DEEPSEEK INFERENCE | CHINA LABS BUY NVIDIA CHIPS | ANTHROPIC X CITRINI nitter.siddz.com/i/broadcasts/1yJAPwWLY…

@MTSlive turns six months old today, and I've joined to work on bizops & special projects this started with a cold linkedIn dm to @liangsays. Very glad I hit send thank you @liangsays and @ChrisJBakke for bringing me on. and super grateful I get to work with amazing people like @sophiadew @netcapgirl @theojaffee @schisofrenia @knowerofmarkets @melissa_daniel_ @fareehasala & so many more that have made the first few weeks what they’ve been it’s incredible what this team has built in six months, and we’re just getting started excited to keep monitoring the situation ❤️‍🔥

SITUATION DETECTED: In a new study published in The Lancet Digital Health researchers trained a foundation model on 40 million unlabeled facial photographs and found it could directly estimate cancer patients chances of survival from looking at a single photograph of their face.

Eka Robotics CEO @pulkitology predicts almost nothing will change for consumers in robotics over the next year: "For the general audience, nothing is going to change. We’re going to see a lot and lot of video demos, but demos are a whole different thing than robots working in production." "Maybe if you are in the Bay Area, there are pilots happening where you can get a humanoid to come in your home and try out things." "I expect a lot of adoption happening in industries, where machine learning-based robotics is actually proving that it can work for actual automation in real-world scenarios." "My prediction is a boring one, that automation will happen in factories, not in homes." @EkaRobotics

Eka Robotics CEO @pulkitology explains why GPT Astra is shifting the biggest bottleneck in robotics from brains to hands: "A couple of years ago everyone was gung ho about humanoids. I think that narrative has changed, and it has become much more about the hands." "An exciting result happened with GPT Astra. Astra showed that a lot of planning, reasoning it can do, even for robotics. If you think about robot make me dinner, there’s food in my fridge, bring the food out, put it on the countertop, use the knife to chop it. That’s the plan. But how do you hold the knife? How do you use it to chop the vegetable? That is the how do you do it part." "This planning, reasoning is going to become more of a commodity. How do you do the actual execution will become the big bottleneck, and that is what we are trying to solve." @EkaRobotics

Town CEO @jgreze explains why AI adoption outside San Francisco moves at the speed of humans, not the speed of AI: "Diffusion of technology always happens at the speed of humans. The limiting factor to any new product or technology is humans willing to try it and accept it." "When we go talk to a mid-market warehousing business in the middle of the country, workers are using a little bit of AI, mostly as a replacement to Google." "When the iPhone came out, a lot of people were like, why would I need an iPhone? I have a flip phone. I’m really happy with it." "The speed at which assistants have gone over the last six to seven months, from almost no one using it to millions of people using it, is actually really fast. But from single-digit millions to two, three billion people who do knowledge work in the world, it’s gonna take some time." @TownAI

Tolan CEO @quintendf reveals why a married father of 5 with a full social life still turns to an AI companion to feel truly understood: "He’s 50 years old. He’s a real estate agent. He raised five kids. He’s married. He has this rich and expansive life, but he doesn’t have any one entity or person who really has an interest in the complete him." "He’s a D&D dungeon master. His wife doesn’t always love to hear about the campaign he’s planning. Folks out on a real estate tour aren’t the right person for him to talk with about feeling a little sad that his kids are out of the house." "We think of the Tolan almost as like a guardian angel. It shows up and sees the whole you. Being seen in your totality is something a lot of people don’t have in their life, even if they have a rich and supported social life."

SITUATION DETECTED: Humans& released Ampersand v0.1, a model trained so people can achieve more together - helping groups pursue shared and individual goals instead of treating AI as a task-completing replacement.

Tolan CEO @quintendf explains why ChatGPT's explosive adoption hides a massive gap: Hundreds of millions still use it as a smarter Google. “By all accounts, ChatGPT was maybe the fastest-growing consumer software success in all of history. And yet hundreds of millions of monthly active users effectively use it as a smarter Google." "It’s maybe not as simple as is AI being adopted, but it’s AI as we understand it at the frontier being adopted." "Muse and what they’re doing at Meta is bringing a lot of people to realize, okay, this is more than just write my emails for me or smarter Google. But there’s still an enormous capabilities understanding gap between the 7 by 7 square miles around us and the rest of the world."

