the development process. There are often reference documents that engineers can follow to bring systems back up, and if they fail, there's always a backup and recovery plan in place. On-call jobs have always been more systematic. This post introduces an autonomous monitoring agent that does what an on-call engineer would do, but autonomously, forever.
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<strong>Capital in the 22nd Century (58 minute read)</strong>
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Labor and capital have traditionally complemented each other. While wealthy people can keep accumulating capital, it becomes less valuable when there aren't enough hands to use all of it, and hands grow more valuable when capital is plentiful. However, this correction mechanism breaks in the world of advanced robotics and AI. A global and highly progressive tax on capital (or at least capital income) may be the only way to prevent inequality from growing extreme.
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<strong>2025 in Review: Jagged Intelligence Becomes a Fault Line (10 minute read)</strong>
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The immediate AI risk comes from people overestimating AI's capabilities. A lack of reliability and trust is preventing wide adoption. There is a growing AI perception gap between quantitative users and qualitative users. AI leaders aren't even attempting to explain how AI works because it's complicated, and they're also incentivized to oversimplify and overpromise.
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<strong>All expertise grows logarithmically, not exponentially (6 minute read)</strong>
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