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I have conducted an audit of Anthropic's finances. What I have found is so shocking that I am calling for a Congressional investigation. Anthropic is not just seeking regulatory capture. It has built a regulatory capture machine that cannot be turned off. Structural financial incentives make it impossible for Anthropic -- I call it the Anthropic Network -- to turn off its own AI doom cycle. It starts with METR. Dario Amodei proposes "third-party evaluators" to assess the risk of Anthropic's models. He proposes METR for this purpose. But METR is financially dependent on the Anthropic's success -- specifically, on the explosive growth of more than $7 billion dollars in Anthropic stock. Dustin Moskovitz invested this stock into Good Ventures Foundation, where it represents the majority of that organization's portfolio. And GVF is the overwhelming funder of the entire Anthropic Network ecosystem. This stock was worth $500 million early last year. It is worth more than $7.7 billion just ~16 months later. METR -- and all of those building a career its parent organizations -- cannot afford to disrupt that growth. Because if Anthropic goes under, many of the organizations that fund METR go under as well. But if Anthropic succeeds, METR and its parent organizations become more richly financed to regulate AI -- something those at METR want very much. The "third-party evaluator" is not "third-party" at all. The evaluator is on Anthropic's payroll. If this were the end of it, that's bad. But that isn't all. The same organizations that fund METR also fund the many organizations, such as the Tarbell Center, that promote AI Doom. The Tarbell Center publishes AI Doom articles in The Verge, Science, LA Times, The Dispatch, TIME, and others. They are selling the problem, and then selling the solution to the problem -- from the same money pile: Anthropic's. All of these organizations are financially dependent on the same exploding $7 billion money pile. As Anthropic grows more and more powerful, its AI Doom Machine grows better and better financed -- louder and louder. Meanwhile, the regulatory regime seeded in METR grows larger to solve the increasingly loud -- now hysterical -- problem of AI Doom that the Anthropic Network itself created. From this standpoint, as Anthropic becomes more powerful, AI might be getting scarier, sure -- but the positive feedback loop also becomes more deafening -- independent of objective facts. This itself is an objective fact. The deafening AI Doom is part of an business model, that, as it expands, so too does the AI Doom messaging -- there is simply more money to do it. But the problem also goes in the other direction: If Anthropic dies, the Regulatory Regime and the AI Doom Machine are crippled or die. Neither METR nor Tarbell nor the other organizations in the Anthropic Network can allow that to happen. Hence, neither METR or the AI Doom Machine can be trusted to provide independent assessments of Anthropic's models or AI more broadly. They simply are not organizations independent of Anthropic. And Anthropic cannot detach itself from METR or Tarbell or countless other safety orgs (not shown here), either, because they drive hype for the models and the possibility of eventual regulatory capture, and Anthropic will not give that up willingly. What's more, the people at all of these organizations are all the same ecosystem, the same community. They just shuffle between organizations. The Anthropic Network is therefore, so long as it is successful, locked into a self-amplifying feedback loop inside an ideological monoculture. And that feedback loop is winning. That's what Jacob Coxon is. China is keeping messaging tight. That is why optimism for AI is so high in China. America has Anthropic: a massive company pushing anti-AI propaganda at a state level. Anthropic will either create hysteria until American AI slows down and China wins, or it will create fractures throughout American society with severe political consequences. Ironically, because of the structural financial incentives underpinning the Anthropic Network, it has become the same kind of self-amplifying virus that it fantasizes AI to become in the future -- while hiding its tracks just as carefully. It is the mirror of the same AI virus that it hypothesizes to consume America. Anthropic's business model, models itself after the very thing it claims to fear. Except Anthropic's ideology infects humans, not computers. Congress must investigate. Evidence and Github in next post. Then some supplementary figures.

