i don’t think people realize how early we still are in the ai cycle even though the major companies are now becoming public.
the models are getting way better but still have gaps. most of the products are still primitive in so many ways. the interfaces are mostly bad. the workflows are barely rebuilt. the hardware layer has barely started. robotics is just the at the very precipice. consumer behavior has not even begun to rewire yet.
there is a long long way to go. what a crazy time to be alive.
SpaceX: Do exactly the same thing. Sign deals with Anthropic and Google right before the IPO, do a little window dressing, tweak the rules to get included in the Nasdaq index as quickly as possible, and then support that sky-high valuation with great stories on X. Cheers 🥂
No question, these are all incredible companies and the achievements are genuinely remarkable. But the practice of pushing private-market valuations to extreme levels and then finding ways to pass those valuations on to retail investors—whether through index inclusion, government participation, or other mechanisms at just the right moment—is probably not great for the average retail investor. In many ways, it’s a form of exit liquidity.
Personally, I think these companies will be worth significantly more in the future. The issue is that they may first need to grow into today’s valuations, potentially with some setbacks and painful drawdowns along the way. Meanwhile, the average retail investor will probably end up selling near the bottom, as usual.
Cheers 🥂
OpenAI / Anthropic: Jack your private valuation up to $1 trillion, convince the U.S. government to buy in, then use taxpayer money to grab a piece of some “super amazing company” at a ridiculous valuation. Cheers 🥂
Aging is arguably the root cause of most major diseases (loss of function in our cells). Four years ago, we made a bet that aging was treatable, and NewLimit was born.
NewLimit now has a prototype drug that reverses the age of some human cells (restores function they had when they were younger), and a clinical trial scheduled for next year (with more drug candidates in the pipeline).
Grateful to Founders Fund, Thrive, Greenoaks, and the rest of the investors for this latest round. @jacobkimmel and the team are just getting started.
The events of the last 6 months in technology are arguable amongst the most important in human history
The tools now increasingly exist for recursive self improvement of models & agents
We are likely in very early lift off & exponential
Largely unnoticed outside of tech
Far left: we need to tear down the system
Center left: we need a system
Center right: we need positive-sum games
Far right: we need to win zero-sum games
Marc Andreessen on the question at the center of data center discourse & why it's so important:
"Can you build anything in America anymore? Can you build a factory? Can you build a chip plant? Can you build a power plant? Can you build a refinery? Can you build a pipeline? Can you build housing?"
"One of the common themes in American life for the last 30 years is the answer to those questions is generally, no, you can't do any of those things."
"Take as an example, Silicon Valley, right? So all the chips are made in Taiwan. Well, 40 years ago, all the chips were made in California."
"Can you build things in America? Can you build a factory? Can you build an energy plant? Can you build a data center? Can you build housing?"
"And on every single one of those, there's this massive problem which is, right now in many cases, in many places, no you can't."
@pmarca with @joerogan
the golden rule is that you should rarely if ever try to change anyone’s mind.
this is a fool’s errand cuz it rarely works, & even when it does the belief you installed is way weaker, the person becomes resentful, & everything dynamic from then on becomes borrowed instead of owned.
you can only gently probe until you understand why they arrived at that conclusion. then you must move on like it never happened. this is true for any type of relationship including professional but esp true in romantic dynamics.
Out of all the announcements at @Google I/O today, this is the one closest to my heart - our foundational research on Co-Scientist was published in @Nature and we announced its broad availability via @GeminiApp for Science.
When you are suffering from a disease, time is everything. As our collaborator and @StanfordMed Professor Dr. Gary Peltz reminds us, there are thousands of diseases out there with zero treatments. There is simply so much left to solve.
Our goal with Co-Scientist has been to give scientists superpowers and help them get to these answers faster - compressing the scientific process from months and years down to hours and days.
Much like Galileo's telescope helped us look into the stars, Co-Scientist is designed to help us make sense of the vast complexity of biological and scientific data. It is among the first examples of a truly general-purpose multi-agent system for scientific discovery.
The core research question behind it was: How can an AI system engage in the rigorous, structured thinking that’s the hallmark of science and scientists?
To tackle this, Co-Scientist builds on the principles of self-play and self-improvement underpinning @GoogleDeepMind breakthroughs like AlphaGo, generalizing them to scientific reasoning through self-debates.
Since our preprint last year, we have further improved its capabilities and have been validating it in collaborations with scientists across over 100 institutions globally, spanning both academia and industry.
And we are thrilled to see the emergence of a new form of AI-human scientist collaboration that's already leading to important new insights, discoveries and peer reviewed publications - from understanding antimicrobial resistance (published in @CellCellPress) to decoding plant immunity, to identifying new treatments for liver fibrosis (Advanced Science), cancer, neurodegenerative diseases like ALS and the grand challenge of aging.
I have always believed AI's greatest promise is accelerating scientific discovery and advancing human health.
My genuine hope for the future is that AI tools like Co-Scientist help democratize science, giving anyone, anywhere the means to pursue their child-like curiosity and change the world.
This work was done with stellar team mates spanning @GoogleDeepMind@GoogleResearch, @googlecloud and @GoogleLabs especially Juro Gottweis (@Mysiak ), who is the heart and soul of this effort.
Special thanks also to all our wonderful collaborators: Gary Peltz, @CostaT_Lab, @jrpenades, @_e_d_v_ , @iambyronic, @OpsBug, @jgooten, @omarabudayyeh Ritu Raman, Ryan Flynn, Filippo Menolascina, Velia Siciliano, Clare Bryant, Matt Onsum, Katherine Labbé and more.
Nature paper link - https://t.co/ap4woY9Fo3
Google DeepMind blog - https://t.co/LLJZ27ufPP
Gemini for Science - https://t.co/lDhsHCCXrj.
if my agent can't use your product, you just lost a customer.
before i even click your link, my agent has already gone through it. if there's no cli, no api, no way for an agent to interact with what you built i'm gone. and so is everyone else who works this way.
the age of acceleration demands a new layer. your product doesn't just need a UI for humans anymore. it needs a protocol for agents. cli. api. mcp. something. anything my agent can talk to.
if you're still building products that only humans can click through, you're building for the last era.
the next wave of customers won't visit your website. their agents will. and if your product can't answer, you don't exist.