Alexander Berger
@albrgr
Enjoys a good applied micro paper. CEO of @coeff_giving. Views my own, tweets self-destruct every once in a while.
2.2K Following 17.7K Followers
It’s easy to mistake linear gains in ECI for linear gains in model performance. Each additional point actually *multiplies* a model’s odds of success on every benchmark. For example, historically each 5-point increase in ECI corresponded to roughly a doubling in time horizon.
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IFP just spent the last 36 hours poring over the new Manager’s Amendment to the permitting bill.
We went through 27 criticisms of the permit-certainty provisions and over a dozen concerns about historic preservation.
The result is 70 pages of memos showing how the amendment resolves every major permit certainty issue we’ve seen raised and takes significant steps to respond to Tribes on historic preservation review:
1. A 32-page memo analyzing and responding to criticisms of the project certainty provisions:
2. A 4-page memo explaining how the Manager’s Amendment resolves project certainty concerns:
3. A 5-page memo explaining why BAAJA does not prevent the revocation of illegally issued permits:
4. A 3-page memo summarizing historic preservation changes in the manager's amendment and covering how BAAJA protects Tribal consultation from executive action:
5. A 25-page memo explaining how Tribal consultation works in BAAJA, exploring concerns and the Manager's changes in depth:
Not everyone will be happy. If your goal is stopping energy, transit, or housing projects on procedural technicalities, this isn’t the bill for you (although projects that violate substantive environmental law can still be stopped, just not over paperwork violations).
But if your goal is energy affordability and stopping climate change, this is a good bill, and a better bill than it was last week.
All of our permitting reform work can be found here:
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Anthropic revenue update, growth definitely slowed further over the last three months. They added $16B, or ~25% growth, which would naively compound to 2.4x over a year.
There's a little bit of signal from the Q3 revenue total that is not encoded here where Ant probably grew slower in August+September and reaccelerated a bit in October.
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I recommend @ajeya_cotra's post about implications of the AI R&D report. Ajeya argues:
- A 2x speed-up is dramatic.
- 2x faster progress implies a much larger effective "time warp bubble" speed for staff.
- This could compound extremely fast.
- We aren't prepared.
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And there it is
Underappreciated reason fed enviro review is bad:
It applies to multifamily housing with federal assistance, but not single-family
So the best housing for climate and urban vibrancy has to go through red tape, while most sprawl does not
The federal permitting bill fixes this!
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And if we’re serious about improving healthcare, can we please compensate kidney donors, which could reverse stagnant donation rates and help save the ~10k Americans who die every year waiting for a kidney?
There are 47 cosponsors on a bipartisan bill that would do just that:
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BAAJA is an opportunity for Democrats to return to holistic energy policy that balances reliability, affordability, and sustainability.
@IrvingSwisher and I wrote about it for The Argument.
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This has got to be one of the funniest charts of this election cycle @Scott_Wiener
NEW PAPER w/ @_josephshapiro & @heidilwilliams_: In 1947, Congress gave feds power to override states blocking gas (not oil) pipelines.
Gas pipeline growth sped up 6x. Oil didn’t.
The Senate permitting bill does similar for power lines. History strongly suggests it'll work. 🧵
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Climate politics have made Democrats bad at energy policy.
Great new piece from @ArnabDatta321 and @IrvingSwisher in @TheArgumentMag today.
All you need to know.
Neoliberal globalization has delivered a much higher world rate of economic growth if growth is measured across people than when growth is measured (as it is normally done) by implicitly weighting GDP.
In other words, is the weight of the US in the calculation of global growth equal to its share of global output or to its share of global population?
When we do the former, the period after 1981 shows a much slower growth (red: plutocratic growth); but when we do the latter, post-1981 witnessed an acceleration of growth--because of fast growth in populous countries like China and India (blue: democratic).
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It's really something how you can get people to universally denounce "donating money to healthcare for the poor" as unthinkably evil if your analysis of which healthcare to donate to is too callous or weird
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I strongly prefer these kinds of things existing to their not existing, but I have a hard time believing everyone is making the right tradeoffs around redaction and IP. You think this stuff might be catastrophic in very short order!!
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"Since ... I may have access to other confidential information that could be relevant to timelines one way or another, I unfortunately cannot state my all-things-considered views on ASI timelines or the probability of a software intelligence explosion right now"
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This report on AI R&D automation (RSI) is a big update towards ASI within 1-2 years. It says AI progress is sped up by RSI right now by around 2x. In AI 2027, this happens around March 2027.
I was seriously wrong about RSI speed up; I previously expected much less in 2026 (around 1.15x-1.3x). It seems as though there was specific privately available evidence that would have changed my mind.
I haven't seen an unredacted version of this report; this is purely about the public report. Because so much of the underlying evidence was redacted from the public report, I think conclusions about things other than the observed 2x faster rate of progress on benchmarks depend significantly on trust for the authors of the report. (E.g., conclusions about whether this speed up is from RSI depend on trust.) I do trust the authors of the report a lot to be careful and rigorous and generally do a good job. (Note that I also work at METR.) Less extensive redactions would greatly reduce this need for trust.
