I write stuff sometimes
Joined January 2023
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Generally speaking, voters want data center moratoriums in the same sense that they want tariffs.
Did voters ask for tariffs? Yes. Did they want them in practice? Absolutely no.
Voters wanted prices to go down & for communities that were hollowed out to be revitalized.
Do voters want data center moratoriums? Yes. But do they want the results of a data center moratorium? Almost certainly not.
Data centers are enormous mechanisms of wealth redistribution. They are huge projects built in otherwise abandoned communities and they funnel money directly into the hands of the people who need it the most.
A single project can double the total tax revenue of the local area, meaning if you want, you can completely cut tax revenues of the area.
If you ask a voter why they dislike data centers, they may say "water" or "noise", but tell them that the water usage is a myth & they can be made without noise, and they'll change their position to something else.
Voters don't care at all about data centers. They care about AI. They're being told that AI might go rogue & that the AI might take their jobs.
The correct response from Democrats should be to hear their constituents and then to work to address the underlying concerns.
But the in-practice reality of banning data centers in the US means that the things voters actually care about like regulating AI & ensuring we redistribute the wealth created by it, become significantly harder.
The in-practice effect is that AI labs build data centers overseas, where it's harder to regulate them, harder to tax them, and nobody except the AI labs sees the economic value from them.
I believe Democrats have talked themselves into believing this works, just as Republicans talked themselves into tariffs, because they believe things that are inaccurate.
A common concern I hear is "AI is a bubble". The belief is that there is simply no ROI to these data center projects.
Democrats need to have a come to jesus moment here. First, you either get to believe that AI is going to go rogue or you get to believe it's useless and a bubble. It's not both.
It just is the case that AI is useful & has ROI. Anthropic has 80% margins. The AI solved millennium prize problems. If you do not believe this, and you are a congressional staffer, please DM me, I am happy to organize a visit to companies in San Francisco. We'll give you a ride in a self driving car and you can see how the AI is used all over the place in science & engineering.
It is also the case that there are meaningful risks and harms in AI. Democrats should understand that the AI industry is a meaningful partner. It is not asking saying "AI is dangerous" as a marketing ploy. Seriously. That does not make sense and you know it.
We must rebuild trust between DC & SF. Democrats should reignite the bond between liberalism and it's science & technology industries. Science & technology is not your enemy; it is the driving force of antipoverty, better healthcare, and for American progress.
Democrats & Republicans alike must stop filling their information spheres with voices that constantly make false predictions. Democrats, please understand that Ed Zitron & Timnit are considered the anti-vaxers of AI. Republicans, please understand that the VCs claiming to be experts in AI have consistently been wrong over and over. They'd be a lot richer if they were right.
It just is the case that Sama and Dario are not trying to end the world. These are people who you can work with. You almost could not ask for better organizations to be steering this technology. Are they perfect? Absolutely not. But they are fundamentally aligned with humanity & with America.
Democrats must learn the actual, factual realities of data center projects. There are definitely harms to be mitigated & we should mitigate them.
But there are equally tremendous benefits we must ensure land in the hands of the people. It must be the case that we tax these things and land the cash into a wide variety of pockets.
The average voter is not asking Democrats to swoop in & to construct a scenario in which people in SF and Malaysia get rich, but the rest of the country gets hollowed out. They are not asking for a scenario in which AI migrates outside of the regulatory domain of the United States & agents run loose causing chaos.
In order for Democrats to consistently win elections, they must be competent in helping the American people. The execution matters. The good must be done, not just said or prophesied.
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There are experts in open source trying to break cryptography with frontier models and their specific knowledge.
You just don't hear about this over the daily panicons.
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not only am i not worried about the crypto community's ability to handle the upcoming ai/quantum threat, i will venture to say that in the next 2 yrs the world will realize crypto is far better prepared for it than the rest of the internet and finance. we've had a trillion dollar *irreversible* honey pot for a decade, producing a far more battletested system and adversarial security culture than pretty much anywhere else on earth.
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Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.
- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.
The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.
So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code.
But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along.
So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions.
TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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Bitcoin's proof of work has done around 2^96 hashes over all time. Breaking the ZKP's in Zcash requires a minimum of 2^120 elliptic curve operations assuming ECDLP. If you had a dedicated ASIC, an elliptic curve addition would cost around 10-100x more than SHA2.
So today breaking an Elliptic curve would cost around 1 billion Bitcoin-hashrate equivalents. AKA a billion times the hardware buildout of all Bitcoin mining ASICs, dedicated to break this.