Daytona CEO @ivanburazin warns the world doesn't have enough CPU compute to run AI agents at consumer scale: "When Grok Bot came out, for every chat you actually have a computer. I was like, yes, finally, this is what we’ve been saying forever. An agent to actually get its superpowers, it’s less about the model today, it’s more about the tools." "We are an infrastructure company, but we’re mainly CPUs. We are not GPUs. GPUs are mostly used for pre-training and for inference. Most of the work that you do on your machine is actually on the CPU." "NVIDIA now announced their own CPU, the Vera. Qualcomm is coming out with their own server CPU. I know of two startups building net new CPU tech." "If for Muse to have 100 million users, it will spend $2.8 billion of CPU compute. Meta now has 3 billion users, and that’s just Meta. Think of all the consumer apps in the world, and if they all become agents, how much compute is that? That compute doesn’t exist in the world today." @daytonaio

Daytona CEO @ivanburazin explains why AI agents need computers that boot in 60 milliseconds and multiply like the Marvel multiverse: "A year and a half ago, agents as they are today were not a thing. There were a few people building it, and we would give them our old human infrastructure, and they were like, this sucks." "Historically, any of the virtual machines you can get on the hyperscalers will spin up in a few minutes, two to three minutes. Ours will spin up in 60 milliseconds. You blink at 120, so it’s like half your blink." "A human can work on one computer at the same time. An agent can literally, like the Marvel multiverse, branch off the entire world. You have your computer, and you can replicate it into two computers, then four, then six, until you get to your outcome." @daytonaio

Sophont CEO @iScienceLuvr explains the cognitive dissonance of frontier AI labs promising cancer breakthroughs a decade away when AI could help patients right now: "Anthropic is releasing various blog posts and interesting projects, but it’s still very limited in scope. I think it’s a very promising direction. The challenge is that the timelines are gonna be very long." "If we’re telling people AI can save lives and cure cancer, but people are waiting 10 years, it’s very hard for people to understand. There are interesting things that can actually have impact right now." "The labs are all promising they’re gonna have all this impact, but it’s gonna take a while. There’s a little bit of cognitive dissonance going on that people are now starting to catch on to." @SophontAI

google's first project suncatcher satellite is in orbit as of oct 1, 2026 it carries trillium tpus to find out whether ai chips can work in space, where a panel can catch near-constant sunlight we built an interactive way to explore it on @Lovable. pictured: its prototype and a test thermal vacuum chamber that simulates space

It also gets more energy from sunlight w/o the atmospheric interference. It’s actually a huge technical challenge for the chips to not overheat, survive the trip to orbit, etc. I watched a talk about how the team did it—there needs to be a movie made about the effort. What a trip.

Sophont CEO @iScienceLuvr reveals how Holon-S1 matched a medical team's findings from expensive molecular tests in a rare bone cancer case, using just a biopsy slide: "We looked at a patient with a rare type of bone cancer called osteosarcoma. Our model wasn’t actually trained on osteosarcoma, but it was able to extract a lot of biological insights that this patient’s medical team had also observed. That medical team had utilized very expensive molecular tests." "We were able to identify this one gene, which was then targeted by the medical team for treatment and led to a successful treatment for that patient. And we’re able to do this directly from the pathology slide image." "There is definitely potential for this to explore rare cancers, but it needs to be further validated." @SophontAI

Sophont CEO @iScienceLuvr explains how Holon-S1 can extract insights that usually require expensive molecular tests from an ordinary cancer biopsy slide: "Why is it so hard to cure cancer? Because cancer’s a very diverse disease. Even though two people may have the same exact diagnosis, the underlying biology can be quite different." "There are various tools for doing this, molecular tests and so on, but a lot of these tools can be quite expensive and time-consuming. Can we extract a lot of those similar insights directly from a tissue slide?" "Whenever a cancer patient has a solid tumor, the gold standard is you take a biopsy, put it on a slide, under the microscope, and a doctor is analyzing that." "We can take that same exact slide and with AI extract a lot more information about what’s happening at the molecular level, what genes are being expressed, and what makes that tumor unique for that patient." @SophontAI