Since in my current role I may have access to other confidential information that could be relevant to timelines one way or another, I unfortunately cannot state my all-things-considered views on ASI timelines or the probability of a software intelligence explosion right now. Here, I’ve done some analysis of the implications using my previous public statements.
A 2x acceleration in overall AI progress from RSI corresponds to a much larger than 2x RSI speed up for AI software R&D (algorithms and data); I did an estimate using my public preexisting modeling of drivers of AI progress and the public report which yielded a very rough estimate of 4.5x for how much RSI is currently accelerating AI software progress (relative to no AI automation). In the AI 2027 scenario, this much acceleration happens around March 2027.
Here are the worked details of this estimate based on my public modeling. There are two main reasons RSI speed up of AI software R&D must be larger:
- Not all of AI progress is from better software (some is from scaling up compute in training runs). I've previously speculated that around 2/3 of AI progress is from software improvements which implies that 2x overall AI progress acceleration requires 3x faster software progress.
- Diminishing returns: A fixed amount of progress requires more work over time, so to ongoingly maintain 3x faster software progress via AI automation, you need increasingly large speed boosts from AI automation (as in, speed ups relative to how fast software R&D would go without AI automation). Based on this report, it seems that there is a substantial amount of additional AI progress from automation that has occurred.
We can estimate the effects of diminishing returns by first determining how many additional years of software progress we've seen (relative to the preexisting trend) and then estimating how much software R&D would slow down after a year of software progress if you held inputs fixed due to diminishing returns. I've previously estimated software R&D would slow down by around 2x for each year of software progress if you held inputs fixed ( and based on the report, it seems as though we've perhaps seen roughly 0.35-1.0 years of additional software progress incorporated into trained models so far (geometric mean of ~0.6). This combines to 3 * 2^(~0.6) = ~4.5.
(Relevant public modeling and numbers I'm using:
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Another cool contribution to the evidence for moderation having electoral value, using language from candidate websites and finding a 7 point gap between the most and least moderate sounding candidates from @MC_of_A and Joel Wertheimer
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I've always had substantially longer timelines than my friends at Anthropic — I've been concerned that they're in an echo chamber and believing the hype about their own models too much, and that they're underestimating bottlenecks and unknown unknowns. And there have definitely been specific occasions when they have overstated how much uplift they were getting from their models. Nonetheless, if METR is correct here (and I think they are among the most trustworthy sources on this topic), then my Anthropic friends have been much more right about timelines than me.
This report is also some evidence that a software-only singularity is plausible. I now think that we are more than 50% likely to have full blown superintelligence in the next 18 months, absent a slowdown. I need to call my family.
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Morphine is among the cheapest essential medicines there is. Ten days of oral morphine costs about the same as a loaf of bread.
Yet, in most of the world: the need for severe pain relief still goes unmet.
@morganfairlessb in @indevmag:
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I am sad that so much of the underlying evidence in this report was redacted. I think evidence transparency is very important for the world to figure this out in time.
This @TheEconomist cover story on effective altruism was interesting and IMO way more accurate (including in its critiques) than most other reporting you will read on EA these days.
A couple quibbles:
-I think calling EA the “the century’s big idea” is, uh, premature to say the least. But I do appreciate the acknowledgement and curiosity about how EA was so early to pandemic risks and the promise and perils of AI.
-They imply that EA started off with “charitable roots” but then got weird over time, whereas I think EA has always made space for pretty weird ideas (e.g., here’s @DylanMatt in 2014: And EA still puts far more money and attention than almost any other community into the kind of evidence-backed global health giving the Economist praises.
-Some of the purported wild EA views they critique are just standard topics of academic philosophy debate (e.g.,
-They attribute the EA interest in AI safety to longtermism, but I think it’s been clear for years that AI safety concerns are justifiable based on potential impacts this decade, not to mention this century (
But I think they correctly gesture towards the IMO best critique of EA ideas, which is their totalizingness. My former colleague Holden wrote a great post about this in 2022:
I wrote a long thread grappling with this critique a few years ago ( I think part of what makes EA distinctive as a community relative to the underlying academic moral philosophy is the orientation around pragmatism - Giving What We Can took off decades after Singer had articulated the underlying case because “give until the marginal giving would entail as much suffering for you as benefit for the other person” was a much worse pitch than “give 10%.” But the community doesn’t always reflect that healthy moderation, and trying to grapple with the vertiginous stakes of increasingly near-term risks from AI really can run a risk of crowding out other sources of value.
At CG, our response to this has been worldview diversification ( spreading our giving across very different views of what matters, rather than going all-in on one. Worldview diversification leaves plenty of hard questions (how do you allocate the pie across very different types of moral good?) but helps cut off some of the ways maximizing can be perilous. It’s one reason global health and wellbeing – which @TheEconomist didn’t give the space it deserved – has gotten most of our funding since 2014.
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