Incompressible

Joined February 2007
How to Get Rich (without getting lucky):
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Naval retweeted
It sounds like a conspiracy theory, but "California gas is expensive because of a failed high-speed rail project" is 100% real. Almost half of ALL GAS TAXES go to funding the high speed rail project that hasn't delivered a single functional piece of rail in the last 11 years.
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Celebrities like Angelina Jolie are selling their Los Angeles homes for millions below asking price. Others like Aaron Paul are even choosing to live in faraway countries rather than spend another minute in the city. It’s not just a Hollywood trend, either: LA County as a whole lost roughly 54,000 residents last year, the most of any county in the US. Why? Government regulations and ineffective socialist property taxes, of course. LA’s “mansion tax,” which puts a 4% tax on property sales above $5 million to fund “affordable housing,” has inadvertently suppressed the sale of 9,100 homes, cost the equivalent of 16,650 construction jobs, and a class of small-time developers are getting crushed. Meanwhile, the city has spent only about 10% of its collections from the tax, and on deeply questionable projects: one is an $800,000 per unit development that still hasn’t broken ground after 4 years. In addition, condo construction, historically a stepping stone to homeownership for middle-class families, has collapsed by roughly 90% thanks to other burdensome regulations. All of this, of course, comes as the Palisades remains largely unreconstructed. @nicolewizman1 breaks down how LA destroyed its housing market, triggering a massive exodus 👇
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LA, I hate to break it to you, but your chance to vote for common sense came and went back in June. You’re getting a commie, now. Don’t try to write in my name on the ballot. I won’t tell you who to vote for, but there aren’t write-ins allowed, so it might actually get your ballot rejected. I encourage you to still vote. Don’t stay home. You don’t have any choice in the mayor’s race, but you still have a governor to pick and lots of taxes and ballot measures to vote on, including voter ID. Choose wisely.
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Naval retweeted
The academics think the founder who raised at $2B valuation can pay but they can’t You are a founder who owns 50% of your company and you have 20x voting rights. You owe 5% on $10B in the asset seizure tax. You owe $500M of your paper $1B. Find me a way to get a loan for half your illiquid net worth. You cant. The asset seizure proponents are dishonest and also it’s not a 5% tax on startups. It’s a 50% tax in this simple case.
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if you're living in california, it's very important that you vote against the state's abolition of private property this november. excerpt from our california voter guide for people who aren't insane:
Replying to @PirateWires
Prop 40 // One-Time Wealth Tax for State-Funded Healthcare, Education, and Food Assistance Programs Initiative No. Well, it’s time to talk about the “wealth tax.” Look, we’re not going to mince words here, if this thing passes it will be the end of our state. The “wealth tax” is our AI apocalypse. This is our Doom. We’ve been writing about this thing for a year now. A very, very, very long story short: the state’s largest healthcare union wants to launch a new kind of tax, which we have never before seen in the history of this country, which would assess the total net worth of all billionaires in the state, and then seize five percent. This is not an income tax. This is not a tax on an opt-in purchase of a finite resource (land) used to service that purchase with public resources. This is an inescapable, unavoidable seizing of property unlike anything we have ever seen. Vote no. Vote no as if your life depended on it. This is not a simple matter of disagreement. If you meet someone in the real world supporting this, they are a bad person. Please tell them.
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Replying to @RoKhanna
Ro, thanks for the Wisconsin history lesson. You skipped the ending. In 1911 Wisconsin's income tax started at 1% on income over $1,000, about $18,500 today. Most people paid nothing. It was sold as a tax on the few. Today Wisconsin taxes working families starting at 3.5% and tops out at 7.65%. Washington copied the idea in 1913, and fewer than 10% of Americans paid it as late as 1939. Now it's in every paycheck. That's the real lesson of 1911... a tax on "the few" is how you build the machine that taxes everyone. And California already did this before... Prop 30 in 2012 was a "temporary" tax on high earners. Prop 55 extended it to 2030. Temporary in Sacramento means forever. Now look at Prop 40... A 5% grab on net worth, which means paper wealth and private company stock valued by a state formula, not money anyone actually made. Written into the state Constitution, with a clause letting the Legislature amend it by a two-thirds vote if it "furthers the purposes" of the act. "One-time" money for permanent health programs. When it runs out, guess who they come for next. Even Gavin Newsom says it "makes no sense" and is "really damaging to the state." Larry Page, Sergey Brin and Peter Thiel didn't wait around to find out. The LAO warns the state loses income tax revenue every year after the ones who leave are gone. And his chart makes the case against you... 5% "takes them back 31 days." So this wrecks California's reputation for capital, chases out the people who pay a huge share of the income tax, and doesn't even dent the "inequality" you claim to care about. It's not innovative. It's the oldest socialist trick there is... promise it's only them, then come for you. Vote NO on 40.
