2026-03-06 07:36:31
To start on a somber note: those of us at UT Austin are in mourning this week for Savitha Shan, an undergrad double major here in economics and information systems, who was murdered over the weekend by an Islamist terrorist who started randomly shooting people on Sixth Street, apparently angry about the war in Iran. Two other innocents were also killed.
As it happens, these murders happened just a few hours after the end of my daughter’s bat mitzvah, and in walking distance from the venue. The bat mitzvah itself was an incredibly joyful and successful event that consumed most of my time lately, and which I might or might not say more about—the nastier the online trolls get, the more I need to think about my family’s privacy.
Of all the many quantum computing podcasts/interviews I’ve done recently, I’m probably happiest with this one, with Yuval Boger of QuEra. It covers all the main points about where the hardware currently is, the threat to public-key cryptography, my decades-long battle against quantum applications hype, etc. etc., and there’s even an AI-created transcript that eliminates my verbal infelicities!
A month ago, I blogged about “The Time I Didn’t Meet Jeffrey Epstein” (basically, because my mom warned me not to). Now the story has been written up in Science magazine, under the clickbaity headline “Meet Three Scientists Who Said No to Epstein.” (Besides yours truly, the other two scientists are friend-of-the-blog Sean Carroll, whose not-meeting-Epstein story I’d already heard directly from him, and David Agus, whose story I hadn’t heard.)
To be clear: as I explained in my post, I never actually said “no” to Epstein. Instead, based on my mom’s advice, I simply failed to follow up with his emissary, to the point where no meeting ever happened.
Anyway, ever since Science ran this story and it started making the rounds on social media, my mom has been getting congratulatory messages from friends of hers who saw it!
I’ve been a huge fan of the philosopher-novelist Rebecca Newberger Goldstein ever since I read her celebrated debut work, The Mind-Body Problem, back in 2005. Getting to know Rebecca and her husband, Steven Pinker, was a highlight of my last years at MIT. So I’m thrilled that Rebecca will be visiting UT Austin next week to give a talk on Spinoza, related to her latest book The Mattering Instinct (which I’m reading right now), and hosted by me and my colleague Galen Strawson in UT’s philosophy department. More info is in the poster below. If you’re in Austin, I hope to see you there!
The 88-year-old Donald Knuth has published a 5-page document about how Claude was able to solve a tricky graph theory problem that arose while he was working on the latest volume of The Art of Computer Programming—a series that Knuth is still writing after half a century. As you’d expect from Knuth, the document is almost entirely about the graph theory problem itself and Claude’s solution to it, eschewing broader questions about the nature of machine intelligence and how LLMs are changing life on Earth. To anyone who’s been following AI-for-math lately, the fact that Claude now can help with this sort of problem won’t come as a great shock. The virality is presumably because Knuth is such a legend that to watch him interact productively with an LLM is sort of like watching Leibniz, Babbage, or Turing do the same.
John Baez is a brilliant mathematical physicist and writer, who was blogging about science before the concept of “blogging” even existed, and from whom I’ve learned an enormous amount. But regarding John’s quest for the past 15 years — namely, to use category theory to help solve the climate crisis (!) — I always felt like the Cookie Monster would, with equal intellectual justification, say that the key to arresting climate change was for him to eat more Oreos. Then I read this Quanta article on the details of Baez’s project, and … uh … I confess it failed to change my view. Maybe someday I’ll understand why it’s better to say using category theory what I would’ve said in a 100x simpler way without category theory, but I fear that day is not today.
2026-02-28 03:37:50
I don’t have time to write a full post right now, but hopefully this is self-explanatory.
Regardless of their broader views on the AI industry, the eventual risks from AI, or American politics, right every person of conscience needs to stand behind Anthropic, as they stand up for their right to [checks notes] not be effectively nationalized by the Trump administration and forced to build murderbots and to help surveil American citizens. No, I wouldn’t have believed this either in a science-fiction movie, but it’s now just the straightforward reality of our world, years ahead of schedule. In particular, I call on all other AI companies, in the strongest possible terms, to do the right thing and stand behind Anthropic, in this make-or-break moment for the AI industry and the entire world.
2026-02-20 14:31:16
2026-02-16 02:05:54
So, a group based in Sydney, Australia has put out a preprint with a new estimate of the resource requirements for Shor’s algorithm, claiming that if you use LDPC codes rather than the surface code, you should be able to break RSA-2048 with fewer than 100,000 physical qubits, which is an order-of-magnitude improvement over the previous estimate by friend-of-the-blog Craig Gidney. I’ve now gotten sufficiently many inquiries about it that it’s passed the threshold of blog-necessity.
A few quick remarks, and then we can discuss more in the comments section:
2026-02-13 00:18:21
The following are prepared remarks that I delivered by Zoom to a student group at my old stomping-grounds of MIT, and which I thought might interest others (even though much of it will be familiar to Shtetl-Optimized regulars). The students asked me to share my “optimistic vision” for the year 2050, so I did my best to oblige. A freewheeling discussion then followed, as a different freewheeling discussion can now follow in the comments section.
