@sama@sama , we’ve met before. I’m advising a startup that brings significant compute efficiency to HPC apps, but on the CPU side. We can help you squeeze a lot more juice out of your compute there, on the order of 30% or more. Have someone reach out if you are interested
Not gonna lie, this is the first time I’ve re-watched a AI generated trailer more than 10 times.
All credit to the amazing @AzeAlter
Audio score by @musoscientific
This needs to become a full movie.
Adventures in a future full of abundance
Top 10 highly technical YouTube channels to learn AI from scratch:
1\ Andrej Karpathy - a blend of general and technical content, Zero to Hero playlist is a must-watch https://t.co/tNNLTyYT86 @karpathy
2\ Umar Jamil - highly technical, implements ML and LLM techniques from scratch https://t.co/AP9ecr04wq @hkproj
3\ Simon Oz - technical low-level machine learning videos https://t.co/7StZUevNXp
4\ Tunadorable - paper review, implementation, triton https://t.co/vwOhYtui07
5\ GPU Mode - technical interviews and walkthroughs about anything related to GPUs https://t.co/gfRuxCeBEn
6\ AI Jason - AI experiments, software design, and new techniques beautifully explained https://t.co/7O7DRRxSQa @jasonzhou1993
7\ Ferdinand Mom - everything related to distributed training & inference https://t.co/gmV7vBQixg @FerdinandMom
8\ Welch Labs - unique in-depth look at machine learning complexities like nobody else https://t.co/ovEt9WnEx2 @welchlabs
9\ Artem Kirsanov - neuroscience and machine learning from a different look, great visuals https://t.co/sJBmDbP7Qy @ArtemKRSV
10\ David Ondrej - new models, building apps with AI, practical for developers https://t.co/BEOr0MgHag @DavidOndrej1
This list is for a practical and technical audience. It's so hard to hand-pick just 10 channels, there are so many great ones out there making great content.
If you know any other channels, LMK.
Meta CTO Andrew Bosworth says that they're finding in Meta's robotics efforts that we're hitting the information-theoretic limits of intelligence; all the human media ever produced isn't enough; breakthroughs in common-sense 'world models' will be needed to understand causality.
From Jensen Huang at GTC. This is a significant shift in computing, a completely new computing paradigm, moving from traditional manual code and files to AI-driven token models.
Jensen Huang at GTC:
"I expect data center build out to reach a trillion dollars, and I am fairly certain we're going to reach that very soon."
"General purpose computing has run its course, and that we need a new computing approach."
"In the past we wrote the software and we ran it on computers. In the future, the computer is going to generate the tokens for the software."
"The computer has become a generator of tokens, not a retrieval of files."
OpenAI CPO, Kevin Weil
"this is the year that AI gets better than humans at programming forever"
according to our internal competitive coding benchmarks, AI will surpass human capabilities in programming this year, and "there's no going back"
OpenAI CPO, Kevin Weil
"this is the year that AI gets better than humans at programming forever"
according to our internal competitive coding benchmarks, AI will surpass human capabilities in programming this year, and "there's no going back"
“The cost of military-grade drones has fallen by three orders of magnitude over the last decade. By 2028, $26 billion a year will be spent on military drones, and at that point many are likely to be fully autonomous”
The Coming Wave
Mustafa Suleyman & Michael Bhaskar
This is a big opportunity to improve customer support by replacing today's comically challenged chatbots with truly helpful agents. Devs can't build them fast enough.
We're launching new tools to help developers build reliable and powerful AI agents. 🤖🔧
Timestamps:
01:54 Web search
02:41 File search
03:22 Computer use
04:07 Responses API
10:17 Agents SDK
This is incredible. It will have a big impact on a large number of high-paying jobs with reverberating economic effects, especially in places like Silicon Valley.
Solar energy costs have plummeted since the 1970s—from $100/W to $2.50/W today.
Installed capacity went from 1.5 GW in 2000 to 2,150 GW in 2025. Capacity has tripled since 2020.
Solar is now generally cheaper, or competitive with traditional energy sources, as long as you are in the sun.
Our first customer use case took 12 months, our second customer use case took just 30 days
Helix learned high-rate logistics with a single neural network
On Sunday, we successfully validated this on-site at the customer
“The Coming Wave” by @mustafasuleyman is a compelling read for anyone interested in potential impacts and outcomes of converging technologies like AI, bioengineering, quantum computing and fusion energy. Incredibly exciting and thought-provoking. Impacts could be wonderful or terrible, but will be significant regardless.
Today, we are excited to announce Thinking Machines Lab (https://t.co/Pe0uB8MxVN), an artificial intelligence research and product company. We are scientists, engineers, and builders behind some of the most widely used AI products and libraries, including ChatGPT, https://t.co/CTXVZKNH1c, PyTorch, and Mistral. Our mission is to make artificial intelligence work for you by building a future where everyone has access to the knowledge and tools to make AI serve their unique needs.
We are committed to open science through publications and code releases, while focusing on human-AI collaboration that serves diverse domains. Our approach embraces co-design of research and products to enable learning from real-world deployment and rapid iteration. This work requires three core foundations: state-of-the-art model intelligence, high-quality infrastructure, and advanced multimodal capabilities. We are committed to building models at the frontier of capabilities to deliver on this promise.
If you’re interested in joining our team, consider applying here: https://t.co/fkT82CRytQ