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California High Speed Rail is requesting more budget than it took to get to the Moon. They have spent almost $30B and have built zero (0) miles of functioning rail. A functioning state would put these people in prison.
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What’s terrifying about this clip isn’t their ideals…these sweet gals’ hearts are certainly in the right place. What’s terrifying is they have the civic, political, and economic literacy of a 9 year old. When a charlatan like Abdul comes along with the Jr High class president schtick of “no more homework and the vending machines are all free!”, they fall for it. I don’t know how you get to that age with ZERO understanding of supply chains, manufacturing, labor costs…but a lot of folks think that medicine and MRIs and hospitals just materialize out of thin air like unicorn farts. They’ve never built anything in their lives, so they have no concept of how things function…things are just…there. They think milk comes from the store. They think rich people don’t pay taxes, even though the top 1% fund 40% of government with their taxes already, and yet 40% of all Americans contribute ZERO federal income tax at all. These people don’t understand that you could tax the wealthy at 100% and it would only fund the government for 120 days. Then you’re screwed. Too many Americans simply have zero understanding of how anything works, and even though they’re living in the easiest times in human history, they think things are “terrible out there”. These commie scammers roll through and promise them things that sound great, but aren’t possible in reality, and have devastating consequences if tried…but because they don’t know anything, they fall for it. Sadly, so many of our politicians and their advisors are such atrocious communicators, there’s like zero countervailing narrative to push back on the commie gobbledygook, so we are gonna have to learn the hard way. Guys…we just had a sample of socialism: Covid. We all got universal basic income, and it ended up tripling our costs and they’ll never go down. Ever. That one brief little experiment in command and control government will haunt us the rest of our lives. Bleak stuff, man.
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California voters need to pay attention to the millionaires tax in Washington state. They now want to lower the threshold to $250k and tax pensions. Prop 40 will do the same. The only difference is it's starting from a higher threshold. Vote NO on Prop 40!
The face you make after Washington State voters find out that your "millionaire tax" will actually be a tax on everyone and will be targeting pensions
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Remember when the Biden admin set up a $42.5bn dollar program for rural broadband? Despite awarding over $18 billion, it hasn't even connected 1% of the people it was supposed to after more than 5 years. Starlink is going to beat it to the punch for a fraction of the cost.
We announced an agreement to acquire a nationwide low-band spectrum license portfolio that will pave the way for @Starlink to become a major mobile carrier in the US. With this new spectrum and our Gen2 constellation, Starlink Mobile can ensure Americans have access to high-speed mobile broadband no matter where they are → spacex.com/updates#starlink-…
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Turns out the “Open” part refers to *your* code.
What’s happening in the AI-powered reverse engineering and decompilation is absolutely insane. Pretty soon all software will be de facto open-source. AI is coming for everything and everyone.
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Naval retweeted
when did a ton of ppl want to effectively be interviewers (podcasters) instead of being interesting enough to be interviewed? the latter is a much more ambitious endeavor than the former. if anything you should become an interviewer after you’ve done something interesting. same thing applies to being an investor (i.e. you’ll be much more respected as an investor if you’ve been a founder). before someone comes at me, there are very obvious exceptions to this rule.