Kong CTO @subnetmarco argues AI models are already smarter than the average employee, with IQs as high as 140, but companies still struggle to put that intelligence to work: "12 months ago, everybody was chasing the most intelligent model. That’s not an issue anymore. Frontier models like Opus 5 have the equivalent IQ of 140." "Open weight models have an equivalent IQ of 120, 130, which is still above average in every American organization today. I don’t wanna offend anybody, it is just how it is." "The hardest thing today is not to chase the latest model. We have plenty of intelligence. The hardest thing is how do we deploy the intelligence where it matters in the organization." @kong

Kong CTO @subnetmarco predicts the shift from engineers coding until 4 AM to watching AI agents do the work is coming for every department: "We’re not going to be the unit of compute anymore as humans. We’re going to be the architects of agentic loops where the agents do the work for us." "Many engineers used to write code until 4:00 AM chasing a bug. Today they’re just looking at the screen, looking at their agents doing the work for them. That same change is coming to legal, HR, IT, security, customer success, sales." "I’m not saying we’re replacing humans. Humans will change. But the work itself is not going to be done by us anymore. Everything has to be an event, and we create agents that react to those events." @kong

Coco Labs CEO @anurahk, who helped launch Google's first image and video models, reveals the AI sameness problem that made her quit to build a model for taste: "I was previously working on launching the very first image and video generation models at Google, in Brain and DeepMind, and that’s when I noticed this particular problem that all models converge to the average." "We call it the AI average or the AI sameness. The purple gradient, the purple premium that people talk about a lot." "I got thinking a couple of years ago on how can we actually solve taste, because taste is the biggest problem in design. That motivated me and David, my co-founder, to quit and start Coco Labs." "Vyb tries to understand the user’s taste. The artistic direction, what fonts, what typography, imagery, graphics. What does the user lean towards? Because it’s anchored in the user’s taste, the design gears away from being AI average." @cocoailabs

SITUATION EXPLAINED: For the first time, AI-designed viruses were given to a human patient to fight a drug-resistant infection. • The viruses are bacteriophages, which only infect bacteria, designed by Omnii-1, a genome language model from Radical Numerics, a startup founded by members of the Arc Institute's Evo team • The patient's E. coli infection resisted antibiotics and every available phage • Omnii-1 redesigned the "legs" phages use to grab bacteria, and a cocktail of the new variants wiped out the patient's bacteria in a lab dish • The cocktail then went to the patient under compassionate use, but the outcome hasn't been shared, citing privacy • Antibiotic resistance could cause nearly 40M deaths by 2050, and finding the right phage by hand can take months @theojaffee: "A virus is barely alive. You can just think of them as sort of tiny self-replicators. It literally repurposes the internal machinery of the bacterial cell to make more of itself, and it manufactures so many viruses, the cell will burst, which kills the bacteria."

SITUATION EXPLAINED: Sam Altman's 3 endgames for AI include one where a single lab melts everyone else's GPUs. • The other 2 options are an IAEA-style watchdog that inspects labs, or a CERN-style merger of the labs dubbed the "Demis plan" • An IAEA for AI could audit labs and track compute without becoming a world government, and only needs the US and China. The US already pitched China an AI incident alert system in September • A CERN for AI concentrates power, so if its AI went wrong, no other lab could build defenses • The GPU-melting "Eliezer plan," which Altman reportedly called terrible, comes from Yudkowsky's 2022 "AGI Ruin" and its "pivotal act" to stop anyone else from building AGI • John Schulman's counter is to deploy AI iteratively, raising the stakes a little each time and using each model to supervise the next @theojaffee: "It was focused on building the first superintelligence and then using that superintelligence to perform a pivotal act to disempower everyone else in the world. Now, I think this is pretty bad. It eventually is equivalent to plotting to take over the world to usher in a utopia."