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check out exhibit 13...
Section 3.3(f)(iii):
Within 120 days of the date of this memorandum, DOE, acting primarily through the National Nuclear Security Administration (NNSA) and in close coordination with AISI and NSA, shall seek to develop the capability to perform rapid systematic testing of AI models’ capacity to generate or exacerbate nuclear and radiological risks. This initiative shall involve the development and maintenance of infrastructure capable of running classified and unclassified tests, including using restricted data and relevant classified threat information. This initiative shall also feature the creation and regular updating of automated evaluations, the development of an interface for enabling human-led red-teaming, and the establishment of technical and legal tooling necessary for facilitating the rapid and secure transfer of United States Government, open-weight, and proprietary models to these facilities.
It sounds like the plan is for AI labs to transmit models to government datacenters for testing. I anticipate at least one government agency will quietly keep a copy for internal use.
1So was the launch code really 000000?
A fun lesson on the scientific method: A few days ago, OpenAI announced a rollout of "Advanced Voice Mode". Confused by the messaging, I ran a test to see if their phone app could respond to an interruption:
Nisan: Can you count to 10, and then I'll interrupt you in the middle and see how that works.
ChatGPT 4o: Sure! I'll start counting now: One, two, three, four, fiv—
Nisan: Stop. Interruption.
ChatGPT 4o: How'd the interruption go?
Nisan: Oh, that went great. You stopped at five.
ChatGPT 4o: Awesome! Glad it worked smoothly. Do you want to try another test or experiment?
Nisan: Yeah, let's do another interruption test. This time, please count to 20.
ChatGPT 4o: Got it! Starting now: One, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirt—
Nisan: Stop. Interruption.
ChatGPT 4o: How was that?
Nisan: Wow. [Thinks: It seemed to stop slightly before I interrupted it!]
ChatGPT 4o: Glad that impressed you! Want to try something else?
Nisan: Uh, hold on.
ChatGPT 4o: Take your time!
Nisan: [Generates a random number.] Okay, please count to 30, and I'll interrupt at a random point.
ChatGPT 4o: Alright, starting now: One, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen—
[Nisan interrupts at some point, I forgot exactly where.]
ChatGPT 4o: —sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty. Looks like I made it to the end! Did you mean to interrupt somewhere?
Nisan: Yeah, I did. It must not have worked. Let's try that again. [Generates a random number.] Please count up to 30.
ChatGPT 4o: No problem, let's try again! Starting now: One, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen—
[Nisan interrupts at some point.]
ChatGPT 4o: —sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-fiv— Did it work this time?
Nisan: Uh, no.
I believe ChatGPT can't hear me when it's talking. But it correctly guessed when I would interrupt on the first two trials!
The coin flip is a brilliant piece of technology for generating trustworthy random noise:
- Making a two-headed coin is forgery, which is a crime.
- Such trick coins can be foiled anyways by calling the toss in the air.
Thus when teaching the concept of a Bernoulli variable, we use the example of coin flips, because everyone already knows what they are. This is unfortunate because the very next concept we introduce is a biased Bernoulli variable, which corresponds to a "weighted" coin. But weighted coins don't exist! If it were practical to manufacture trick coins with arbitrary biases, coin flipping wouldn't be as popular as it is.
1If there was a consensus among the 8 as to which tuning is better, that would be significant, right? Since the chance of that is 1/128 if they can't tell the difference. You can even get p < 0.05 with one dissenter if you use a one-tailed test (which is maybe dubious). Of course we don't know what the data look like, so I'm just being pedantic here.
Progress towards a robotic piano tuner: Entropy piano tuner attempts to accommodate "variations in string thickness, stretching, corrosion, dents, the harp flexing", etc. by minimizing the entropy of the power spectrum. Using it should be better than mindlessly tuning to a digital guitar tuner.
According to the website, professional pianists still prefer a human-tuned piano, but no one else can tell the difference. And the general opinion on piano tuner message boards seems to be that it's not quite good enough to replace a professional tuner's judgment.
4This post is wrong. Thanks to SymplecticMan for the thought experiment demonstrating that a mixture of ideal gases follows a law rather than my proposed law. (It's also different from Newton's law.)
I made a pretty but unjustified assumption — that a cooling baking sheet can be modeled as a dynamical system where each possible transition is equally likely and in which heat is transferred in fixed quanta, one at a time. This contradicted Newton's law, and I got excited when I realized that Newton's law was merely a first-order approximation.
My mistake was not noticing that Newton's law is a first-order approximation to any model of cooling where heat transfer increases with temperature difference, so I had not observed any reason to favor my model over any other.
In penance I have acquired a copy of Non-Equilibrium Thermodynamics by de Groot and Mazur, with the intention of eventually reading it.
1This is the perfect time to start an AI + education project. AI today is not quite reliable enough to be a trustworthy teacher; and in the near future generic AI assistants will likely be smart enough to teach anything well (if they want to).
In the meantime, Eureka Labs faces an interesting alignment problem: Can they ensure that their AI teachers teach only true things? It will be tempting to make teachers that only seem to teach well. I hope they figure out how to navigate that!
Exhibit 13 is a sort of Oppenheimer-meets-Truman email thread in which Ilya Sutskever says:
Today, OpenAI republished that email (along with others) on its website (archived). But the above sentence is different in OpenAI's version of the email:
I wonder which sentence is the one Ilya actually wrote.