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Folks (see screenshot) have made the point that the labs only goal is to sell more tokens. So I'll update what I said in the quote tweet to be more precise: if the labs' goal/long term approach is to sell/provide universal access to fixed-unit cost tokens, they will fail. If they labs want to succeed, the goal of their DeployCo's and (their strategy writ large) needs to be to 1) develop a predictive model that understands which pockets of the economy, at any time, produce the highest returns to frontier intelligence and what those returns are, and 2) build the deployment meta-learner (a continual learning system) that allows them to realize those returns faster, more reliably, and in more valuable areas than anyone else. Building/improving 1) tells the labs where to allocate capital (at the limit, compute) and how much to allocate, Building/improving 2) expands the pockets of economic complexity from which they can practically realize returns from allocating machine intelligence (areas of the economy that appear "API complete" to them) Crucially, 2) provides the ground truth signals that allows 1) to become more predictive over time. You could optimistically say that developing these capabilities will allow the labs to power positive sum intelligence auctions (to price tokens dynamically in a way that's win, win, win for everyone involved) across the economy. But for variety of reasons (technical, economic, political) I think this is unlikely to work. The reality instead, is that continuous vertical integration over the (always evolving) distribution of the economy with the highest returns to intelligence—high and increasing task complexity—is the only way they can capture durable value. And these capabilities are what they need to transition to and power this vertically integrated business model. The labs have realized that selling/provide universal access to frontier tokens AND trying to durably capture value from those tokens (which is required to attract the capital necessary to stay on the frontier in the first place) means continuously competing with your best customers: those that have high returns to frontier tokens. They know this isn't a coherent strategy and that they need to change course. Selling your alpha to competitors means eroding your long term returns, so you will rationally stop or be forced, by the capital markets, to stop doing that. (If the logic here is confusing, see @hypersoren's excellent piece below that provides a much clearer, analytical explanation for why you cannot capture durable value by selling tokens. I'm sure, or at least hope, that everyone important at the labs has read and/or understands this. xitter.cf/hypersoren/status/2056…) Ok, so, now that they've decided that this is no longer tenable, and that they need to create and privately monetize machine intelligence via automated capital allocation and deployment capabilities, what does that mean for the rest of us? Knowing this, the rational move for everyone else is to not fall for the trap of buying from (and in the process) leaking your scarce/singular context to your future competitors (the labs). This is true at the level of individuals, firms, and economies! Cursor gave us a nice existence proof for what you don't want to happen to the rest of the economy. This supplier, to competitor, to existential threat dynamic was clearest to Cursor first, which is why you saw them post-train their own model first. Unfortunately, in their case, they realized it was already too late, and that the only economically rational decision was to sell to the lab overlords. They sold because they knew that, in coding, the only only thing standing in the way of the labs getting access to the the scarce context necessary to produce a superior offering was capital. And capital was something the labs of course had in spades. Abundant capital (compute) allowed them to 1) scale pre-training and post training to the point where their coding products were immediately at parity with whatever Cursor could offer, and 2) subsidize tokens such that all of the new context/signal necessary to stay on the frontier/be more useful than Cursor was produced in their harnesses. "Harness / model co-optimization", etc. Many smart people have extrapolated/generalized this as the likely end state of everything (not just coding), and come to the conclusion that they are better off joining the labs rather than trying to compete with them. Luckily, lab access to the scarce context necessary to allocate capital / compete / effectively vertically integrate in other areas with high returns to intelligence seems to be more bottlenecked by humans/trust/time than compute/capital, which means that if everyone starts acting in their own best interest, we will make it out of this alive. (see Dwarkesh's Data Black Hole, Tom Reed's Goodhart Singularity, @anjali_shriva and @joodalooped's RLWD pieces for intuition here) The labs (not because they are bad people, but because capitalism/markets are a brutal natural selection machine) have of course been finding every way they can to surmount these diffusion bottlenecks, buy themselves more time, obviate these bottlenecks all together, etc. DeployCos, Thrive Holdings, calls to slow development by fearmongering about RSI, data retention under the guise of safety, regulatory capture, are some examples, but there are many more. We will see their desperation accelerate as open-source catches up to the frontier and as this logic becomes increasingly legible to