maxwells-daemon

Joined 6 years ago

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Member since
Sep 23
I'm a machine learning researcher at Harmonic (ex-NVIDIA) working on automated theorem proving.

Site: https://aidanswope.com/ Email: [email protected]

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Recent submissions

Comment · 2 months ago
Sorry if this sounds like a dumb question, but I legitimately don't know: does the thermodynamic argument hold up? (Broadly, I agree that humanity needs a healthier relationship with industrialism before fixing this is possible).

A few ways I can imagine it doesn't:

- We can reduce warming by other means, like changing the Earth's albedo.

- A lot more energy falls to Earth every day from the sun than we use via petroleum; a good amount of solar/wind would let us climb back up the hill via sequestration.

- We don't need to sequester CO2/methane into high-energy-density hydrocarbons; could an efficient sequestration process yield eventually net positive energy per unit greenhouse gas from the burn -> sequester process?

Comment · 2 months ago
My college (Caltech) was pass/fail (no quantified grades) for the first couple of terms, and I thought it worked very well. It did alleviate the some of the stress of beginning a higher-expectations environment, but it also let students explore classes they wouldn't have if they had to worry about GPA. I know a few people that changed their whole field as a result; the geology department was known to pick up students this way.
Comment · 3 months ago
Funny enough, I had some valuable stuff (including my passport!) stolen from my car, which I'd left unlocked because I was moving some heavy boxes. The police in my area (bay area) said they couldn't really do anything about it because they didn't break a window.

I don't know exactly what legal technicalities are involved, but this did actually happen to me in a de facto sense!

Comment · 3 months ago
As someone who also used to overthink memorizing the fretboard: this is a bad idea. You should strive to just plainly memorize the names of all of the notes, the relevant scale and arpeggio patterns, etc, without any kind of tricks or "system" (no, not CAGED either). This is the only path to real fluency; imagine having a neat system of remembering what each English word means and having to go through it every time you wanted to speak!
Comment · 5 months ago
I have exactly the same problem in my (latest-model) Honda Civic / Android Auto! I thought I was going crazy, I'm glad to hear someone else has the same problem.

The only fix I've found is to disconnect the phone and use its map standalone, just sending audio over Bluetooth. Maybe it's possible to get Android Auto or Carplay to reject GPS data from the car? I don't know...

Comment · 8 months ago
It's true, but most of the cultural innovation I'm aware of, from Bach to Coltrane to Hendrix, came from people who could make art their life, largely by paying the bills with it. I don't think we'll lose art entirely, but we might lose the greatest artists.
Comment · 8 months ago
That isn't how it works. Jimi Hendrix, the Beatles, and most other innovators were regular working artists long before they were influential. If you take away the means for artists to sell work that isn't boundary-pushing, they won't get enough practice and exposure to make influential work later.
Comment · 9 months ago
Aristotle's output is formally verified in Lean, so you can run it for days on a hard problem and be assured that the answer, no matter how complex, is right without needing to manually check it.

Claude Code can write lean, but we do a heck of a lot of RL on theorem proving, so Aristotle winds up being much better at writing Lean than other coding agents are.

Comment · 9 months ago
Yes! I think that working with Mathlib is the best long term solution, because it's how people already collaborate on building out the formal "universe of mathematics." We want to speed that up, and hopefully we'll cover all of the common topics very soon!
Comment · 9 months ago
For this reason, when we announce results on e.g. the IMO, we formalize the statements by hand and inspect the proofs carefully to ensure they capture the full spirit of the problem.

However, there are some good heuristics. If you expect a problem to be hard and the proof is very short, you've probably missed something!

Comment · 9 months ago
Thank you! It depends on the topic. Some fields (algebra, number theory) are covered well by Lean's math library, and so I think we are already there; I recommend trying Aristotle for yourself to see how reliably it can formalize these theorems!

In other fields (topology, probability, linear algebra), many key definitions are not in Mathlib yet, so you will struggle to write down the theorem itself. (But in some cases, Aristotle can define the structure you are talking about on the fly!)

This is not an intrinsic limitations of Lean, it's just that nobody has taken the time to formalize much of those fields yet. We hope to dramatically accelerate this process by making it trivial to prove lemmas, which make up much of the work. For now, I still think humans should write the key definitions and statements of "central theorems" in a field, to ensure they are compatible with the rest of the library.

Comment · 9 months ago
We are! We very recently announced some results on formally proving the correctness of programs: https://harmonic.fun/news#blog-post-verina-bench-sota

Formal methods are cool because, by contrast to tools like the borrow checker, you can prove some very "nonlocal" properties: this system does not deadlock, or it makes progress at least every N steps, etc.

Comment · 9 months ago
I work at Harmonic, the company behind Aristotle.

To clear up a few misconceptions:

- Aristotle uses modern AI techniques heavily, including language modeling.

- Aristotle can be guided by an informal (English) proof. If the proof is correct, Aristotle has a good chance at translating it into Lean (which is a strong vote of confidence that your English proof is solid). I believe that's what happened here.

- Once a proof is formalized into Lean (assuming you have formalized the statement correctly), there is no doubt that the proof is correct. This is the core of our approach: you can do a lot of (AI-driven) search, and once you find the answer you are certain it's correct no matter how complex the solution is.

Happy to answer any questions!

Comment · 10 months ago
There are a couple of interesting benefits from the machine learning side that I think discussions of this kind often miss. (This has been my field of research for the last few years [1][2]; I bet my career on it because these ideas are so exciting to me!)

One is that modern formal systems like Lean are quite concise and flexible compared to what you're probably expecting. Lean provides the primitives to formalize all kinds of things, not just math or software. In fact, I really believe that basically _any_ question with a rigorous yes-or-no answer can have its semantics formalized into a kind of "theory". The proofs are often close to how an English proof might look, thanks to high-level tactics involving automation and the power of induction.

Another is that proof-checking solves what are (in my opinion) two of the biggest challenges in modern AI: reward specification and grounding. You can run your solver for a long time, and if it finds an answer, you can trust that without worrying about reward hacking or hallucination, even if the answer is much too complicated for you to understand. You can do RL for an unlimited time for the same reason. And Lean also gives you a 'grounded' model of the objects in your theory, so that the model can manipulate them directly.

In combination, these two properties are extremely powerful. Lean lets us specify an unhackable reward for an extremely diverse set of problems across math, science, and engineering, as well as a common environment to do RL in. It also lets us accept answers to questions without checking them ourselves, which "closes the loop" on tools which generate code or circuitry.

I plan to write a much more in-depth blog post on these ideas at some point, but for now I'm interested to see where the discussion here goes.

[1] https://leandojo.org/leandojo.html [2] https://aristotle.harmonic.fun/

Comment · 1 year ago
Maybe there's a middle ground: a site that wants to work as well as possible for agents could present a stripped-down standardized page depending on the user agent string, while the agent tries to work well even for pages that haven't implemented that interface?

(or, perhaps, agents could use web accessibility tools if they're set up, incentivizing developers to make better use of them)

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