Viewpoints, commentary, analysis, interviews, and discussion of trends.
In remote interviews, if you encounter a candidate suspected of using an AI face swap, asking them to wave a hand in front of their face might give it away 😂 https://twitter.com/loktar00/status/2111090535515513296
Alexandr Wang thanked Meta Superintelligence Labs’ research teams after a week of launches, including Muse Wonder [full] and Muse Spark open. He said MSL and TBD began a little more than a year ago with the goal of producing a frontier model within a year or so, despite the ambition of that target given where Llama 4 landed. Wang said the teams have also built a scalable system for continuing to advance models at the frontier.
Addy Osmani, Morgan Westlee Lunt, and Qing Wang say the Claude Code team reviews changes continuously, with Claude reviewing and fixing most changes at least once before a human looks. They describe asking what could go wrong and which check—automated or human—is right to catch it, rather than using whether a human read the code as a proxy.
The paper on how a team of Gemini 4 agents beat Minecraft is worth a look. It is accessible example (partially because it is AI written) of spontaneous coordination among agents to accomplish a complicated goal & how their approach differs from humans/ https://t.co/brrmhydhWw https://t.co/cxlp4jTjqf
Seriously, there is no way to algorithmically filter out the obvious AI slopreplies? https://t.co/nwHLySb0pc https://t.co/6ikEfg1K05
Six projects from the last few weeks that caught our attention: A wildfire analysis prototype that maps the fire’s spread over time and tracks hot spots, made with Opus 5.5.
Senior AI reporter James O’Donnell interviews Stanford University bioengineering PhD candidate Samuel King about using a generative AI model to propose genetic blueprints for microscopic viruses. The session covers King’s work, his recognition as one of MIT Technology Review’s Innovators Under 35, and new ways of seeing biology. The source says this is not yet an example of AI-generated life.
ClaudeDevs announced that Code Review is now generally available for Claude Team and Enterprise plans, with faster reviews, improved detection of consequential bugs, and per-repo Quick, Standard, or Deep review levels selected by admins. Boris Cherny says it runs on all his PRs and catches almost every bug before it gets in, helping his team move quickly while raising quality. https://twitter.com/ClaudeDevs/status/2110866210573386065
Perplexity can be your Personal CFO with the @Plaid connector set up inside Computer. https://twitter.com/Plaid/status/2111109925745168644
The back of the Navier-Stokes milestone shirt is the last line of the chain-of-thought from the solution:
Amazon CTO Werner Vogels argues that companies should understand their business problems and AI’s capabilities before rushing to adopt it. Speaking in Shenzhen, he emphasized task suitability, operating costs, explicit limits on Agent actions, and developers’ responsibility for outcomes. He also warned that AI-generated code can accumulate verification debt and stressed that junior engineers still need experience reading and reviewing code.
The article describes how VLA models and world models are being developed and deployed in Shanghai: VLA enables robots to perform tasks, while world models predict what may happen before an action. Ant Lingbo’s “Lingbo General Brain” has been adapted to 17 robot brands and 20 configurations, and robots using it are working in multiple Shanghai pharmacy locations. The article says the two approaches are beginning to converge, while planning, standards, and evaluation are advancing.
Sam Altman says he is very happy to see Nick Cammarata’s post on interpretability. Cammarata says early work at OpenAI left him pessimistic, with primitive tools making about 2% of neurons legible. He now claims modern agentic tools make the vast majority legible in models up to trillions of parameters, and believes ambitious interpretability could be solved quite soon as automated scientists improve. https://already-clean.goodfire.com/
Amulya Vishwanath, a former NVIDIA robotics product marketing leader and founder of Techable VC, says robotics is in its “Lego era,” with basic building blocks still being rebuilt. On TechCrunch’s Equity podcast, she discusses investing in physical AI across robotics, materials science, and life sciences, and defines it broadly to include “a molecule, a material, a medicine,” or a factory machine.
Amulya Vishwanath, who spent seven years leading product marketing for NVIDIA’s robotics platforms, says robotics is still rebuilding basic components such as actuators, robotic hands, software, and safety standards. On TechCrunch’s Equity podcast, she discussed where she is investing through Techable VC, the early-stage firm she founded to back physical AI across robotics, materials science, and life sciences.
A safe assumption when people are all commenting on a short Chinese policy document is that they don't know what it means and tried to parse a partial translation from Claude, without reading all the way through. There are maybe 5-10 on this site who I trust to comment.
A safe assumption when people are all commenting on a short Chinese policy document is that they don't know what it means and tried to parse a partial translation from Claude, without reading all the way through. There are maybe 5-10 people on this site who I trust to comment.
MAI is the most accurate & most popular transcription model on OpenRouter across all languages and use cases. Try it out for your agents now! 👇 https://t.co/rHOlsQWzro
Mark Wahlberg said at TechCrunch Disrupt that AI can have a place in filmmaking when it enhances the work while keeping storytelling at its heart. He may use AI to enhance the stadium setting in his upcoming Pete Rose biopic, and said he’d be open to an AI likeness continuing his legacy, including in his animated series “Ted.”
Cammarata argues that better tools and automated agents make neural networks more interpretable than earlier research suggested, while Google DeepMind's Neel Nanda disputes that a broad breakthrough is near. Cammarata reports preliminary findings that about 90 percent of neuron poles in Qwen3-32B have one main job and reinterprets classic superposition examples as related features. Nanda sees practical value in neuron analysis but expects significant gaps and maintains that superposition is real. The technical companion paper has not yet been released.
Replit CEO and co-founder Amjad Masad said the company’s work is increasingly driven by AI agents, which handle much of the initial support-ticket triage and can be deployed to submit fixes. He said people still provide judgment and taste, while spending more time deciding what to work on, discussing ideas, and planning architecture.
