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Scott Aaronson has a nice post discussing recent experimental progress in quantum computing from Google, Microsoft, and Quantinuum. In particular, he says
Let me end by sticking my neck out. If hardware progress continues at the rate we’ve seen for the past year or two, then I find it hard to understand why we won’t have useful fault-tolerant QCs within the next decade. (And now to retreat my neck a bit: the “if” clause in that sentence is important and non-removable!)
If you’ll permit me to indulge, I’d like to compare the reported progress to the predictions from the 2020 forecasting paper by Jaime Sevilla and me.
I understand the Google results to be that they have ~10-3 physical two-qubit error rates and they they would have ~10-6 logical error rates if they had ~1500 physical qubits, but they actually have 101 in the present device.
For forecasting purposes, Jaime and I defined a figure of merit, the “generalized logical qubit” (GLQ) count. See Eq. (1) and Fig. 1. It essentially equals the surface-code logical qubit count in the limit of low errors and many qubits (assuming we demand 10-18 logical error rate), but is smoothly defined with fractional values when error rates are larger and/or physical qubit counts are smaller. Our naive (log linear regression) forecast from data at the time was that 1 GLQ would be achieved 2026-2033 and 4,100 GLQs (the rough number necessary to be cryptographically dangerous) would be achieved in 2029-2060 (both 90% confidence intervals — not Bayesian credences!). Our forecasts for 2024 were 0.02-0.3 GLQs.
I’m pleased to see that the above Google numbers correspond to a GLQ count of about 0.03, which is consistent with our model (though this is perhaps not impressive since it’s only been 4 years and our confidence intervals were wide).… [continue reading]
[Jaime Sevilla is a Computer Science PhD Student at the University of Aberdeen. In this guest post, he describes our recent forecasting work on quantum computing. – Jess Riedel]
Advanced quantum computing comes with some new applications as well as a few risks, most notably threatening the foundations of modern online security.
In light of the recent experimental crossing of the “quantum supremacy” milestone, it is of great interest to estimate when devices capable of attacking typical encrypted communication will be constructed, and whether the development of communication protocols that are secure against quantum computers is progressing at an adequate pace.
Beyond its intrinsic interest, quantum computing is also fertile ground for quantified forecasting. Exercises on forecasting technological progress have generally been sparse — with some notable exceptions — but it is of great importance: technological progress dictates a large part of human progress.
To date, most systematic predictions about development timelines for quantum computing have been based on expert surveys, in part because quantitative data about realistic architectures has been limited to a small number of idiosyncratic prototypes. However, in the last few years the number of device has been rapidly increasing and it is now possible to squint through the fog of research and make some tentative extrapolations. We emphasize that our quantitative model should be considered to at most augment, not replace, expert predictions. Indeed, as we discuss in our preprint, this early data is noisy, and we necessarily must make strong assumptions to say anything concrete.… [continue reading]
In this post I review the 2010 book “Lifecycle Investing” by Ian Ayres and Barry Nalebuff. (Amazon link here; no commission received.) They argue that a large subset of investors should adopt a (currently) unconventional strategy: One’s future retirement contributions should effectively be treated as bonds in one’s retirement portfolio that cannot be efficiently sold; therefore, early in life one should balance these low-volatility assets by gaining exposure to volatile high-return equities that will generically exceed 100% of one’s liquid retirement assets, necessitating some form of borrowing.
“Lifecycle Investing” was recommended to me by a friend who said the book “is extremely worth reading…like learning about index funds for the first time…Like worth paying 1% of your lifetime income to read if that was needed to get access to the ideas…potentially a lot more”. Ayres and Nalebuff lived up to this recommendation. Eventually, I expect the basic ideas, which are simple, to become so widespread and obvious that it will be hard to remember that it required an insight.
