Dan

Incredibly excited to say Twist! Is live. An AI party game where you submit a photo, prompt a friends, and go up against your friends in a hilarious head to head showdown! This build in public journey has been fun and excited to keep sharing the adventure with you all!

What isn’t priced into Anthropic’s or OpenAI’s gigantic valuations is that they have no moat. I use both ChatGPT Pro and Claude Max, and we’re reaching the point where there’s very little practical difference between Codex, Claude Code, GPT-5.5, and Opus 4.7. That tells me the long-term value won’t sit in the model or harness layer. Those layers will become commodities, with pricing pushed down to token cost plus a thin margin.

@infleqtion @grok how does the stock not react positively to this news?

Infleqtion has been awarded a Phase II contract by the U.S. Navy to advance QuIRC, our Quantum-Inspired Rapid Context machine learning platform for RF signal processing. QuIRC is designed to reduce the data needed to be stored or transmitted in dense, dynamic RF environments while preserving critical info: infleqtion.com/infleqtion-awa…

@chamath I know in my experience most consumer sites see most usage from mobile. Is this different for enterprise software?

Apparently enterprise software companies need good websites. Ours sucks and conversion showed it. So we put a bunch of changes into an auto research loop and then shipped it. New site is live. If you click, it worked! 8090.ai

@Jason I’m in

We started an AI founder twitter group... reply with "I'm in" if you're a founder and want to be added

@karpathy Is this not how deep research operates?

LLM Knowledge Bases Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So: Data ingest: I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them. IDE: I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides). Q&A: Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale. Output: Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base. Linting: I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into. Extra tools: I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries. Further explorations: As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows. TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.

Tonight, millions of Jews gather at the Seder table to retell the story of Passover. A story of slavery to freedom. Of questioning everything. Of refusing to accept the world as it is. For over 3,000 years. Same night. Same ritual. Not to look back. To carry it forward. Wishing you a beautiful night with family, friends, and a full table. Chag sameach.

@SullyOmarr It helped me build a hardware MCP and Claude can poll the dashboard it made

Serious question Has anyone even found computer use remotely useful? It’s way to slow and expensive for how mediocre it is

So Claude controls my home now

I built a hardware MCP agents, watch as I build a smart home powered by Claude

A smart home powered by Claude!

@AlexFinn This also poses a risk to the build in public strategy if you’re not operating with the best tools

In a few weeks the most powerful AI model of all time Claude Mythos will release This makes me deeply nervous Not because of cybersecurity risks or anything like that But because it will quite obviously be significantly more expensive which will cause the wealth gap to explode Let me explain First the obvious: tokens aren’t getting cheaper. In fact, they’re getting significantly more expensive Almost every new version of ChatGPT and Claude brings a slight bump in price over the last one And plans haven’t been going down either, they’re only coming out with more expensive ones. ChatGPT Pro plan for $250 a month. Claude Max for $200. GPUs, RAM, CPUs all going up in price. And now Mythos, which the leaked blog post hinted won’t even be included in a plan. It will only be in the API for what will be an astronomical cost. And do you seriously doubt this won’t lead to an upcoming $2,000 a month Ultra plan that every other AI company will immediately copy? It’s one thing to make luxury items more expensive. It’s another thing to make intelligence more expensive. Intelligence that is critical to getting ahead in a crumbling economy. Let’s just call it what it is: using AI gives you an advantage against everyone else. Those with AI are keeping their jobs. Those not using AI are losing their jobs Now a new level of intelligence that will only be accessible to the rich is coming out. Only the rich will be able to use this super intelligence to create more economic value than others. What happens to the people that can’t afford Mythos? Or ChatGPT 6? They are left with a major disadvantage in the economic battlefield. Then on top of that, both OpenAI and Anthropic are going to IPO this year (it’s killing the middle class that this didn’t happen years ago, but that’s another story) They both are heavily incentivized right now to explode revenue as much as they can. They both are incentivized to make these new models as expensive as humanly possible. The middle class is already gutted. A middle class without access to the intelligence that the upper class will have will only gut them further. If a job position is between someone in the middle class with Claude Sonnet, and someone in the upper class with Claude Mythos, the Claude Mythos candidate with 100% get the job. It’s like a ballet dancer getting in a weight lifting competition with someone on insane amounts of steroids. Or say someone with Claude Opus has a genius idea for a business, and someone with Claude Mythos gets the same one. The one with Claude Mythos will release a significantly better product much much faster, crushing the person with Opus. I’m very pro-capitalist. In fact, I might be a radical capitalist. But at the same time this country (and this world) needs a middle class. I don’t know the answers or solution. There probably isn’t one. I honestly don’t even know what I’m trying to achieve with this post. I just have gotten incredibly scared over the last few days thinking about this scenario. I think the best plan of action at the moment is to just create as much economic value as you possibly can right now. (Ethically) earn as much money as possible. Save everything. If you want to compete in the future, you’re going to need to be able to afford the top tier intelligence. It’s critical for you and your family to survive. But in the meantime, don’t let anyone tell you intelligence is going to become “too cheap to meter”.

@AlexFinn @grok how well quickly do open source models catch up to a SOTA release and at what cost ratio

Coming soon, eyes and ears for AI agents :)

My AI agent just retired my Google home. I built a sensor MCP connected sensors to wifi and now Claude lives inside my home. Turning lights off, security checks, baby monitoring!

My openclaw has eyes

You’re looking at my open claw existing in the real world. Say hi! I hooked it up to an ESP32 a microphone and built a sensor MCP and now Claude has access to eyes and ears. It’s really cool and creepy!

Day 2 of my hardware project. Giving Claude senses. Today we officially met

I just met my claude agent after giving him eyes

Day 1 of openden complete. I made an MCP for my open claw giving him eyes, ears, temperature sensor, motion detector and air quality sensor. He’s loving sensing the real world. Smart homes are actually going to become a reality with agents, stay tuned!

@nroute_ Thanks, still a work in progress but initial results have been awesome

@DanielFluxman Damn, this is pretty cool!

First hardware project is giving Claude eyes and ears. The results are epic, will share build guides soon!