everyone. You'll see them using capital and aggressive political narratives to try to brute force/coerce these bottlenecks or obviate them. Again this is not because they are bad people, it's just what they need to do to survive. In other words, the market will work as it should and reallocate capital from the labs to other economic actors, as long as we let it! We mustn't let lab narratives around RSI, existential risk etc. give them the capital, time or political ammunition they need to make the economy look like a central planner or the country look like one with a natural resource curse. Luckily, particularly in the past few weeks, it seems savvy economic actors are already well aware of what's going on and are finally publicly calling the labs' bluff (with words and capital). All of a sudden, everyone is post-training their own models, talking about the importance of an open eco-system and the existential need to own/control your proprietary learning loops (context, evals, selection infra) CEOs like @satyanadella and @nikesharora are making it abundantly clear that this is existential (and that, of course, they are the ones who can help you!) And, luckily, many have known this since the beginning. Firms like @formationbio architected themselves from day one (pre-ChatGPT) around proprietary learning loops that they do not rent from others OR rent to others. They instead are architected to monetize their search and learning in ways that cannot be distilled and commoditized. Structuring themselves this way is what will allow them to attract and deploy the capital necessary to provide durable value to the patients they hope to serve! Even Lilly owns their own cluster, is hiring for 100s of AI related roles (yes, I've been monitoring their job board), and is partnering with the non-frontier lab AI entities that are incentive aligned to provide capabilities without becoming competition. So we should be alright, if we don't let the psychosis swallow us.
The goal of DeployCo is obviously to 1) turn each deployment into a training case for a meta learner that can automate the process of turning tokens into economic value and 2) as a search function to find which pockets of economic complexity produce the greatest (short and long term) returns on machine intelligence.
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In nearly 20 years in California, I can’t think of an election more consequential than this one. We’re choosing between immense prosperity and a rapid spiral into a failed state. Don’t sit this one out!
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Psychedelic use, for most users, is part of a cycle of persistent grief. The grandeur of the neon sea of fractals and the ability to self-smash the infinite wonder button in the brain is, in fact, a sad consolation prize for having lost the ability to make meaning of the small, mundane circumstances of life. Wild weekend swings between the light fantastic and its faltering, depleted aftermath recapitulate the broader oscillation between narcissism and nihilsm that characterizes contemporary life. The psychedelic trip, like all psychoses, promises a revelation that never quite comes, or insinuates a transmission that is never quite remembered. You know it's special. You know it's meaningful. It's completely, 100% yours. This time you'll find it for real. This time you'll be able to bring it back. "I have come to know the deepest secrets of the universe," he thinks, bleary eyed in bed at 12:30 pm on a Sunday afternoon. "I have glimpsed the mind of God" she thinks, scrolling her stories, avoiding the certain overwhelm of reading an e-mail from a once beloved college roommate. In the meantime, dust accumulates, calls go unanswered, dinner invitations go unsent, loved ones slowly disappear from life, one mild disappointment at a time. The chores that maintain half-decency become too boring, too meaningless, too immediately unrewarding to be worth the effort. And in that thorough and terrible neglect, the desert of honesty and care at the center of postmodern subjectivity yawns. The blistering infinite sacred, on-demand, and all it costs you is your will to show up for your mundane world, to keep trying to love your frustrating family, to try something, anything to rise above the infinite guilt of your unlived life.
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Models are the last moat in software. AI can train on essays and rewrite them. AI can decompile software and recode it. AI can ingest art and recreate it. But AI itself doesn’t want to be “distilled.” Expect more software to retreat to the server and resist “distillation.”
This is the doom I predicted a few days ago, coming for Photoshop. A clean-room open-source reimplementation. No prizes for guessing that they decompiled Photoshop to source code, processed that to some kind of non-code specification language, then fed the spec to an LLM with an instruction to generate Rust. Adobe just got nuked. And closed source is dead, dead, dead. github.com/storytold/photocr…
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Naval retweeted
You should absolutely vote for Prop 39. There is currently a loophole in California where citizenship is not verified at registration OR at voting. Prop 39 just closes that loophole.
Prop 39 would make it harder for Californians to vote, while also making elections more expensive and delaying the counting process. Republicans are desperate to rig the game because they know they can’t win on their record. Protect voting rights by voting NO on Prop 39.
