
Founder & CEO | Digital Infuzion. Building AI-ready systems for biomedical research and government. Personal views only. Official account: @digitalinfuzion
Maryland
Joined June 2008
- Tweets198
- Following232
- Followers112
- Likes61
Hemant Virkar retweeted
Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead.
You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence. You’ve also claimed the lead is widening because of recursive self-improvement.
I don’t see what you see in the lab. If the unreleased models are scary enough that you think you should slow down, I support your decision to be responsible.
But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier.
Most of all, stop pretending the motivation to slow down is purely altruistic. You face massive product-liability exposure if your products enable a truly damaging cyberattack. The market already punishes models that behave in unpredictable or unauthorized ways. After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability. Call it alignment if you want. It is also just giving customers what they want.
Pacing the frontier would also create breathing room for a more intelligent conversation about regulation than Bernie Sanders’ “shut it all down.” China is very unlikely to join a global agreement, as you know, and that has to be taken into account as well.
So go ahead and pace the frontier. You are the ones setting it. The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system. So just do it.
If you do, you’ll buy goodwill for the next conversation. If you don’t, we’ll know this was just another bid for regulatory capture — or an election-season psyop.
Hemant Virkar retweeted
Today, I shared with the OpenAI team that I have decided to leave my full-time role at OpenAI and transition to being a part-time advisor.
Three months ago, I had to go on medical leave after a severe exacerbation of a chronic illness I’ve lived with for seven years. During that time, it became clear that the road to recovery would be much longer and more complex than I had anticipated—and that I needed to focus on it fully.
When I went on leave, many people told me I was courageous for prioritizing my health. The truth is that I am only making this decision now because I failed to make it many times before.
Over the years, doctors, friends, colleagues, and loved ones encouraged me to slow down. Two years after I got sick, Facebook offered me the opportunity to take a full year of medical leave. I didn’t even pause to consider it. I immediately said no. At the time, Zuck told me I should play the long game. I wish I had listened.
Looking back, I realize that a lot of what made me successful also made this decision incredibly difficult.
I grew up believing that opportunities were precious and that when they appeared, you grabbed them with both hands. That mindset carried me from a small town in southern France to opportunities I never could have imagined. By the time I turned 40, I had already gotten to do more than I’d ever dreamed possible as a kid growing up in Sète.
I love building. My work has always given me a deep sense of purpose. OpenAI in particular felt like a role that my entire career had been building toward, which made this decision even harder.
But what I’m learning now is that grit and endurance are not the only skills required to have impact over decades. Sometimes the harder thing is to stop, listen, and trust that taking care of yourself today makes it possible to contribute for much longer tomorrow.
This experience has also strengthened my conviction about why this work matters.
It has been a jarring experience to spend my days helping build the future while simultaneously navigating a disabling disease that still has no cure.
Over the last seven years, I’ve spent countless hours in doctors’ offices, dealing with symptoms, treatments, insurance, uncertainty, and all the invisible work that comes with being a patient. Like millions of others living with chronic illness, I’ve experienced firsthand how difficult healthcare can be to navigate, even when you have every possible advantage.
More than ever, I believe that some of the most important opportunities for AI lie in helping people solve real problems in their daily lives: their health, their finances, their time and the everyday burdens that shape human experience.
In particular, curing disease is the most important thing AI could accomplish. I’m excited to continue working towards cures through OpenAI but also through my work with @ChronicleBioAI and @CODA_research.
I’m deeply grateful to @sama, @gdb and the OpenAI board for their support during this time and for offering a way for me to continue contributing to the mission without sacrificing my chances of recovery. I’m also so thankful to my team and the many extraordinary colleagues I’ve had the privilege to build alongside.
For now, my focus is recovery. But my belief in the potential of technology to solve deeply human problems has never been stronger.
One pattern I see often:
Teams spend time aligning.
Strong teams spend time deciding.
The difference shows up in what actually gets done.
In practice, complexity rarely comes from the problem.
It comes from too many people trying to shape it at once.
Clarity usually follows ownership.
Most organizations are still asking,
“What AI tools should we use?”
The better question is,
“What outcome are we responsible for?”
One leads to activity.
The other leads to results.
I have yet to see an initiative succeed without this:
A clear outcome.
A single owner.
A defined way to measure progress.
Everything else tends to drift.
In most teams I work with, execution breaks down the same way:
Too many priorities.
Too many experiments.
No clear owner.
None of this is a technology problem.
Just took my first @Waymo ride in Miami. It is awesome. The technology is seamless, and this truly feels like the future of urban mobility. 🌴🚗⚡️ #Waymo #Miami #Innovation #Tech
Hemant Virkar retweeted
We’ve trained a multimodal AI model to turn routine pathology slides into spatial proteomics, with the potential to reduce time and cost while expanding access to cancer care.
Strong leaders do not ask,
“What can AI do?”
They ask,
“What outcome do we need?”
The order matters.
A thoughtful conversation at Wharton this week.
A reminder that leadership is not about having all the answers. It is about asking the right questions and staying focused on outcomes that matter.
If your AI effort cannot be explained in one sentence,
it is not ready to scale.
Clarity is the real prerequisite.
Hemant Virkar retweeted
Rare Disease Day is more than recognition at Digital Infuzion. It reflects work that shaped who we are.
Our N of 1 Health Research Platform was built with rare disease communities including Gaucher, Pompe, Fabry, MPS, and FOP, alongside advocates, researchers, and industry partners.
These collaborations reinforced that progress depends on making complex data usable, connected, and actionable, and recognizing that every dataset represents a patient and family waiting for answers.
We remain committed to enabling research, improving decisions, and advancing care for communities too often overlooked.
#RareDiseaseDay #RareDiseaseAwareness #DigitalHealth #HealthcareInnovation
The hardest part of AI is not adoption.
It is subtraction.
Stopping projects.
Saying no.
Removing noise.
Leaders who cannot subtract fall behind.
AI roadmaps fail when they try to predict the future.
The better approach:
Short horizons.
Fast feedback.
Clear exit criteria.
Adaptation beats prediction.
Keeping up with AI is not about staying current.
It is about staying disciplined.
Clear goals.
Small bets.
Relentless follow through.
The rest is distraction.
Most organizations do not need better AI.
They need clearer ownership.
If no one owns the outcome, the technology will never matter.
Hemant Virkar retweeted
A conventional narrative you might come across is that AI is too far along for a new, research-focused startup to outcompete and outexecute the incumbents of AI. This is exactly the sentiment I listened to often when OpenAI started ("how could the few of you possibly compete with Google?") and 1) it was very wrong, and then 2) it was very wrong again with a whole another round of startups who are now challenging OpenAI in turn, and imo it still continues to be wrong today. Scaling and locally improving what works will continue to create incredible advances, but with so much progress unlocked so quickly, with so much dust thrown up in the air in the process, and with still a large gap between frontier LLMs and the example proof of the magic of a mind running on 20 watts, the probability of research breakthroughs that yield closer to 10X improvements (instead of 10%) imo still feels very high - plenty high to continue to bet on and look for.
The tricky part ofc is creating the conditions where such breakthroughs may be discovered. I think such an environment comes together rarely, but @spectorb & @amspector100 are brilliant, with (rare) full-stack understanding of LLMs top (math/algorithms) to bottom (megakernels/related), they have a great eye for talent and I think will be able to build something very special. Congrats on the launch and I look forward to what you come up with!