If a hypothetical billion X improvement came in, you'd need a chip buildout on the level of bitcoin mining before you can break anything. While competing against all the hyperscalars for fab-space.
AKA plenty of warning time, for a recovery process that takes a couple day response time max.
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The ability to resist panic and think in dimensions rather than memes seems increasingly important in the age of AI
People read one emotional Matt Green tweet about public key encryption, spent 0 seconds thinking about it, and decide to panic.
Sure ECDLP will be broken with QC's one day. But there's so many levels to this being wrong to panic over.
- 0 actual progress on attacking anything
- We have tons of alternate plans available.
- Quadratic advantage hash-based PKE
- Lattices
- Multivariate polynomials
- A whole field of KEM's from fine grained cryptanalysis. (Fun fact, works even if P=NP)
Sure you can wake-up and choose doomer and be wrong.
We have decades of cryptography to draw from on for all the above options, AND how to build a lot of what we want from UX tweaks without PKE. PKE just made a lot much easier, and less web of trust routing like.
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Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR.
We don’t yet understand what this system does, but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA. Historically, the discovery of such programmable systems has helped revolutionize medicine. CRISPR, for instance, is now the foundation of genetic medicines. But it will take much more work to learn what this system does, and whether it can be put to similar use.
Read more: anthropic.com/news/claude-di…
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zcash is simultaneously
- the most important unfinished project in crypto (in the eyes of many ogs at least)
- the last opportunity with an infinite tam (non-sovereign store of value)
- the most compelling price action setup (breakout after decade-long distribution)
confluence like this only comes once every few years
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when i talk about dynastic things, i think of generational time periods
you can 躺平/quiet quit, check yourself out of society and genuinely enjoy the rest of life
but at the expense of handicapping your next gen, instead of giving them unfair advantages to destroy their peers
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People forget Bitcoin ran from $800 to $20k in 2017.
This was during the dumpster fire of block wars, ETFs getting denied, shady exchanges, forever FUD on Tether.
Crypto liquidity was tiny then, not the trillion dollar oceans you see today.
Communism was not on the raise, Gov debt was not imploding globally, AIs had not constructed a panopticon.
Encrypted Bitcoin the last 1000x
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The Tesla that Jessica just bought cost $48k and has a range of about 350 miles. The one she bought in 2015 cost $135k, adjusted for inflation, and had a range of 270 miles. People who think they dislike capitalism don't know how good they have it.
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The mechanisms seem straightforward to me (and doesn’t require any speculation, just mild extrapolation.)
We’ve been getting almost daily AI breakthroughs in medicine. At its simplest I interpret the cause as “directed brute force.” If we can simulate enough protein folding and enzyme interactions we find helpful new ones that let us treat the body like a machine, intervening more and more as we gradually gain deep understanding.
Cancer treatments and cures are popping up all over the place.
“Cure all disease” and “cure death” are very strong statements. I don’t think anyone is arguing that AI will save your life if you jump into the sun. But if we look at mortality causes, AI is on its way towards eliminating ~90% of them pretty quickly (heart disease and automobile fatalities as examples.) We’re close to growing most organs in vats, have promising treatments for dementia/alzheimers/parkinsons. The only major cause of death that I’m aware of that remains mysterious is telomere shortening, but we know of many animals that have “solved” this, won’t take that long to understand how and apply it to humans.
Will AI in practice cure disease and death for all people? Of course not for political/social reasons. Same way people starve next to full supermarkets or die of drug abuse.
We’ve already gotten unbelievable medical breakthroughs in the last decade, but for political/bureaucratic reasons, your GP likely doesn’t know about many of them (like custom gene therapy for cancer), and there’s no distribution for a lot of this stuff.
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the future is going to be amazing
don’t let the doomers psyop you into thinking otherwise
MODERNA, MERCK MRNA CANCER VACCINE SUCCEEDS IN PHASE 3
$MRNA and $MRK say their personalized mRNA cancer vaccine, intismeran, combined with Keytruda slowed melanoma recurrence and spread in a late-stage trial.
The study was stopped at its first interim analysis after positive results, though detailed efficacy data have not yet been released.
If the benefit holds up, this would mark the first randomized Phase 3 validation of a personalized neoantigen cancer vaccine and could significantly broaden the use of mRNA technology beyond traditional vaccines.
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The outlook for medical breakthroughs that we are likely to see in our lifetimes, especially with AI and quantum, have to make you so bullish on life and humans broadly. Just try not to get hit by a bus in the next 10-15 years.
An experimental cancer vaccine kept melanoma from coming back. It’s the first successful late-stage mRNA study validating decades of custom-treatment research on.wsj.com/4qy7Ule
