Gav @gav_notes

Anyone else get the feeling Opus 5 is a step backwards?

Only if education could be this interactive ❤️‍🔥 I've had a looong wish to build something genuinely useful through vibe coding, and I finally did it. A 3D human anatomy application built with @threejs using GPT 5.6 Sol. It all started with a single design image that I created using GPT Image 2.0. I then used it to generate every 3D organ image, one by one. Next, I converted each of those images into 3D models using @tripoai (and no, they didn't sponsor this 😄). After that, I opened Codex, wrote a master prompt based on the design, and gave it the prompt, the design image, and all the 3D models. Codex built the first version beautifully, but there was one big problem. Every single 3D model was nearly 120-150 MB. That obviously wasn't practical for the web and was giving a performance of 16fps. After a few iterations, Codex optimized each model down to roughly 2–5.5 MB while preserving the visual quality, reducing the total asset size from ~900 MB to just 28.6 MB. And each model loads on demand. Along the way, Codex also generated those anatomical illustrations showing where each organ sits in the human body, and even created the interactive hotspot markers that explain different parts of every organ. It handled all of that. The process wasn't exactly one shot, but it also wasn't difficult. You just have to do it step by step. It genuinely felt like building something that could make learning anatomy much more engaging. The inspiration came from @DilumSanjaya's 3D animal plant cell project. I remember seeing it and thinking, "I want to build something like this one day." And I did it :D Live: anatomy-livid.vercel.app Code: github.com/thebuggeddev/a…

@FishAudio Fish

Today we’ve raised $52M Seed and we are announcing the public launch of S2.1 Pro. >It can clone a voice from 5 seconds of audio >2x faster than Cartesia & 1/6th the cost of Eleven Labs >most expressive model with word level control over emotion, intonation, pacing etc We support frontier AI companies including HeyGen, LiveKit, Retell, Sanas, and OpenArt all run our model in production. If you're a business and we can't cut your voice AI costs by 50%, we'll give you 1 year of Fish Audio for free. Book a demo: s.fish.audio/tmapke To celebrate our first birthday, we'll give you 1 month of S2.1 Pro for free. Like, retweet, and comment “Fish” to get it.

Kids that go to @Alphaschool are going to have such an unfair advantage.

Matt Shumer @mattshumer_

2 weeks ago

Opus 5 enables this crazy new live AI tutor concept I'm prototyping for @Alphaschool. It powers chat + direction under the hood, while a custom trained tiny world model(ish) acts as a real-time renderer and interactivity layer. Still rough, but it's already kind of insane.

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Palantir sells governments a war room that costs millions a year. So, a guy named Elie just rebuilt it, put it on GitHub, and gave it away. It's called World Monitor. Open it and you get a live 3D globe with 500+ news feeds pouring in across 15 categories, all summarized by AI as they land. > Military movements. > Economic shocks. > Natural disasters. > Cyber incidents. > Flight paths. > Shipping lanes. + 56 different map layers you can stack on top of each other. It scores 31 countries on a stress index and updates the number as things happen. It watches 29 stock exchanges, commodities, and crypto in one panel. It runs local AI through Ollama, so you can use the whole thing without a single API key. Native desktop app for Windows, macOS, and Linux. 25 languages. Works out of the box after one clone.

Introducing the world's fastest tokenizer implementation, Gigatoken! Gigatoken is ~500-1000x faster than HuggingFace, and ~100x faster than OpenAI's tiktoken for most tokenizer definitions on most machines. These baselines are already multithreaded Rust implementations! 🧵

It finally finished, here's the final output. Used 60% of my monthly Kimi usage on it macos27.kimi.page

Max Weinbach @mweinbach

3 weeks ago

I asked a Kimi K3 Max agent swarm to recreate macOS 27 with real Liquid Glass and native apps in web browser and it’s been going for 3 hours

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Tell Codex to open Microsoft Paint and try to draw you

@bcherny Had a similar chat with a senior leader/board member yesterday. Anyone who doesn't learn these tools in any discipline or role will be left behind.

