Startups & Ventures

🎓 MIT drops a free course on AI agents, theory and real-world practice The folks at MIT have released a free, comprehensive course on AI agents, covering both fundamentals and applied use cases. 🔸 AI agents, what they are, how they differ from chatbots, and where they actually make sense. 🔸 Planning, task decomposition, decision-making loops, and agent control logic. 🔸 RAG (Retrieval-Augmented Generation), grounding agents in external knowledge and tools. 🔸 MCP (Model Context Protocol), structuring context, memory, and tool access for scalable agents. 🔸 Examples & case studies, real implementations, not just academic theory. 🔸 Designed as a practical base for anyone building agentic systems in production.

MIT isn’t just teaching how to talk to models, it’s teaching how to make AI act, which is quickly becoming the most valuable skill in applied AI.

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🔥 A 10-hour fireplace turned into a full-time income There’s a YouTube channel with a single video: ten hours of a burning fireplace. No edits, no commentary, no updates. That one video brings its creator around $180k usd a year. Sometimes the smartest business model is realizing people just want something calm playing in the background. Anyway, holiday’s over. I’m back to work tomorrow. 📊 Powered by Crypto Insider

🔥 A helmet straight out of Cyberpunk Looks like gear worn by NPCs in Night City but it’s real. This is Alpha Wave, a futuristic bicycle helmet from Also, and it’s packed with unconventional safety tech. 🔸 The core innovation is the Release Layer System, an alternative to classic MIPS. 🔸 Under the outer shell panels sits a layer of tiny polycarbonate balls. 🔸 On impact, a special adhesive releases the shell panel at the contact point, allowing it to roll freely in any direction and then detach. 🔸 This movement dissipates rotational energy, the kind that usually gets transferred directly to the brain. 🔸 The chin strap is redesigned too. The HighBar system replaces the usual Y-straps with rigid mounts, flexible straps, and a one-handed adjustment wheel under the chin, usable even with gloves. 🔸 Lighting is built in: • 200-lumen headlight up front • 75-lumen work light for digging through a backpack in the dark • Rear light wirelessly syncs with Also’s TM-B electric bike 🔸 Audio is fully integrated: • 4 speakers with wind protection • 2 noise-canceling microphones for calls and navigation prompts 🔸 Specs: IPX6 water resistance, USB-C charging. 🔸 Price: $250, not cheap, especially since a serious impact means full replacement. 🔸 Pre-orders open soon, with delivery starting early next year.

It’s expensive, disposable after a crash, and unapologetically futuristic but when it comes to your head, everyone decides for themselves what protection is worth.

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When AI finally runs the world, you’ll know exactly where to point the finger. P.S. GPUs owe their existence to games like Quake and Half-Life 2. Even Demis Hassabis, now leading AI at Google, began as a game developer. Turns out the gaming industry wasn’t just entertainment, it quietly laid the groundwork for modern AI, and its role is still massively underestimated. 📊 Powered by Crypto Insider

⚡️ China’s superconducting maglev hits 700 km/h in a 400-meter sprint Chinese engineers from the National University of Defense Technology (NUDT) accelerated a monocoque test vehicle to 700 km/h and back to zero on just a 400-meter track, setting a new benchmark for superconducting maglev systems. 🔸 The acceleration reached ~10 g, well beyond what even trained fighter pilots can tolerate; braking peaked at around 5 g, confirming this is a tech demo, not a passenger vehicle. 🔸 The system uses high-temperature superconductors, cooled with liquid nitrogen to −196°C far simpler and cheaper than classic liquid-helium superconductors at −269°C. 🔸 This makes the setup more practical for real-world infrastructure, while still enabling extreme speeds and stability. 🔸 The stated next milestone is 1,000 km/h, faster than the cruising speed of commercial passenger aircraft. 🔸 At that speed, a Shanghai–Beijing trip could theoretically drop to ~2 hours, versus ~14 hours by car today. 🔸 China already operates the world’s only commercial high-speed maglev: the Shanghai Maglev, which covers 30 km in 7–8 minutes at up to 431 km/h.

China isn’t just experimenting with futuristic transport, it’s systematically pushing maglev toward air-travel territory, where trains start competing with planes rather than cars.

