Hi @gmail does the "report phishing" button do anything

"Using a better model for analysis" 🤨 I didn't realize I was using haiku all this time, no idea when claude code snuck this one in rofl.

Diffusion video models but now - **realtime**! Simple video filters are real-time but can only do basic re-coloring and styles. Video diffusion models (Veo and friends) are magic, but they take many seconds/minutes to generate. MirageLSD is real-time magic. Unlike simple video filters, diffusion models actually *understand* what they are looking at, so they can style all parts of the feed intelligently (e.g. putting hats on heads, or light sabers into hands, etc.). And they are arbitrarily steerable, e.g. by text prompts. Customizable, intelligent video filters unlock many cool ideas over time: - transform camera feeds into alternate realities - direct and shoot your own movies, acting out scenes with props. Realtime => instant feedback/review. - vibe code games around just simple spheres/blocks, then use a real-time diffusion model to texture your game to make it beautiful. - style and customize any video feed: games, videos, ... e.g. Skyrim but "MORE EPIC"? DOOM II but modern Unreal Engine quality with just a prompt? Horror movie but "cute, pink and bunnies only"? I don't know! - zoom call backgrounds+++ - real-time try on clothes virtually - glasses: e.g. cartoonify your vision in real time? - we can now build Harry Potter Mirror of Erised, showing the "raw feed" of you in the mirror but augmented with your deepest desires (as inferred by the AI). - I don't know, I'm probably missing the biggest one, so many things! (Disclosure I am (very small) angel investor in Decart, I was excited because imo this technology will get very good very fast and it feels general, powerful but it's also technically very difficult. Congrats on the launch to the team!)

I always learn a lot more from in-depth analysis of few random cases over dashboards of aggregate statistics across all cases. Both projections can be helpful but the latter is disproportionately pervasive.

I often rant about how 99% of attention is about to be LLM attention instead of human attention. What does a research paper look like for an LLM instead of a human? It’s definitely not a pdf. There is huge space for an extremely valuable “research app” that figures this out.

This is what the ideal grocery store looks like. Minimally processed (NOVA Group 1) food only (no "edible food-like substances"), organic, local, fresh. Food should not be more complex than this, yet I don't believe this exists.

my weekend project to learn about bluetooth mesh networks, relays and store and forward models, message encryption models, and a few other things. bitchat: bluetooth mesh chat...IRC vibes. TestFlight: GitHub:

Knowledge makes the world so much more beautiful.

How to build a thriving open source community by writing code like bacteria do 🦠. Bacterial code (genomes) are: - small (each line of code costs energy) - modular (organized into groups of swappable operons) - self-contained (easily "copy paste-able" via horizontal gene transfer) If chunks of code are small, modular, self-contained and trivial to copy-and-paste, the community can thrive via horizontal gene transfer. For any function (gene) or class (operon) that you write: can you imagine someone going "yoink" without knowing the rest of your code or having to import anything new, to gain a benefit? Could your code be a trending GitHub gist? This coding style guide has allowed bacteria to colonize every ecological nook from cold to hot to acidic or alkaline in the depths of the Earth and the vacuum of space, along with an insane diversity of carbon anabolism, energy metabolism, etc. It excels at rapid prototyping but... it can't build complex life. By comparison, the eukaryotic genome is a significantly larger, more complex, organized and coupled monorepo. Significantly less inventive but necessary for complex life - for building entire organs and coordinating their activity. With our advantage of intelligent design, it should possible to take advantage of both. Build a eukaryotic monorepo backbone if you have to, but maximize bacterial DNA.

The race for LLM "cognitive core" - a few billion param model that maximally sacrifices encyclopedic knowledge for capability. It lives always-on and by default on every computer as the kernel of LLM personal computing. Its features are slowly crystalizing: - Natively multimodal text/vision/audio at both input and output. - Matryoshka-style architecture allowing a dial of capability up and down at test time. - Reasoning, also with a dial. (system 2) - Aggressively tool-using. - On-device finetuning LoRA slots for test-time training, personalization and customization. - Delegates and double checks just the right parts with the oracles in the cloud if internet is available. It doesn't know that William the Conqueror's reign ended in September 9 1087, but it vaguely recognizes the name and can look up the date. It can't recite the SHA-256 of empty string as e3b0c442..., but it can calculate it quickly should you really want it. What LLM personal computing lacks in broad world knowledge and top tier problem-solving capability it will make up in super low interaction latency (especially as multimodal matures), direct / private access to data and state, offline continuity, sovereignty ("not your weights not your brain"). i.e. many of the same reasons we like, use and buy personal computers instead of having thin clients access a cloud via remote desktop or so.