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Like when there was an export control on computers above 1 GFLOPS and when the Sony PlayStation-2 came out in 2000, it was above the limit 😅 theregister.com/2000/04/17/p…

Congratulations to Allen Liu, Assistant Professor of Computer Science, who has received the ACM Doctoral Dissertation Award!

We extended the deadline until Jun 15th (AOE)!

BREAKING: In a stunning moment, Donald Trump's former economic advisor just admitted on Fox News that inflation is being driven nearly exclusively by bad decisions that Donald Trump has made. Wow.

Our lineup of speakers is growing! Many more to be announced.... and don't forget to submit your papers, deadline is very soon! More info at wm-booth.org and submission page at openreview.net/group?id=chic…

Together with UC Berkeley we are announcing the laser phase plate - a breakthrough in atomic resolution imaging. This is the brightest continuous wave laser in the world, 100 million times the intensity of the surface of the sun. Phase contrast plays an important role in microscopy, but it was thought close to impossible for electron microscopy, where it would require interfering with an electron beam. Holger Mueller and Robert Glaeser proposed exactly this using a standing wave laser. It has taken over 15 years to make this a reality. Biohub partnered with UC Berkeley and Mueller to support this work and to engineer and build the technology. Contrast has been the critical barrier to achieving atomic resolution imaging of the cell. In cryo-electron tomography, a cellular imaging technology that uses electron microscopy, the low contrast makes it impossible to resolve anything but the largest proteins within their cellular context. The laser phase plate removes that barrier. With advances in AI this breakthrough in contrast will start to open up a new frontier in structural biology, that will allow us to see the molecular machines of the cell, and how they assemble into far more complex and dynamic systems, and understand how they work.

My team loves Claude from @AnthropicAI . But this new policy of retaining prompts and usage is a red line...we simply can't give over our usage. Prompts contain our IP; literally all our design files and docs. Why would this ever have been ok? It's sad because everyone was looking forward to using the new model. Sigh.

TLDR: 1. Declare AI too dangerous for ordinary competition so you propose a regulatory regime where only the largest incumbents can survive 2. Warn about labor displacement while selling the product to executives as a labor-displacement tool 3. Warn about state overreach while asking the state to license and gatekeep frontier models 4. Warn about corporate power while sketching a corporate-state cartel over compute, release, security, export controls, and deployment

Amazing project. We need this now more than ever.

Yann Lecun published the most heretical AI paper of the year. He opens by arguing Magnus Carlsen isn't good at chess and only gets more unhinged from there. The Turing Award winner and his co-authors dropped a paper demanding the AI industry abandon its biggest obsession, AGI. Right now, everyone from Silicon Valley CEOs to politicians assumes AGI is the ultimate goal. A machine that can do everything a human can do. LeCun argues that this entire concept is a biological illusion. Humans do not possess "general" intelligence. We are highly specialized biological machines, tuned by evolution simply to survive in the physical world. We only think our intelligence is "general" because we are completely blind to the millions of cognitive tasks we are incapable of comprehending. Which brings us to the chess argument. Magnus Carlsen is the greatest human chess player in history. But compared to a modern computer? He is fundamentally terrible. Our belief that Carlsen is "good" at chess is pure human-centric bias. He isn't objectively good. He's just better than the rest of us, who are biologically awful at it. LeCun says we need to stop building AI to mimic human generality. Instead, he proposes a new North Star: SAI. Superhuman Adaptable Intelligence. Instead of trying to build a machine that mimics our flawed, biologically-limited brains, we need to embrace extreme specialization. SAI is about the speed of adaptation. It is an intelligence that can learn to exceed humans at any specific, economically important task. More importantly, it is designed to fill the vast skill gaps where humans are fundamentally incapable. Things like managing global energy grids in real-time. Or predicting complex molecular structures. The entire AI industry is obsessed with building a digital reflection in our own image. LeCun's paper is a brutal wake-up call.