In part, what makes the main argument so compelling is that (as shown in the next section), it is closely related to an elegant explanation for something we all knew to be true — you should increase the bond-stock ratio of your portfolio as you get older — yet previously had bad justifications for. It also gives new actionable, non-obvious, and potentially very important advice (buy equities on margin when young) that is appropriately tempered by real-world frictions.… [continue reading]
[Tina White is a friend of mine and co-founder of COVID Watch, a promising app for improving contact tracing for the coronavirus while preserving privacy. I commissioned Tom Higgins to write this post in order to bring attention to this important project and put it in context of related efforts. -Jess Riedel]
Countries around the world have been developing mobile phone apps to alert people to potential exposure to COVID-19. There are two main mechanism used:
The first mechanism generally uses the phone’s location data, which is largely inferred from GPS.a The second method can also be accomplished with GPS, by simply measuring the distance between users, but it can instead be accomplished with phone-to-phone bluetooth connections… [continue reading]
I’ve been mulling for a long time whether to stay in physics, and a colleague pointed me toward this Master’s thesis on career regret by Hennessey.
In this blog post I’ll mostly just pull out notable excerpts. I encourage you to read the thesis if this catches your interest. (See also Hanson on deathbed regrets.)
From the introduction:
If you work full time for thirty years the number of hours spent on the job would be approximately 60,000…
… [continue reading]What if you never figured out what you want to do with your life? What if you spent your whole life searching and never found the work you wanted?
I was privileged to receive a reply from Robin Hanson on my critique of his largely excellent book The Elephant in the Brain with co-author Kevin Simler. I think in several cases he rebutted something other than what I argued, but I encourage you to read it and judge for yourself.
Given the high-profile book reviews that are probably forthcoming from places like the Wall Street Journal, I thank Robin for taking the time to engage with the little guys!
I’ll follow Robin’s lead and switch to first names.
Some say we should have been more academic and detailed, while other say we should have been more accessible and less detailed….Count Jess as someone who wanted a longer book.
It’s true that I’d have preferred a longer book with more details, but I think I gestured at ways Kevin and Robin could hold length constant while increasing convincingness. And there are ways of keeping the book accessible while augmenting the rigor (e.g., endnotes), although of course they are more work.
Yes for each motive one can distinguish both a degree of consciousness and also a degree of current vs past adaptation. But these topics were not essential for our main thesis, making credible claims on them takes a lot more evidence and argument, and we already had trouble with trying to cover too much material for one book.
I was mostly happy with how the authors handled the degree of consciousness. However, I think the current- vs past-adaptation distinction is very important for designing institutions, which Kevin and Robin correctly list as one of the main applications of the book’s material. For instance, should the arXiv host comments on papers, and how should they be implemented to avoid pissing contests?… [continue reading]
Drawing on a large academic literature in topics like sociology, behavioral economics, anthropology, and psychology, and especially the (generalized) theory of signalling, Robin Hanson has assembled a large toolbox for systemically understanding hypocrisy, i.e., the ways in which people’s actions systematically and selfishly deviate from their verbalized explanations. Although he would be the first to admit that many of these ideas have been discovered and rediscovered repeatedly over centuries (or millennia) with varying degrees of clarity, and although there is much I am not convinced by, I find the general framework deeply insightful, and his presentation to be more clear, analytical, and descriptive (rather than disruptively normative) than other accounts. Most of this I have gathered from his renowned blogging at Overcoming Bias, but I have always wished for a more concise (and high status!) form factor that I could point others to. At long last, Hanson and his co-author Kevin Simler have written a nice book that largely satisfies me: The Elephant in the Brain (Amazon). I highly recommend it.
The reason I title these sorts of blog posts “Comments on…” is so I can present some disorganized responses to a work without feeling like I need to build a coherent thesis or pass overall judgment. I do not summarize the book below, so this post will mostly be useful for people who have read it. (You might think of this as a one-sided book club discussion rather than a book review.) But since I will naturally tend to focus on the places where I disagree with the authors, let me emphasize: the basic ideas of this book strike me as profound and probably mostly true.… [continue reading]
Branching theories vs. collapse theories
For maximum flexibility, foreXiv by C. Jess Riedel is multi-licensed separately under CC BY-SA 4.0, CC BY-NC-SA 4.0, and GFDL 1.3.