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🔥 Claude Code is now writing 100% of its own code and its creator let it happen Claude Code’s lead developer has admitted that every single contribution over the past 30 days was written by Claude itself not as an experiment, but as normal workflow. 🔸 The developer is Boris Cherny, widely regarded as the original creator and “founder” of Claude Code, which began as his side project in 2024. 🔸 In the last month alone, Claude Code: • shipped 259 pull requests • made 497 commits • added ~40,000 lines of code • deleted ~38,000 lines, with every line generated by Claude Code + Opus 4.5. 🔸 The human role has shifted to orchestration: prompts, reviews, architecture decisions not typing code. 🔸 Claude can now run continuously for minutes, hours, even days, using Stop hooks to manage long-lived development loops. 🔸 This isn’t toy automation or autocomplete, it’s end-to-end software production at scale, driven by the system itself. 🔸 What started as a side project has quietly become a proof point for a new programming paradigm.

Software development is crossing from human-written with AI assistance to AI-written with human supervision and this is likely the slowest this transition will ever be.

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🔒 Google released a mega-guide with 40 tips for working with modern AI models Google compiled a practical playbook for using today’s most hyped neural networks, essentially a year’s worth of AI learnings packed into one guide. 🔸 The guide includes non-obvious Gemini 3 features, showing where it outperforms expectations and how to unlock hidden capabilities. 🔸 It collects AI tools, prompt patterns, and workflows that go beyond basic chat usage aimed at real productivity gains. 🔸 Many tips focus on combining models and tools, not treating any single AI as a silver bullet. 🔸 The recommendations are task-agnostic: writing, coding, research, planning, analysis, and creative work all fit the framework. 🔸 A recurring theme is leverage how small prompt or setup changes can lead to disproportionately better outputs. 🔸 The guide positions AI less as a chatbot and more as a programmable co-worker that rewards structured thinking.

AI skill is no longer about knowing which model is best, it’s about knowing how to extract leverage from any of them.

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📺 LEGO TV recreates the hidden guts of a 1960s CRT set A LEGO enthusiast has gone beyond retro styling and rebuilt what actually lived behind the back panel of old televisions, down to the physics. 🔸 Creator FMDavid designed a LEGO TV that isn’t just a shell, but a full internal reconstruction inspired by real 1960s cathode-ray televisions. 🔸 The model features a large CRT tube dominating the interior, with surrounding deflection coils that, in real TVs, steered the electron beam across the screen. 🔸 Inside are LEGO versions of vacuum tubes, capacitors, transformers with cooling fins, and detailed color wiring between components. 🔸 The back panel even includes RCA connectors, reinforcing the illusion that this is a functional analog device. 🔸 The screen is convex, not flat a subtle but accurate detail, since real CRTs needed curved glass to withstand atmospheric pressure against the vacuum inside. 🔸 The project is now live on LEGO Ideas; if it reaches 10,000 votes, LEGO may consider turning it into an official set.

This isn’t just nostalgia, it’s a reminder that past tech was physical, visible, and mechanical, and that understanding how things worked can be just as compelling as sleek modern design.

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🧠 Andrey Karpathy says he feels like a lagging programmer in the AI era Former OpenAI and Tesla AI leader Andrey Karpathy shared a candid reflection on how AI is radically reshaping what it means to be a programmer and why even top engineers now feel behind. 🔸 Karpathy says human contribution to code is becoming sparse and fragmented, with large parts delegated to AI systems rather than written directly. 🔸 He believes he could be 10× more productive if he fully mastered the new AI tooling stack that has emerged just in the last year and calls his inability to do so a skill issue. 🔸 A new abstraction layer has appeared on top of traditional software engineering: agents and subagents, prompts, contexts, memory, modes, tools, plugins, skills, hooks, MCP, LSP, slash commands, IDE integrations, and workflows. 🔸 Developers now need a mental model of stochastic, error-prone, constantly changing systems very different from deterministic software yet deeply intertwined with classic engineering. 🔸 Karpathy compares AI to a powerful alien tool with no manual, where everyone is forced to experiment in real time while the profession undergoes a magnitude-9 earthquake. 🔸 His advice is blunt: roll up your sleeves, because the pace of change means standing still is falling behind.

