A couple of other things that stand out to me as particularly egregious:

• My understanding is that Trump is far more corrupt than past presidents (including Trump in his first term). An example of this is allowing export controls of Nvidia's AI chips to China in exchange for gifts from Jensen Huang.
• The Trump administration has launched criminal investigations against political opponents at an unprecedented rate, most recently against Jerome Powell yesterday.
• And of course, the fake electors plot to steal the 2020 presidential election (not to be confused with January 6th -- I think his conduct on January 6th was really bad, but the fake electors plot is a much greater indictment of Trump's character and much stronger evidence of his authoritarianism).

We finally did it, we found the median voter!

I think that by far the most important thing in this space is for a Democrat to win the 2028 presidential election. And I think the most important thing for making that happen is to nominate a Democrat whose positions on the issues are relatively close to the median voter.

We can get a sense of this by seeing how much potential Democratic candidates outperformed fundamentals (i.e. what you would have predicted given the state they were running in and the political environment that year). Some candidates who have done well on this metric include:

• Andy Beshear (governor of Kentucky, a really red state)
• Josh Shapiro (governor of Pennsylvania, a swing state, where he won his election by a large margin)
• Amy Klobuchar (senator from Minnesota)
• Ruben Gallego (senator from Arizona)
• Mark Kelly (senator from Arizona)
• Raphael Warnock (senator from Georgia)

Some candidates who have not done well on this metric include:

• Gavin Newsom
• Kamala Harris
• Tim Walz
• AOC
• [Edited to add] Elizabeth Warren fares particularly badly on this metric, though I don't think she'll run in 2028

Anthropic: “we expect powerful AI systems will emerge in late 2026 or early 2027… Intellectual capabilities matching or exceeding that of Nobel Prize winners across most disciplines… The ability to navigate all interfaces available to a human doing digital work today… The ability to autonomously reason through complex tasks over extended periods—hours, days, or even weeks… The ability to interface with the physical world”

This is kind of annoyingly phrased, because it sounds like they're saying that AIs will be making Nobel Prize-level discoveries by late 2026 or early 2027. But in fact that's not what they're saying. They're only claiming that AIs will be capable of doing tasks that Nobel Prize winners could do in hours or days (or maybe even weeks) -- whereas Nobel Prize-level discoveries take years.

Bores repeatedly addressed concerns about regulatory burden by saying that frontier AI developers' own memos said this bill would add 1 full time employee, and so wasn't that burdensome. 

• I'd be surprised if this was true and very surprised if it's what frontier developers said even if it was true, given their incentives. I'm waiting to hear back on the memo

As far as I can tell, Bores never said that frontier AI developers' own memos said this; rather, it was that an opposition memo said this. Bores mentions this memo a few times during the 90 minutes; here's a typical quote:

I'll note that what came in as an opposition memo said that they estimated that this would require one full-time employee to comply with.

I believe that this is the memo that Bores was talking about. It was written by Will Rinehart of the American Entreprise Institute, which opposed the bill.

I just found myself here (two years later) because of a discussion about Control AI. I feel conflicted but am closer to agreeing than disagreeing with your comment. I think that my original comment was somewhat written in soldier mindset.

Thanks for the suggestion!

For what it's worth, we believe that a mechanistic estimator can beat all sampling-based methods, no matter how sophisticated they are. The philosophical reason for this is that sophisticated sampling-based methods outperform simple Monte Carlo by exploiting structure in the function whose average value they're estimating -- but a mechanistic estimator can exploit that same structure, too.

In fact, I think it almost follows from the MSP that we can beat any sampling-based method. To see this, suppose you have some sophisticated estimator $\text{Est}(M_{\theta },r)$, which is given a neural net $M_{\theta }$ and some random coin flips $r$ as input, and produces a sophisticated, unbiased, low-variance estimate of $E\left[M_{\theta }\right]$ using $r$. Now, define the architecture $M^{\prime }$ as: $M_{\theta }^{\prime }\left(x\right)=\text{Est}(M_{\theta },x)$. The MSP says that we need to be able to estimate the average output of $M_{\theta }^{\prime }$ (which is the same as the average output of $M_{\theta }$) with squared error less than or equal to the variance of $M_{\theta }^{\prime }$, in the time that it takes to run $M_{\theta }^{\prime }$. (We're taking $\epsilon =1$ here.) In other words, given any sophisticated sampling algorithm for estimating the average output of $M_{\theta }$, there needs to be a corresponding mechanistic estimator that gets lower (or equal) error in the same amount of time.

(I think this argument isn't perfectly tight, because it'll probably run into the same uniformity issues that I discussed in the "getting rid of $\epsilon$" appendix, which is why I said "almost follows" rather than "follows".)

Note that "toss-up" races are races where the general election (i.e. between the Democratic and Republican candidates) is a toss-up. By guess is that in such races, an extra $2,500 spent on TV ads is necessary to net a candidate one extra vote. This is because the pool of persuadable voters is much smaller: most voters will vote for the Democrat no matter what or vote for the Republican no matter what. By contrast, spending goes a lot further in primary elections.

There’s a cottage industry that thrives off of sneering, gawking, and maligning the AI safety community. This isn't new, but it's probably going to become more intense and pointed now that there are two giant super PACs that (allegedly) see safety as a barrier to [innovation/profit, depending on your level of cynicism]. Brace for some nasty, uncharitable articles.

One such article came out yesterday; I think it's a fairly representative example of the genre.

My guess for Bores was:

• 25% better to donate on first day than second day
• 2x better to donate in late 2025 than 2026

I think that similarly for Wiener, I don't think it makes a huge difference (maybe 15% or so?) whether you donate today vs. late December. Today vs. tomorrow doesn't make much difference; think of it as a gradual decay over these couple months. But I think it's much better (1.3x?) to donate in late December than early January, because having an impressive Q4 2025 fundraising number will be helpful for consolidating support. (Because Wiener is more of a known quantity to voters and party elites than Bores is, this is a less important factor for Wiener than it is for Bores.)