Vinod Khosla

Family First

Our robots built this in the city of Almere: curved walls, different types of bricks and bonds, indented text. Real world deployment, insane complexity, 100% of every brick done by our robots, with another 15 houses to come in the coming weeks.

This is a very exciting potential new treatment for food allergies! But to appreciate just how remarkable this development is, let me share a personal story about Xolair, the anti-IgE antibody currently used to treat allergies, and how painfully slow biomedical progress has been until now. I believe AI is about to change this dramatically! Back in 1989, 37 years ago, I was a visiting medical student as an intern at Ciba-Geigy immunology laboratories (which later became part of Novartis) in Basel, Switzerland. In the immunology department where I was working, one of the scientists, Christoph Heusser, had proposed developing antibodies against IgE, the molecule responsible for triggering allergic reactions, back in 1986! Around the same time, scientists at a small biotech company called Tanox had independently developed a promising anti-IgE antibody. Ciba-Geigy and Tanox subsequently formed a partnership in 1990 to advance this approach. I still remember the excitement surrounding this research as vividly as if it were yesterday! Imagining the possibility of treating allergies by targeting a single molecule responsible for triggering the entire allergic response was extremely novel back than. I was fortunate enough to witness the early development of this revolutionary idea firsthand, and it was incredibly exciting! But here is where the story becomes rather astonishing. Genentech subsequently developed a similar antibody in 1993, and the three companies eventually joined forces. Their collaboration led to Xolair (omalizumab), which finally received FDA approval in 2003, 17 years after the original concept! And that approval was initially for allergic asthma. It took another 21 years, until 2024, for Xolair to receive approval specifically for food allergies! Think about that. Almost 40 years after those original discoveries, Xolair remains the only FDA-approved anti-IgE antibody for food allergies. That is how painfully slow the traditional process of developing new medicines has been! Now compare that timeline with what Claude and Divergence Labs have accomplished in approximately ONE MONTH! Claude generated roughly 35,000 antibody designs, helping identify promising candidates that could potentially remove IgE already attached to immune cells. This could be a major advance over Xolair, which primarily neutralizes free IgE. Some of these new antibody designs already performed better than Xolair in specific laboratory tests! Of course, these are still early experimental results. The complete therapeutic antibody needs to be developed, validated, and eventually tested in clinical trials. But consider the implications! We are witnessing the beginnings of a fundamental transformation in biomedical research. As AI intelligence continues to advance exponentially, combined with automated laboratories, virtual cells, and eventually patient digital twins, I believe we will compress decades of drug discovery into months or even weeks! Clinical trials and regulatory approval will also become much faster as AI improves our ability to predict efficacy, toxicity, and treatment responses. My prediction is that instead of waiting decades for individual breakthrough medicines, we will eventually be developing hundreds, perhaps thousands, of new treatments in parallel, within just a few years! Having personally witnessed the beginnings of anti-IgE antibody development nearly four decades ago, and now seeing AI begin to revolutionize that very same field, makes this moment extraordinarily exciting for me. I have been waiting for this transformation for most of my scientific career. And I believe we are finally entering the era when the pace of medical discovery will accelerate beyond anything we have experienced in human history!

Industrial robotics and advanced manufacturing are foundational to America’s defense industrial base. Securing domestic production capacity isn’t just an economic priority – it’s a national security imperative. whitehouse.gov/presidential-…

Today, @FoundryRobotics is announcing our $100M Series A, led by @MarlinspikeVC with continued support from @khoslaventures. Together we’re securing America's ability to defend, compete, and innovate by building critical hardware at home with our new 130,000-square-foot factory in Emeryville, California. We’re already shipping to paying customers across energy, telecom, autonomous vehicles, and defense. The next era of American manufacturing starts here. Time to build.

If you look closely enough, breakthroughs in everything are accelerating exponentially. An exponential always starts off looking small.

Today, we’re kicking off the Highlight beta. Try it here: go.highlightai.com/highlight… I want a future where AI helps make your work uniquely yours, and not feel cookie cutter. That’s what we’re building Highlight for. Highlight is your working world, all in one place. It connects your apps, meetings, and screen, creating a single command center where you can find answers, see what needs your attention, and start every task with the first draft already done.

Bunkerhill has grown 12x annualized since January, with 8 figures in ARR closed in the last week alone. Health systems want agents that do the work, and we need help building them. We’re hiring across engineering, forward-deployed and sales. Join us!

John Schneider had been on an absolute heater when making major trades since 2022. Whether buying or selling, he’s crushed it.

The résumé speaks for itself.

"What if you didn't have to go through classical compute limits at all?" - @PimDeWitte Pim’s argument is that the optimal approach is to learn directly from the data the universe produces continuously, rather than relying on simulators. On top of that, the training runs are tiny compared to frontier LLMs.