Arthur Mensch argues that Europe should build frontier AI models, warning that relying on American and Chinese providers would deepen economic dependence and limit control over access, pricing, security, and scientific research. He argues that open models only partly address this dependence and that frontier research supports industrial deployment. At Mistral, he says, compute capacity is set to increase sixfold over the coming year, and the company will raise capital to move faster.
wait who the hell was driving the tesla
Live the kind of life where the suggestions from Codex Composer Text Predictions are always wrong.
@emollick posted: “Live the kind of life where the suggestions from Codex Composer Text Predictions are always wrong.” Ethan Mollick: I couldn't help myself. https://t.co/1D6DQqXvAC https://t.co/baQEzSDYII
@90VuHwwuzNhhW3h says vLLM supports Muse Spark Open and made a little film to tell its story, using open-source models served by vLLM-Omni. The inference engine also gets a role behind the camera. https://t.co/n3gvdWTC6T The main author calls the film cute and says it brings multimodal understanding, 1M context, agentic planning, DSpark, and cross-platform support to life. https://t.co/yHPXC7qfdM
Well, I think we have a product demo that manages to beat both the iPhone and Engelbart's Xerox PARC demo.
@thoughtcrime___ called the video their “official submission to sloptoberfest” and wrote, “LOOK HOW FAR WE’VE COME.” Alexandr Wang reacted: “Holy fuck Holy fucking fuck That video of yours is absurd (but actually the dopamine release from watching this video was insane)” https://twitter.com/thoughtcrime___/status/2110803960105968063
This paper shows why I am skeptical of the idea that frontier models can be easily replaced by cheaper ones (and why you should use the best models as orchestrators): Small improvements in accuracy & judgement compound over long-horizon tasks, creating huge gains in outcomes.
@kirillk_web3 says Meta’s Llama 4 disappoints everyone, Meta goes closed with Muse Spark, Zuck writes a $100-200 billion check, Muse Wonder ships on Monday, and 3 days later Meta drops you with open weights: 816 billion parameters, only 42 billion active at a time. https://t.co/031gtR0nHm https://t.co/nEN1JMzvBa Alexandr Wang: “lmao muse spark open balling out” https://t.co/AcUT9o8NEQ
Cal AI founder Zach Yadegari said the company’s rapid growth came largely from paying influencers to promote its calorie tracking app. An early influencer post brought about 1,000 new users in two days, and Cal AI generated over $30 million in revenue over two years before MyFitnessPal acquired it in March for an undisclosed amount.
Harnesses + smart models = the end of the last famous hard benchmarks. Models can now work for extremely long times (bye, METR Long Tasks), they can output professional documents with correct math (so long, GDPval) and they can solve complex novel puzzles (farewell, ARC-AGI-3). https://twitter.com/arcprize/status/2110768288523251762
The first review I’ve seen of my upcoming book, Co-Existence, from The New Scientist. (When I became an author, I was surprised to learn you don’t know who is reviewing your book until the review comes out, so it is nice to start with a positive one!) https://www.newscientist.com/article/2593188-how-to-build-a-real-relationship-with-ai-and-keep-your-cognitive-edge/
Mira Murati says one of the best parts of this year, inside Thinky and out, has been watching people follow their own ideas into weights they own. https://twitter.com/thinkymachines/status/2110851669915570685 In the quoted post, @thinkymachines marks one year since Tinker’s launch with a look back at what it has shipped and what users are building. https://thinkingmachines.ai/news/one-year-of-tinker/
The New York Times visualizes the staggering amount of math needed to train AI models, using data from Epoch's research teams 📊 https://t.co/Cz21cuf9oQ Our training compute estimates: https://t.co/X7jSJHtWnz The Epoch Capabilities Index (ECI): https://t.co/RbP83Metg6
A new wave of films about Silicon Valley figures presents them more critically than earlier portrayals, reflecting audiences’ dimming views of Big Tech. The films include The Social Reckoning, which connects Facebook’s past decisions to current concerns about Meta’s influence, and Alex Gibney’s Musk documentary, which is screening in select theaters and has faced advertising restrictions. Luca Guadagnino’s Artificial and Nathan Fielder’s You Can See Everything also examine Sam Altman and Elizabeth Holmes, respectively.
We're sending a bunch of Microducks to assess @AnthropicAI! Kidding aside, it hasn't been approved yet but in my opinion, it's very important that open-source engineers and scientists are included in these important endeavors for transparency. That's a big part of why @Thom_Wolf is starting the open alignment initiative. We're all in this together!
Amazon devices chief Panos Panay said ambient devices that use sensors and AI could handle more tasks in the background, making app-based interactions less important. He described Amazon’s new Bee devices, introduced Thursday, which passively record audio and take notes; they process audio in real time and delete it afterward. Panay said he expects an intelligence layer connecting different devices, rather than one form factor replacing another.
Aravind Srinivas argues that neoclouds can't just rent GPUs and need to own the full agent inference platform, including open-weight models (SGLang), fine-tuned models (Miles, River), and secure sandboxes (SPACE). He looks forward to working with Coreweave, Akamai, Crusoe, and more partners. In the quoted post, Reed Albergotti reports that Perplexity is open sourcing its sandbox, SPACE, with partners including Akamai, Coreweave, and Crusoe. https://twitter.com/ReedAlbergotti/status/2110782821879144922
Neoclouds can't just lease GPUs. They need to own the full agent inference platform: open-weight models (SGLang), fine-tuned models (Miles, River), and secure sandboxes (SPACE). We look forward to working with Coreweave, Akamai, Crusoe, and more partners. https://twitter.com/ReedAlbergotti/status/2110782821879144922