I was asked to share my optimistic vision for the future. The trouble is, optimistic visions for the future are not really my shtick!
It’s not that I’m a miserable, depressed person—I only sometimes am! It’s just that, on a local level, I try to solve the problems in front of me, which have often been problems in computational complexity or quantum computing theory.
And then, on a global level, I worry about the terrifying problems of the world, such as climate change, nuclear war, and of course the resurgence of populist, authoritarian strongmen who’ve turned their backs on the Enlightenment and appeal to the basest instincts of humanity. I won’t name any names.
So then my optimistic vision is simply that we survive all this—“we” meaning the human race, but also meaning communities that I personally care about, like Americans, academics, scientists, and my extended family. We survive all of it so that we can reach the next crisis, the one where we don’t even know what it is yet.
But I get the sense that you wanted more optimism than that! Since I’ve spent 27 years working in quantum computing, the easiest thing for me to do would be to spin an optimistic story about how QC is going to make our lives so much better in 2050, by, I dunno, solving machine learning and optimization problems much faster, curing cancer, fixing global warming, whatever.
The good news is that there has been spectacular progress over the past couple years toward actually building a scalable QC. We now have two-qubit gates with 99.9% accuracy, close to the threshold where quantum error-correction becomes a net win. We can now do condensed-matter physics simulations that give us numbers that we don’t know how to get classically. I think it’s fair to say that all the key ideas and hardware building blocks for a fault-tolerant quantum computer are now in place, and what remains is “merely” the staggeringly hard engineering problem, which might take a few years, or a decade or more, but should eventually be solved.
The trouble for the optimistic vision is that the applications, where quantum algorithms outperform classical ones, have stubbornly remained pretty specialized. In fact, the two biggest ones remain the two that we knew about in the 1990s:
Quantum simulation could help with designing better batteries, or solar cells, or high-temperature superconductors, or other materials, but the road from improved understanding to practical value is long and uncertain. Meanwhile, breaking public-key cryptography could help various spy agencies and hackers and criminal syndicates, but it doesn’t obviously help the world.
The quantum speedups that we know outside those two categories—for example, for optimization and machine learning—tend to be either modest or specialized or speculative.
Honestly, the application of QC that excites me the most, by far, is just disproving all the people who said QC was impossible!
So much for QC then.
And so we come to the elephant in the room—the elephant in pretty much every room nowadays—which is AI. AI has now reached a place that exceeds the imaginations of many of the science-fiction writers of generations past—excelling not only at writing code and solving math competition problems but at depth of emotional understanding. Many of my friends are terrified of where this is leading us—and not in some remote future but in 5 or 10 or 20 years. I think they’re probably correct to be terrified. There’s an enormous range of possible outcomes on the table, including ones where the new superintelligences that we bring into being treat humans basically as humans treated the dodo bird, or the earlier hominids that used to share the earth with us.
But, within this range of outcomes, I think there are also some extremely good ones. Look, for millennia, people have prayed to God or gods for help, life, health, longevity, freedom, justice—and for millennia, God has famously been pretty slow to answer their prayers. A superintelligence that was aligned with human values would be nothing less than a God who did answer, who did deliver all those things, because we had created it to do so. Or for religious people, perhaps such an AI would be the means by which the old God was finally able to deliver all those things into the temporal world. These are the stakes here.
To switch metaphors, people sometimes describe the positive AI-enabled future as “luxury space communism.” AI would take care of all of our material needs, leaving us to seek value in our lives through family, friendships, competition, hobbies, humor, art, entertainment, or exploration. The super-AI would give us the freedom to pursue all those things, but would not give us the freedom to harm each other, to curtail each others’ freedoms, or to build a bad AI capable of overthrowing it. The super-AI would be a singleton, a monotheistic God or its emissary on earth.
Many people say that something would still be missing from this future. After all, we humans would no longer really be needed for anything—for building or advancing or defending civilization. To put a personal fine point on it, my students and colleagues and I wouldn’t needed any more to discover new scientific truths or to write about them. That would all be the AI’s job.
I agree that something would be lost here. But on the other hand, what fraction of us are needed right now for these things? Most humans already derive the meaning in their lives from family and community and enjoying art and music and food and things like that. So maybe the remaining fraction of us should just get over ourselves! On the whole, while this might not be the best future imaginable, I would accept it in a heartbeat given the realistic alternatives on offer. Thanks for listening.
2026-02-10 11:29:11
This is just a quick announcement that I’ll be hosting Nate Soares—who coauthored the self-explanatorily titled If Anyone Builds It, Everyone Dies with Eliezer Yudkowsky—tomorrow (Tuesday) at 5PM at UT Austin, for a brief talk followed by what I’m sure will be an extremely lively Q&A about his book. Anyone in the Austin area is welcome to join us.