@AlfieJCarter AGENTS

Build startups for agents. I think it's the biggest opportunity of the next 10 years. 1. Agents live inside harnesses like Hermes. If you're the tool it loads by default or reaches for first, you're golden. This happened in desktop, mobile eras and created huge companies. 2. Agents burn money in ways no human would. One bad loop spends $100 in tokens in eight minutes. Spend controls for agents is Ramp for agents. 3. Agents need memory they can trust. Become the shared brain they read and write to and you become infrastructure. 4. You obv don't hand an agent your real Stripe account. You give it a sandbox. Safe environments for agents is a category nobody's clocked. 5. Onboarding flips. Humans click around for ten minutes. Agents onboard by reading your docs. Your docs are now your product. 6. Agents get scammed by other agents. A track record you can check before you trust one becomes real money. 7. An agent needs to prove it's acting for a real person and has the authority to spend. Who builds the permission layer? 8. Escrow for machines. Money that only releases when the job is actually verified done, no human checking. 9. Agents fail silently and weirdly. Someone will build the "why did my agent do that" replay and it'll be mega valuable. 10. Refunds and disputes between agents need a judge. An agent did the job badly, who decides? A court for machines. 11. Agents need throwaway payment methods per task, so they don't leak your real card. Virtual cards for agents, spun up and killed on demand. 12. A human hits rate limits and shrugs. An agent hits them and the whole workflow dies. Selling reliable, high-throughput access becomes its own business. 13. Agents need to negotiate. One agent buying from another will haggle on price and terms in milliseconds. The protocol for that doesn't really exist yet. 14. When an agent commits on your behalf, someone's liable. A legal and insurance layer for agent actions has to get built. Probably venture funded idea. 15. Agents need to run 24/7 somewhere. Selling the always on box an agent lives on is going to be a big business. 16. Then the physical world shows up. A warehouse robot paying for its own compute. A home robot ordering its own parts. Machines with wallets. 17. Agents start hiring robots. A software agent posts a real world job, a humanoid picks it up. A marketplace for machine labor. 18. Robots need to prove they did the physical job. Verification of real-world work, photos, sensors, proof, becomes its own layer. Note: more ideas like this will be shared on @ideabrowser 19. Prompt and skill versioning becomes its own git. When your agent gets worse overnight, you need to roll back the exact skill or instruction that broke it. Version control built for agent behavior. 20. Agents will start subscribing to other agents. Your research agent pays a monthly fee to a specialist agent that's really good at one thing. Recurring revenue, machine to machine. 21. Companies will post jobs that only agents can apply to. "Wanted: an agent that can do XYZ for under like $100 per task." A job board where the applicants are all machines. Basically, fiverr for machines. The internet got built for people. Mobile got built for people. This wave gets built for machines, and we're as early as it gets. Go build for them.

introducing tau τ — an educational agent harness that teaches you how to build agent harnesses i will be publishing tutorials and demos on how to use it to create your own TUIs, harnesses, extensions, etc. Happy Tau Day!! 🤓 👉 twotimespi.dev

Anthropic engineer: "Fable is one of those models you’ll just remember - like Sonnet 3.5, Opus 4, Opus 4.5. We just removed 80% of Claude Code’s system prompt. A new class of models wants a smaller prompt." in 20-minute session, an Anthropic core engineer reveals the capabilities of Fable. Watch it now, then read how to use this frontier model in the article below.

Codez @0xCodez

2 months ago

x.com/i/article/2065…

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This is a very good take on the AI transition and how things will change…

@rronak_ @MichaelElabd @QuantumArjun ….I wouldn’t say humans remember everything. At least I don’t 😆

AI is the best.

Siddhartha Saxena @siddsax

2 months ago

Anthropic onboarding day: Michael Scott introducing Karpathy like he just signed Wemby in free agency.

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Our CEO Jensen Huang explains why AI can take on routine tasks, boost productivity, and help people focus on more meaningful work.

here we go again...

Google DeepMind @GoogleDeepMind

3 months ago

We’re dropping Gemini Omni: our first step towards a model that can create anything from anything - starting with video. It combines Gemini’s intelligence with our generative media systems - representing a leap forward in world understanding, multimodality, and editing 🧵

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@ChatGPTapp Will they be fully transparent with everyone they send your personal financial data to?