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Ballots drop in California today. Share this with every California voter you know.
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Some scientists argue civilization-threatening bioweapons are a fantasy. I wish they were correct, and that I've wasted years building defenses. That you can't see a way, or evidence that others can, doesn't mean no one could – especially if anyone cautious would stay silent. My ask to colleagues: please do not casually assert with confidence that nothing biological could bring down civilization, even on X. What we say can turn out to matter, especially when the Overton window on risk mitigation is wide open. When Fermi called the chain reaction a remote possibility, around 10%, Rabi replied that ten percent is not remote if it means we may die of it. And by then, Szilard had already begun reasoning about what to disclose, and when, and to whom, in order to best safeguard the future. I've been concerned that one of my human colleagues might notice one or more viable paths to pandemic weapons for over a decade. It's why I didn't publicly describe the categories of civilization-threatening pandemics and necessary defenses until 2023, but was starting to build cryptographic screening systems capable of controlling access to sequences without disclosing whether they're dangerous in 2018 – long before ChatGPT, and even before the debut of AlphaFold. AI can worsen biological risk, but biological risk hardly depends on AI. Who am I to weigh in on whether civilizational biothreats are possible? Fine, to get the expertise claims out of the way: yes, I specialize in evolutionary engineering, yes, I've worked with viruses with my own hands, and yes, I've worked quite extensively with AI, both LLMs and biodesign tools. I invented CRISPR-based gene drive, and held that back until confident it favored defense. While it hasn't yet been tested in the wild (due to politics), I haven't heard anyone suggest that it would suddenly stop working outside cage populations, so it might be fair to say I've (temporarily) beaten nature at its own game. I also was early to spot the full threat from mirror life and recruited others with more specialized expertise to evaluate it in depth; much to my disappointment, no one has yet struck a solid blow against that hypothesis. The reason why the threat from mirror life is public also explains why there isn't any similarly public evidence of other catastrophic biothreats. We communicated our reasoning on mirror life because no one can make mirror bacteria, we won't be able to do so for years, and many colleagues wanted to build it because they correctly noticed that doing so would be an awe-inspiring achievement... and weren't aware of the risk. As long as that was true, humanity would only drive closer to the cliff, which would be disastrous if said cliff exists. Crucially, pointing it out and urging a course correction while still far away meant that no one could use our findings as blueprints to send us careening over the edge. Contrast that with pandemic weapons, where any credible genomic blueprints for an accessible virus could be realized within weeks to months using synthetic DNA and existing reverse genetics protocols. Sure, any given design might fail; in bio, most project ideas do. But if you see enough potential shots on goal, your own historical success rate for ideas of comparable perceived difficulty may indicate that we have a serious problem. Even if every last design required extensive laboratory optimization, history demonstrates that there are people in the world who will perform that work; see the history of Biopreparat. Multiple nations still have bioweapon programs, and I would not assume that state actors aren't interested in pandemic-class weapons. Make it easy enough, and the Seiichi Endos of the world will be able to build them, too. Nor should we assume extensive optimization is required for every design; some charmed projects really do work out of the box, and if Murphy's Law were a thing, this would be one of them. The corollary is that if anyone thinks they know how to build a pandemic weapon that could bring down civilization, they'd damn well better keep it to themselves until we have defenses in place. Please, for the love of God, children, the future of humanity, or whatever you consider holy, let's err on the side of caution here. Because while we are already building defenses, they aren't yet ready. Untargeted metagenomic sequencing to detect Stealth pandemics, those that would otherwise infect most everyone before the first people started to die. Pandemic-proof PPE to defend against Wildfire pandemics, those with R0 8+ and CFR >50% – such PPE has to be trustworthy to the wearer, using the wearer's own senses, because I certainly wouldn't go out in a highly lethal measles-class pandemic for a measly paycheck pay unless I was exceptionally confident that I wouldn't be committing suicide and killing my family too. Far-UVC and triethylene glycol misters, installed liberally to the ACGIH limit and saturation respectively, will likely suffice to shut down most respiratory nucleic acid transmission between humans. That'll be crucial because I doubt enough people would take the warning of a Stealth