🆕 Presenting: The 2025 AI Engineering Reading List https://t.co/IjOwDdNnnD 1 paper/blog/model family per week for every week of 2025, for you to run paper clubs or binge over the break.

"The role of academia especially in AI has shifted quite a lot in the last decade. 5 or 10 years ago, you really could train state-of-the-art models in the lab with just a couple GPUs... [now] you can't. That means the expectations around what we should be doing as academics

Full episode on youtube: https://t.co/MO9AUumdaN

From years as a Stanford professor and building ImageNet, the project that catalyzed the deep learning revolution, Fei-Fei Li joined forces with her former student Justin Johnson and a select team to start World Labs, staking their careers on spatial intelligence as the next

Why guess when you can know?

Hopped back on the @latentspacepod to chat about AMD, kernel dev, and model architectures. Always a great time :) https://t.co/t4TusNxaht

"It's been the year of the agent. We store some data for a session but we only store it for 30 days. When the user first started hitting that they were upset. We [originally] were like, 'There's no way anyone's going to be using a single session for 30 days.'" Jed elaborates

Wow, surprisingly I’m very aligned with what @ChanZuckerberg Biohub seems to now be excited about - they’re calling it “frontier biology meets frontier AI” ;) PS. A great @latentspacepod podcast: https://t.co/9hkEmm3K19

Elevate your look with our rose gold bangles — a blend of modern style and timeless elegance. Intricate details, lasting shine, perfect for stacking or wearing solo. A chic choice for any occasion.

"'If I had a kid in college, I wouldn't recommend they study computer science.' This was long before Jensen Huang and people had been saying this kind of stuff. This is either going to take my art, my craft or this is a tool to create better art." Jed touches on the debate

Full episode on youtube: https://t.co/SiPD8BnEhZ

Jed Borovik from Google Labs is building Jules, Google’s autonomous coding agent, after nine years working on search. Jed has lived through the shift from classic ML ranking to long-running AI agents with their own computers. His “Stable Diffusion moment” convinced him that AI

Excited to be on @latentspacepod soon with @realchillben. What a time to be alive! Thanks for a fun conversation @swyx

The coming years will split companies into two groups: those that become AI-native and those left catching up. The innovators who harness AI now will define the winners of tomorrow. Follow me for strategic insights on leading through the AI revolution.

"The moat is what is the hardest to do... in any part of the stack. If the app layer is easier to build, I think the model layer is harder and therefore will naturally capture all the value net of competition from other model providers. It is far easier for Anthropic to try to

"VCs have a tendency... to trivialize a problem into a one-sentence narrative. With Glean, that narrative was 'You built this enterprise search thing which never worked and then AI came along and then it became a thing.' Which I think is not the story at all. We did all the

"Sam Altman once came out and said, 'If you're an investor in OpenAI and one of these five companies, including Glean, we don't want you as an investor' Yet here's what I see. Look at the revenue of Anthropic and OpenAI right now. These are billion dollar revenue scale

Really good @latentspacepod podcast with @deedydas. On AI, Investing, Enterprise Search, Glean and many things in between. https://t.co/1FleEbrM3t

"Some of the joy of coding used to really be you're stuck on this annoyingly hard problem and you just bang your head against a wall... and then eventually you're like, 'I've figured it out' and then you solve it. That's the muscle you build when you improve and get better."

New @latentspacepod Essay: why Agent Labs are clearly emerging in 2025 as a complement to Model Labs' all becoming AI Cloud platforms. https://t.co/b5rLhF4W9I

"Furthering the intelligence of models in ChatGPT, a consumer product, does not lead to more users or more retention. It only is really applicable to a thin slice of users who care about very smart type queries. Most of the 800 million users on ChatGPT are asking like, 'How do

Great episode of @latentspacepod hosted by @swyx and @FanaHOVA and @deedydas as guest. One of the highlight of this episode was his view on research investing. IMO, Right now all investment is going on wrappers and short terms tech, good to know some research startups and

"If we believe as a society that 5 and 10 years later in the future these models are going to be critically important for making pretty heavy decisions, then I don't think the black box approach is long-term scalable. Mechanistic Interpretability is really going into the weights

~2.5 years after first joining us, Deedy is back!