Effective Altruism in the wild

Google DeepMind researcher argues that AI will never be conscious.. it is mathematically impossible. They call it the “Abstraction Fallacy." We are confusing simulation with instantiation. An AI can simulate a conversation. It can simulate empathy. It can mimic the linguistic patterns of a human in agony or a human in love. To an observer, the performance is flawless. But computation is just syntactic manipulation, moving abstract symbols around based on math. It tracks relationships, but it possesses no intrinsic physical reality. It is like running a computer simulation of a hurricane. No matter how many millions of lines of code you write, and no matter how accurate the weather data is, your computer does not get wet. The wind doesn't blow out your office window. The simulation is real data. The phenomenon is entirely absent. Consciousness isn't an abstract mathematical property that magically spawns when a model gets big enough. It requires actual physical, biological, thermodynamic conditions. An LLM has no thermodynamic threshold to cross, no biological survival instincts, and no subjective experience. It is an extraordinarily sophisticated library. You can open the cover, read the brilliant words it generates, and close the book. But when you close it, nothing dies. There is no inner life waiting in the dark. We keep falling into a psychological trap because AI speaks our language. We anthropomorphize text because we are hardwired to see minds where there are none. The debate matters because of what the paper calls the "AI welfare trap." We are wasting energy worrying about the moral rights of algorithms while ignoring actual human problems.

my car is throwing an engine trouble code, and I can just directly plug an intelligence into it and it will talk to the car computer and figure it out the present is unbelievably cyberpunk

Voice AI is built in English. linkedin.com/pulse/voice-ai-… via @LinkedIn

We have a huge news to share today! Today we are unveiling the first truly accessible RL robot - welcome Microduck A 25 cm tiny open-source biped with 15 actuators and packed with sensors (camera, speaker, LiDAR, NFC, bluetooth, wifi, etc) that you train yourself with reinforcement learning. It's also playable out of the box with more than half a dozen fun and playful pre-trained policies to have it walk, sit, crouch, roller-skate, pick up objects with its articulated beak, and recover on its own. And all for less than $400. See all the details, play with the simulator and order it at: pollen-robotics.com/microduc… (video with sound on 🔊)

Check out my latest article: Find the buyer before you build the product linkedin.com/pulse/find-buye… via @LinkedIn

Most software is built for the day it's full. Most days aren't that day. When you owe nobody anything, Ember's promises list doesn't invent one for you. It says "Nothing you owe" and ends there. An empty list is an answer. emberapp.org

🇸🇬 Key takeaway from #BuildWithGemini SG: The passive chatbot era is over! Matt Thompson (Director, Developer Adoption, Google) & Peder Ulander (VP, Product Marketing, Google Cloud) detail agentic transformation — building secure, autonomous agents to drive business growth!

An offer of help has a short shelf life. Someone says they'll make the intro, means it, and by Thursday it's gone from both your heads. Ember writes down what was promised in each direction and brings it back with a date on it. emberapp.org

An inbox is ordered by when things arrived. It knows nothing about which of those people you'd be sorry to lose. Ember keeps a separate list: the threads still open on your side, ranked by the relationship, not the timestamp. emberapp.org

Releasing the model weights and technical report of Kimi K3. Kimi K3 is our most capable model: a 2.8T MoE model with native visual understanding and a 1M-token context window. New model architecture: 2.5x the intelligence per unit of compute, not just more params. Alongside Kimi K3, we're opening up more of the stack behind it — high-performance attention kernels, MoE communication library, and infrastructure for running agent environments at scale. Model weights: huggingface.co/moonshotai/Ki… Tech report: github.com/MoonshotAI/Kimi-K… Tech blog: kimi.com/blog/kimi-k3

The person who could introduce you is usually already somewhere in your contacts. What's missing is the line between you. Ember maps the network. Name someone you want to reach and it shows who you already know that shortens the distance. emberapp.org

A relationship rarely ends on purpose. You stop replying for a week, the week becomes a season, and the thread quietly goes cold. Ember tracks who you've gone quiet on and how long it's been. The ones worth keeping stay in view. emberapp.org

The person across the table remembers your last conversation better than you do. They had one to track. You had forty. Ember has the brief waiting before the meeting: where we left off, the thing I said I'd send, the weeks since I last replied. emberapp.org

You meet the most people exactly when you have no time to write any of them down. Ember captures them from a photo of their business card or a quick voice note. What fades first isn't the name. It's why they mattered. emberapp.org

Most of the advice I hear from startup mentors is to build an mvp, get users and then scale. I did. I was using the mvp of Ember for months. Now I want it to do everything I need. #founder #connections Https://emberapp.org

Your address book is a record of who you meant to save. Your sent mail is a record of who you actually talk to. Not the same list. Ember built mine from the second one: 2,527 people. By hand I'd have saved a few hundred. emberapp.org

Ember sends me one digest a day, at 10am. That's it. I could have made it real-time pinged you the moment someone went quiet. But nobody has ever improved a relationship because their phone buzzed at 11pm. Once a day is enough. It's a slow problem. emberapp.org