Karpathy’s post reads less like a complaint and more like a warning: programming isn’t dying but the old mental models are, and even the best engineers now have to relearn the craft from scratch.

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When the robot rebellion begins, no one will know, but there will be signs 📊 Powered by Crypto Insider

🧠 A 33,000-skill “brain” for AI agents is emerging A massive, structured skill database is being built for Claude Code, OpenAI Codex, and ChatGPT, allowing neural networks to be explicitly taught new capabilities instead of relying on ad-hoc prompts. 🔸 The database contains 33,000+ distinct skills spanning automation, software development, research, data workflows, and operational tasks. 🔸 Each skill comes with clear instructions, constraints, and expected behavior, making them reusable rather than one-off prompt hacks. 🔸 A search engine and filters make it possible to quickly find the right capability by domain or use case. 🔸 Skills are linked to real sources on GitHub and documentation, grounding them in practical implementations. 🔸 The system is designed to plug directly into agentic workflows for coding agents and autonomous AI systems.

This marks a shift from prompt engineering to capability engineering where AI systems are upgraded by importing skills, not rewriting prompts.

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🐬 Disney’s quiet bet on aquatic robots Disney has been developing robotic aquatic creatures for years and what started as simple underwater tech is now starting to look like a full replacement for live-animal shows. 🔸 Disney’s work on aquatic robots began over 20 years ago, initially as basic underwater drones with motors for vertical and horizontal movement closer to radio-controlled vehicles than lifelike robots. 🔸 Around 2020, Disney shifted toward biomimetic designs, unveiling dolphin-inspired robots that used fins instead of propellers, dramatically improving fluidity and realism. 🔸 By 2025, Disney introduced near-autonomous hydrofoil-based aquatic robots equipped with GPS, ultrasonic sensors, and self-balancing systems. 🔸 These robots are currently designed for live shows inside Disney parks, where predictability, safety, and choreography matter more than full autonomy. 🔸 Disney says the designs are inspired not only by real marine animals, but also by fictional creatures from Avatar: The Way of Water, blending biology with cinematic imagination. 🔸 The implication is hard to miss: realistic robotic animals offer spectacle without ethical backlash, training costs, or regulatory pressure.

What you’re seeing isn’t just a theme-park experiment, it’s an early glimpse of a future where dolphinariums are replaced by code, sensors, and storytelling instead of live animals.

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📚 Hugging Face’s free ML courses, perfect for New Year learning Hugging Face has expanded its library of free machine learning courses, collecting 12 updated offerings in one place, a great way to dive into AI over the holidays. 🔸 Courses include: • LLM Course (highly recommended) • Robotics • MCP • Post-training techniques (small course) • Agents • Deep Reinforcement Learning • Computer Vision • Audio • Open-Source Cookbook (not exactly a course, but very useful) • ML for Games • Diffusion Course • ML for 3D

Whether you’re a beginner or looking to specialize, these hands-on, updated courses provide a structured way to learn state-of-the-art ML techniques for free.

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🗣️ Jeffrey Hinton says the era of AI scaling is over Jeffrey Hinton argues that traditional scaling is hitting a wall, not because of compute, but because the free internet data used to train models is largely exhausted. 🔸 According to Hinton, the most valuable remaining data now lives inside closed corporate systems, inaccessible for large-scale training. 🔸 This makes simply training bigger models on more scraped data increasingly ineffective. 🔸 His bet is on synthetic data, models generating their own training data as part of the reasoning process. 🔸 Hinton points to AlphaGo, which surpassed humans by playing against itself rather than relying on human examples. 🔸 He believes LLMs can follow the same path, using self-generated data to improve reasoning and exceed human intelligence.

The next leap in AI won’t come from more data or bigger models, but from models that learn by thinking.

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⬇️ One tool to download videos from almost anywhere A new free utility makes it possible to download videos from nearly the entire internet locally, fast, and without relying on cloud services. 🔸 Supports 1,000+ platforms, including YouTube, TikTok, Twitch, Vimeo, Kick, and more. 🔸 Lets you download only specific segments, not the full video. 🔸 Handles multiple downloads at once, no need to queue manually. 🔸 Includes quality selection, from low-res to the original source. 🔸 Can download subtitles alongside the video. 🔸 Supports auto-downloading new videos from a feed or channel. 🔸 Runs entirely locally, no accounts or cloud processing. 🔸 Has a browser extension, one click and the video is saved.

