Sarah Guo

New @NoPriorsPod with @dmitri_dolgov ceo @Waymo on all things self-driving! https://t.co/Bu7sKp9J0N https://t.co/pXDQq5hIgR

Not A Normal Market

Only about once a decade does the technological ground shift. The ARPANET in the late 60s, which laid the groundwork for the modern Internet. The microcomputer revolution in the 70s and 80s, which put a PC on every desk and in every home. The World Wide Web in the 90s, which made the Internet accessible to everyone and birthed the dot-com boom. The rise of broadband and network equipment in the 90s and early 2000s, which made high-speed connectivity ubiquitous. And the emergence of cloud computing and SaaS in the 2010s, which transformed how software is delivered and consumed. We are living through the mother of those transitions now with AI…

oh look, a herd of VCs

This is what a platform company looks like. Grateful to the GOAT Jensen Huang and team @nvidia for hosting @conviction, @eladgil and founder friends yesterday. Incredibly impressed by the warm commitment (30+ years in, at massive scale) to the startup and developer ecosystem. https://t.co/dMteINqeA4

They caught it. They caught the Starship with chopsticks. We are going to Mars someday. I’m crying. Now make the rocket for $5M, make 10,000 of them, move 1m tons of payload. One miracle at a time. @elonmusk do @NoPriorsPod and explain when what it will take to go to mars!?

1/2 Powerful AI has radical potential long term benefits, not just radical risks Everyone should read @DarioAmodei’s “educated and useful guess” on a optimistic future, and his framework of using “marginal returns to intelligence” to judge impact on different fields (eg biology) 2/2 This essay is important to read in part because Dario underestimates “constraints from humans” And for humanity to accomplish that future of abundance, many people and organizations (outside of model research labs) will need to contribute to relaxing those constraints. ☀️

Jensen Huang round 2 coming to @NoPriorsPod: what are your questions?

huge alpha in understanding the difference between marketing to technical vs nontechnical audiences, and when to apply each see: Optimus teleop at Tesla event vs. research demos

just try stuff

Help! Do I know anyone who works on Google ARCore

AI is Chemistry

Repeat after me: backdoors designed for our government will get compromised https://t.co/NTzx1cb4qW

🆕 @NoPriorsPod with @linakhanFTC FTC Chair and youngest head of a government agency. Must-listen for everyone in tech *her philosophy for regulating M&A *AI "acquisitions" *competition in foundation models *non-competes *why there are few young people in gov https://t.co/prMy8OaG2A youtube: https://t.co/4YQ1grhoNf spotify: https://t.co/fqfJzl9dRV apple podcasts: https://t.co/lwbnc8bPX1

what designers do I know want to work on the future of AI interfaces? DMs open

goodbye and good riddance sb 1047

counter to the popular narrative: because businesses have imperfect incentives, and have cycles of slow change management/procurement/not-invented-here 90% of the value from AI to date is actually going to workers (and smbs) adopting fast

simplest explanations

Talked with @stanine COO @Rippling about their new launch, Talent Signal, that uses AI to understand employee performance: - looking at work product with models - initial reactions - how they considered abuse / bias - incorporation into decisions - what makes rippling powerful https://t.co/c5X69su4Mv Spotify: https://t.co/RG4ulOxQer YouTube: https://t.co/tiNArOzdXF The best part is that Matt’s so diplomatic: “for the longest time, their roadmaps sucked”

some feedback for candidates looking for jobs at promising startups: don’t claim “x years of experience” that’s not an outcome, that’s hanging around the hoop. you can do something in a mediocre way for years instead describe something great you have built, fixed, quota hit…

Undervalued: infectious enthusiasm

people are sleeping on accessibility APIs in the age of AI

1/ As AI models grow more powerful, it’s becoming clear that data strategy is just as important as model architecture for advancing capabilities. The right data—and how we use it—will determine the future of AI performance. 2/ I was explaining to someone (not in AI) that neural networks don’t just “memorize” word sequences. Instead, they learn deeper patterns, allowing them to predict the next word even when they haven’t encountered that exact combination before.. 3/ Neural networks don’t store all possible word combinations. Instead, they map words to vectors in a space where similar words are grouped together. This helps them understand c…

.@btaylor is the rare unicorn of leader, technologist, product thinker, (friend!) must-listen episode for insight into AI in the enterprise, agents in the wild, and long-term arc of tech landscape https://t.co/DIDn1ayzP1

build that datacenter baby we’re so back https://t.co/hCBPYJTD7c

if there was ever a sign that supply chain security needs to be a top natsec priority, the 9/17 pager attack was it all the policymakers talking about pushing “norms” in the supply chain for adversaries — the Overton window on these “norms” is not one you want to rely on

everyone on this “models are a commodity” train now huh

Ｔｈｉｎｋｉｎｇ

New @HeyGen_Official avatars are better at expressions than my real face

Destruction of the world’s 2nd biggest innovation ecosystem (China) is a massive unforced error. I hope many of these entrepreneurs become immigrants. “The whole industry has just died before our eyes. The entrepreneurial spirit is dead. It is very sad to see.” (via @FT) https://t.co/l816c0Y9LB https://t.co/vWAqo3Mqwx

do I know any engineers who are 1) good writers and 2) interested in understanding AI in production and 3) have some time on their hands