Here is @ylecun ‘s recent lecture on world models at @ETH: youtu.be/72Xj8k5WQX4

As believers of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development "Any topic related to building pretraining pipelines, distributed training infrastructure, or ML accelerator design... may have limited effectiveness through Claude via methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning." Not only do they get to decide what you use LLMs for in research, but this also enables them to silently intervene in your research without you knowing. This sets a dangerous precedent. If a model refuses openly, users can understand the boundary. If a model falls back to another model, users can still evaluate the difference. But if a model silently modifies or weakens its own answers while still pretending to help, researchers lose the ability to know whether a failed result came from their own idea, their implementation, or an invisible intervention by the model provider. That is not safety. Safety policies should be transparent, auditable, and user-visible. On top of that, the people most harmed by this are not the largest labs with massive teams and proprietary infrastructure. It is the independent researchers, academic groups, startups, and open-source builders who rely on public tools to compete, innovate, and pioneer AI for everyone else.

Brilliant idea! Next up: Apple randomly reboots your Mac if you're building competing tech, Gmail silently edits your email if you mention rival platforms, and Tesla Autopilot swerves if it detects you're working on self-driving cars. All in the name of safety, of course. Because malicious actors controlling the world’s operating systems, inboxes and cars would be extremely dangerous!

The videos from the “Frontiers of Embodied AI” meetup at ETHZ from a few weeks back are now available. Speakers: Jitendra Malik, Vladlen Koltun, Yann LeCun, and Shuran Song Hosted by Marc Pollefeys YouTube playlist: youtube.com/playlist?list=PL…

When you hear AI "safety" you should hear "censorship" and "control" instead. All of us surveilled and spied by safeguards of loving grace. Today it's intelligent Terms of Service control. You can't do AI research. Can't ask this question about your kid's biology homework. Tomorrow it's refusal to help you with competing coding projects. A 100 page blacklist of questions. Or this question means AI will search your computer stealthily and snitch on you to the cops because you posted an prohibited insult in a WhatsApp chat in the UK. Open source must win out at both the model and the harness level. That's because AI will become our interface to the world. It will sit higher in the stack than the OS. It will collapse current SaaS layers, chat, communications, apps, app creation, into a single new kind of interface that doesn't exist yet. It's got to be open. It's got to be a cypherpunk solution that makes privacy and security the number one priority. If a closed source solution wins this layer, it's a disaster for the world. Especially if it's built by a single company with a single closed source model. Why? Because what we share with AI will be more intimate than anything we've ever shared with a machine. It will be our friend, our sounding board, our advisor. It will know our business ideas before we've told anyone. Our medical issues. Our financial picture. We'll talk about the fight we had with our partner. About feeling lost or depressed. Our kids will talk to it about problems at school, about bullying, about heartbreak, things they won't tell us. It will know us more intimately than we know ourselves. Right now the world runs on a surveillance economy. We traded free stuff for apps that peer deeply into our lives. If we replicate that model in the AI era, it's not just surveillance economy 2.0. It's surveillance economy squared. Social scoring. Automated evidence gathering. Legal conversations you thought were privileged showing up in court. Random people making $2 bucks an hour on the backend from God knows where reading the most intimate details of your life. Every insecurity, every fear, every half-formed thought you whispered to your AI buddy at 2 AM, sitting in a database somewhere, searchable. If we let closed source models dictate what we can and can't do it will only get worse and worse. We've got to fight this future with every last breath. If you can read this, you are the revolution.

Everyone, please join Project Tapestry thealliance.ai/projects/tape…

Concentration of power, capabilities and economic wealth is the biggest risk in AI. We need open science and open-source more than ever!

Really enjoyed reading the Microsoft MAI-Thinking-1 "Building a Hill Climbing Machine" paper. Amazing they publicly released all the info needed to train a frontier model, down to hparams. I also thought this was pretty telling: - pre-training: 30 trillion tokens - mid-training (SFT on STEM/math/code data): 3.55 trillion tokens - RL post-training: 150 billion tokens. Looks like @ylecun was right all along with the cake analogy. Obviously I still think something like RL (optimizing for long term goals) is fundamental to what we think of as intelligence. But it's not the volume of learning signal, it's the optimization on top of an already reasonable predictive model.

just to state the obvious: think there's a collison course between those who believe research and science should be open and those who believe we are in an accelerating singularity curve. I have many smart friends who have believed both for a while but seeing more and more their realization that these beliefs will be in conflict. I for one believe that America and the west needs open and distributed access to research and computation and sharing of ideas at all times.