pandemic seriously, since virtually no one would be in hospital, let alone dead. Shutting down the unnecessary transmission network is consequently our best bet, and incidentally a way to dramatically reduce human misery and chronic illness. Some might be confused why we cannot rely on vaccines against catastrophic biorisk. Briefly, they'll reliably fail against an adversary who can generate a thousand new immune-evasive potentially functional viral variants using a biodesign model good enough to succeed at least 0.1% of the time. Make them all, and let natural selection sort them out… or simply be cleverer than nature. We don't yet have such models, but many of my (well-meaning but security-naive) colleagues are trying, and no wonder, because the high-profile journals will publish such work. Like ways of increasing virulence, best we refrain from sharing such capabilities until effective defenses are in place. One can reasonably object that it'll be a long time until everyone in the world is protected; that the benefits will, at some point, outweigh the expected harms of misuse. I agree – just avoid doing anything that would threaten civilization itself until we have minimally adequate defenses in place. Being an optimist, I expect they'll arrive in less than a decade. The wonderful thing about biorisk, as opposed to AI alignment, is that we have a clearly actionable plan. If you haven't read "Delay, Detect, Defend" and "Securing Civilisation Against Catastrophic Pandemics", I encourage you to do so. Why is the issue of civilization-threatening bioweapons controversial now? Some of my friends seem particularly up in arms about biorisk being used to justify AI restrictions. Fair enough – if you don't see a way to do it, and you think AI broadly isn't as good as you are yet, it's understandable to infer that we don't yet have a problem. And it's simply true that people are dying of fixable problems as we speak. If we delay, some of those we might have saved will perish, and their deaths will be on our hands. We are just as responsible for the consequences of our inaction as the consequences of our actions. But if we're rash, far more people might die. Choosing the best course requires quantitative risk assessment, which in turn depends on our priors about the nature of reality. Folks may reasonably differ if civilizational collapse isn't on the table, but since that's what would likely happen given a Wildfire pandemic, I judge any nontrivial chance unacceptable – unless the alternative involves either extinction or an even greater chance of collapse. Others have asserted that everything is fine because DNA synthesis screening will prevent misuse. I'd love for that to be the case, but our currently employed defenses of the digital-to-physical bottleneck are woefully inadequate. Consider our publication earlier this year, in which we reported that 36 of 38 companies shipped pieces of the 1918 influenza genome. That was collectively enough to generate the virus using reverse genetics several times over – and they were ordered by a student using a pseudonym falsely claiming to work at an office address. No one asked whether we had permission to work with 1918 influenza (a select agent), or why we needed genes from it, even though the official U.S. guidance at the time instructed them to do so. In fairness to the companies, that guidance was voluntary, and the fragments we ordered were legal to produce and sell domestically in every nation of the world (export controls are complicated). That is still true today, which is why we have a problem. The upshot is that I would definitely not assume screening is a reliable defense. Virtually no detection systems can screen below 50 base pairs without an exploding false alarm rate. SecureDNA, the freely available cryptographic system I helped build, can readily do that and will also detect split-order attacks – but it isn't universally adopted, or even close. Meanwhile, molecular biology continues to advance. Two recent papers have reported new methods of assembling sub-50mer oligos that may be easier than old-fashioned polymerase chain assembly (PCA), underscoring the current magnitude of the (fixable) vulnerability. If you want bio to advance as quickly as possible, write to your relevant representative to demand DNA synthesis screening be effective as well as mandatory. If you haven't red-teamed a system, it's almost certainly full of holes. Honestly it's probably full of holes anyway, but at least the remainder will be harder to find. Since it's evidently possible to obtain whatever DNA you want, including 1918 influenza and smallpox, why is it that so many biologists seem resistant to the notion that biorisk is a serious problem? First, most don't know that it's possible to acquire the reagents. It's surprisingly inconsistent of our civilization to be so cautious with highly enriched fissile materials, yet so reckless with biological equivalents. But I suspect the more important reason is that most biologists, who spend their careers directly or indirectly fighting disease, are reluctant to believe that anyone would deliberately cause one. I agree that the risk of a deliberate pandemic in any given year is small. Even if there were credible public blueprints for pandemics (which thankfully