This feels like a “Swiss army knife” for video downloading: simple on the surface, but surprisingly powerful under the hood.

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🗣️ Sam Altman on competing with Google Sam Altman argues that OpenAI’s window to challenge Google opened because the incumbent moved too slowly and now the gap is harder to close. 🔸 In 2023, Google could have easily crushed OpenAI if it had treated the startup as a real threat and fully focused on AI. That moment passed, and catching up is now much harder. 🔸 Google’s distribution advantage is enormous, but Altman believes OpenAI can still win on product quality and speed of iteration, where smaller, more focused teams move faster. 🔸 He calls Google’s ad-driven search business the best business model in tech but also a trap. It makes it extremely difficult for Google to disrupt itself with a radically new AI-first product. 🔸 OpenAI, by contrast, has little to lose. It can afford to rethink interfaces, workflows, and pricing from scratch without protecting legacy revenue. 🔸 Despite this, Altman says Google remains the most dangerous competitor. To stay ahead, OpenAI plans to build a full-stack AI platform: models + infrastructure + devices and interfaces.

This isn’t a fight about who has more data, it’s about who’s willing to cannibalize their own business first.

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⚠️ Microsoft wants to eliminate C and C++ and replace them with Rust by 2030 Microsoft is outlining an ambitious long-term goal: phasing out all C and C++ code across its software stack and moving to Rust, a safer systems programming language designed to prevent entire classes of security bugs. 🔸 A senior Microsoft engineer said the internal objective is to remove every line of C and C++ by 2030, replacing them with Rust wherever possible including core systems software. 🔸 The motivation is security: memory-safety issues account for the majority of serious vulnerabilities in large codebases, and Rust eliminates many of these problems by design. 🔸 The plan is not a manual rewrite. Microsoft is betting on automation, tooling, and AI-assisted code translation to migrate massive legacy codebases at scale. 🔸 Microsoft has already been introducing Rust into parts of Windows, Azure, and security-critical components, making this a continuation rather than a sudden pivot. 🔸 Important nuance: this is a long-term engineering goal, not a guaranteed company-wide mandate. Some teams and legacy components may keep C/C++ where Rust isn’t practical.

This isn’t about fashion or developer preference, it’s about reducing systemic risk. If Microsoft succeeds, it could redefine how the entire software industry thinks about legacy code and security.

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🧠 Promptschat is building a library of ready-to-use AI prompts A growing collection called Promptschat is positioning itself as a one-stop archive of prompts for virtually any neural network and use case from serious technical work to pure creativity. 🔸 The library contains hundreds of prewritten prompts, covering coding, analysis, writing, design, marketing, and experimental use cases. 🔸 Some prompts are long, structured “meta-instructions” that effectively turn an AI into a specialist coder or domain expert, not just a general assistant. 🔸 Others focus on creative tasks, storytelling, ideation, tone shifts, and unconventional experiments with generative models. 🔸 The core value is speed: instead of reinventing prompts, users can copy proven frameworks that already produce strong results.

Promptschat reflects a broader shift: as models become more powerful, prompt engineering is turning into reusable intellectual infrastructure, not just a personal skill.

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🔥 Huawei built a 19th-century European city for its employees Huawei’s office campus in Dongguan doesn’t look like a tech headquarters at all. Instead of glass towers, the company built 12 blocks styled after classic 19th-century European architecture, turning the workplace into something closer to a historic city. 🔸 Huawei deliberately rejected modern glass-and-steel offices, arguing that uniform corporate architecture suppresses creativity and long-term thinking. 🔸 The campus prioritizes natural spaces, walkability, water, and classical design, avoiding the clichéd “futuristic” aesthetic common in tech campuses. 🔸 Employees move between buildings via streets, bridges, and gardens more like a town than an office park. 🔸 The idea is cultural as much as functional: calm environments, human scale, and beauty as productivity infrastructure.

The result looks less like Big Tech and more like a European capital from the 1800s which might explain why some call it the best office in the world.

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