t6aguirre's Quick takes

Some notes on OpenAI disproving the Erdős unit distance conjecture (from a non-mathematician):

• First, this is big. A notorious math conjecture being disproved by AI would be sci-fi 10 years ago. In my layman's read, this is plausibly the most prominent math result in the last 12 months -- AI, centaur, human or whatever.
• Second, it rebutted an Erdős conjecture, and I found it curious that the first clear math breakthrough goes against consensus. There are a few potential reads to this: a) this seems to go against the LLMs-are-sycophantic-machine claims; b) even if LLMs are that sycophantic, exploring different intellectual paths is so cheap to them that sycophancy doesn't quite matter as much; c) it may mean that AI is sycophantic at the user-level but not at the literature-level, which actually may be great for finding novel solutions,  but is also the very thing that enables e.g. AI psychosis.
• Third, it's hard to wrap my head around having an intelligence that is probably at the level of a very promising Terence Tao graduate student -- but not Tao-level yet. It allows exploring many hypotheses/conjectures/counter-examples/constructions that go against intuitive human ~quick evaluation/priors of what is promising, simply because they can be so exhaustive in their exploration. It’s the country part of a “country of geniuses in a datacenter”
• Fourth, the solution combines insights/techniques from different fields. It pulled off an answer that used algebraic number theory to solve a combinatorial geometry problem. Mathematicians seem to think how it did it may unlock more. In a world where specialization is deemed necessary structurally/institutionally, AIs have a special advantage even with "mere" cross-field interpolation [tbc, in this case there seems to be substantial extrapolation in my layman's read]. Also, the constraint here may not be human intelligence per se. Surely we don't have a current Riemann-level mathematician partly because of bottlenecks of human intelligence as things specialized, but also institutionally/organizationally we may have incentivized specialization too much besides what was intellectually needed -- and organizational innovations may actually be the bottleneck for solving some big Millennium-level math problems [e.g. focused research organizations that allow for interdisciplinary moonshoots]
• Fifth, we don't know much about how many other math problems OpenAI explored. Is this the first [prominent] one they got a solution to after running through all (relatively prominent) ~Erdős problems? I don't want to come across as moving goalposts -- again, this is really big. But what does it mean if they did an extensive evaluation of various problems and this particular one is the first one to land? My best sense right now is that they probably ran a search across various problems, had internal employees [that include very bright mathematicians] to verify what was most promising, then got Gowers/other prominent mathematicians involved to double-check. This may mean that various other problems have been solved but is currently bottleneck by expert human verification. 

Lighting has been getting ridiculously cheaper. And for the most part we seem to be not taking advantage of that positive externality: reducing crime through better lighting. This has been battle-tested as one of the effective ways for public security, see Chalfin, Hansen, Lerner & Parker (2022), an RCT in NYC public housing finding ~36% reductions in nighttime outdoor index crimes from added street lighting. Many, many major cities still haven't copied this at the right levels!

But we're also getting substantially negative externalities of bright lighting. Office buildings that never turn off their lights because why would they care. Apropos the new office building that just opened next to my housing. This may alimentate NIMBY spirits in me, God forbid. Kyba et al. (2017) document that Earth's artificially lit outdoor area grew 2.2% per year from 2012 to 2016, with the LED transition producing a rebound effect instead of getting savings. Jevons paradox and such.

Also, this has all sorts of annoyances. I think malls, pharmacies, and hospitals have all become much brighter since my childhood. I may be more sensorially overloaded than most people, but this does meaningfully affect my qualia, so much that Pigou himself would collect taxes from the pharmacies with dozens and dozens of LEDs, while Coase would advocate that I have the natural property right of not being assaulted with that much lumen while buying a Tylenol. This does affect wellbeing of more than just me (Cho et al. 2015). But lightly enough, ha, to not be a topic of discussion.

Brazil has been dealing with massive criminal wildfires for the last few weeks, and the air quality is record-breakingly bad. Besides other obvious issues (ineffective government response in going after the criminals setting fires, climate change making everything worse), hardly anyone is talking about how to deal with the immediate air quality problem. It's a bit bizarre.

People aren't widely adopting PFF2 masks and air purifiers. These remain somewhat niche topics even though pretty much everyone is suffering. To be fair, there are occasional media reports and government alerts about how to deal with the situation, but these feel too little, and one only gets them if actively looking for them.

1. It's affecting tens of millions of people (scale ✓)
2. Barely anyone is really addressing it (neglectedness ✓)
3. We have simple solutions that could help a lot (tractability ✓)

It feels like there's potential for some serious impact if one approaches this right. It may be a severe case of availability bias, but all this is making me value air quality more as an EA cause area.

Securitization is indeed coming 

"OpenAI appoints Retired U.S. Army General Paul M. Nakasone to Board of Directors"

https://openai.com/index/openai-appoints-retired-us-army-general/