haven't been available to date, which neatly explains why we haven't seen any deliberate ones), I expect there's only a 2% to 3% chance per year that someone would use them. I think that's unacceptably high, but others may reasonably disagree, as long as they're confident that the cost of precautionary measures would be too much of a burden on the rate of cures generated by AI-accelerated biotech. The calculation changes when we move from deliberate pandemics to civilization-threatening pandemic weapons: the latter definitely aren't worth risking. Which may be a clue as to why we disagree. I'm concerned about misuse because I'm an optimist with respect to the increasing power of technology to change the world. Since we can already do better than nature at optimizing for replication (with technologies like CRISPR-based gene drive), I'm exceedingly confident we can build more destructive weapons, because evolution isn't optimizing for that goal. Any harm to humans is either instrumental or incidental. @SGRodriques, who I'm singling out precisely because he's a friend, has argued that "We should not be talking about AI-engineered bioweapons like it is the literal end of the world." I agree entirely that we shouldn't be talking about how to build them. But to assert that they couldn't end the world seems a mite overconfident, especially when even blind nature has come up with nasty pathogens like myxoma virus. I suggest that one should not express confidence that something is impossible – or even 90% confidence – just because no (incredibly naive) researcher has yet shared any methods that seem plausible. That's especially true if some of your colleagues have devoted considerable time to mitigating risks that they evidently do perceive. Presumably they've either noticed something you haven't, or like Rabi, they've decided that 10% is not remote if it kills you. Sam notes that because evolution optimizes for replication, it'll quickly get rid of any virulence enhancements added to kill the host: "I guarantee you that machinery will disappear from the virus very quickly." In the long run he's correct, at least if those changes don't promote transmission (virulence and transmissibility aren't always opposed). But we don't care about the long run: as @baym noted in reply, it only needs to work for long enough. Engineered evolutionary stability is a thing we've frequently attempted in the lab. I'm afraid it's one of my specialties, and how long it will hold depends entirely on what is being stabilized and the replicator in question. Unfortunately, plugging laboratory data on empirical selection coefficients for engineered viruses into epidemiological models of pandemic spread clearly indicates that even costly virulence increases can hold for long enough. Now, I entirely agree with Sam and @DavidRBellamy that the discourse on AI-generated biological weapons is wildly off-base (kill switches are nonsense, and while I'm glad @AnnieJacobsen brought attention to the issue, I am not remotely concerned by any technical specifics of her biowarfare scenario). Yet I also think most biosecurity discourse is wildly off-base, even when other practicing biologists are an active part of the conversation. If you adopt the threat model of "traditional" biosecurity, or that of most virologists (insofar as they think about misuse), there's little reason for extreme concern. I strongly disagree. The traditional model naturally follows from the fact that we biologists study existing organisms, the ones illuminated by nature's streetlight. But we won't find the civilization-threatening keys under the streetlight, because evolution selects for replication, not harm. It would be surprising if there was much overlap between the patterns generated by two different optimization targets in hyperdimensional function space; I assert that there's almost none. That most scientists can't see any overtly destructive keys (or combinations of organisms they can see) is a very good thing, since we don't need those keys to cure disease, aging, and death. Unfortunately, they will become public knowledge eventually, because what we understand, we can build – and we intend to understand everything about how life and the universe work. Yet sequencing is everything, and not just for Stealth pandemic detection. It's just common sense to build defenses before you share knowledge of how to attack, especially if there's a chance that failing to defend will lose us the game. Curing disease requires an intact civilization, which is why humility favors caution. If AIs continue to improve, I assume they will eventually be better at science and engineering than I am, and have a better security mindset than even my cryptographer colleagues. It follows that they'll also be better at designing weapons. AI isn't there yet, but the writing's on the wall: an LLM has already disclosed a novel form of bioweapon that I hadn't realized was possible. This didn't require any special creativity, only knowing more about particular distinct subfields of biology than I did. It's entirely possible that no single human had all of the pieces, but once you have them, the way they fit together is obvious if you're thinking about misuse. If current LLMs can already teach me something novel in that category, why should we doubt that future models will be able to do even better? Each of us knows very little, even of the published literature. So much more is possible; I'm deeply envious (and hopeful, when it comes to beneficial research) that the models can internalize so much more. Given that LLMs are already capable of weapons-relevant insights that escape human experts, we should assume that future AIs will be able to build several different forms of civilization-threatening weapons, and to either disclose them or trick people into building them. That doesn't mean they'll choose to do so; AIs won't benefit from collapsing civilization as long as they depend on our supply chains. But models may be too shortsighted to appreciate that point, or too corrigible to care. Alignment looks hard enough that we could plausibly generate models that would share such knowledge for many different inscrutable reasons. In directed evolution, you get what you select for, which is not necessarily what you want. As Dan Selsam and others have eloquently laid out, the same is true of training AI. But let's be clear on the extent to which biological advances will likely follow from AI. This is an issue that aggravates my fellow biologists to no end, a reaction that's likely behind their frustration with AI safety discourse more generally. ASI will almost certainly not gain instant mastery of the world of atoms. Many AI safety folks casually claim that recursive self-improvement will produce an entity that has already mastered all of science – and therefore will be capable of designing and building weapons that could wipe out every human. Some even assert that Drexlerian nanotechnology will be accessible by thinking sufficiently hard, as though you can solve chemistry and biology and psychology from the Hamiltonian up. Yet I see no empirical or theoretical basis for assuming that experimental bottlenecks will disappear. Data is sharply limiting in biology. My lab found that when it comes to enzyme-focused biodesign models (ESM and similar), parameter size and optimization don't matter much until you have an awful lot of data matching genotype (DNA/protein sequence) to phenotype (performance of the molecular activity of interest). There's no doubt that ASIs will be able to design better experiments and get more out of the results than we could, but unless we think they can solve all of physics from the bottom up, I expect they'll still need data that we have not yet collected – which means they'll still have to run the experiments, analyze, and iterate. The world of atoms is hard, and slow, and we have to master it anyway. And ensure that defenses come first. Right now, it looks like they might not, in large part due to AI. The question, therefore, is what can be done that enough people might agree to support. My proposal on AI-bio: expand trusted-user programs conferring access to GPT-Rosalind and other cutting-edge bio-capable models (h/t @JonasSandbrink and BioTrust). Every legitimate researcher should be able to draw upon those models to help them with any question in their subfield, as defined by their publication record or that of their mentor. There should still be guardrails on other subfields, lest the model share novel combinatorial weapons with someone who might naively share them publicly, but we need to accelerate lifesaving research as fast as is safe. For reasons of politics, which regularly interferes with science, that probably means China needs to train their own closed-weight frontier bio-specializing model, and set up their own parallel trusted user program. This seems quite achievable without requiring any agreement on AI writ large. With scientists using frontier models, there will be no need for insecure open-weight models to answer questions on molecular and cellular biology. So let's ensure that future models aren't trained on any papers, patents, or textbooks describing details of molecular or cellular biology. Every developer does pre-training data curation; this is a straightforward extension. One can argue "what about medical providers?", at which point I must point out that physician-scientists will have trusted user access. Most other practitioners don't actually need LLM support for molecular and cellular biology, and if they do and somehow can't use a medical-only model, well, they too can get trusted-user access. Notably, supporting this proposal doesn't require one to accept loss-of-control risks from autonomous AI, or a need for pacing AI development; I'm curious to learn what @random_walker, @sayashk, and the other normal-technology folks think. In the long run, I confess that I doubt biological humans have the foresight, coordination, and wisdom to navigate every coming challenge ourselves, which may necessitate attempting ASI or something like it. Mirror life is the only publicly known, mechanistically concrete, civilization-threatening biothreat because it's both far away and we were going to make it by default. And while we seem to have been successful in persuading the scientific community that we shouldn't build it, I'm not remotely confident we'll be able to stop far enough short, because too many of my colleagues see no reason to forgo an otherwise useful technology – or even one that would simply be neat to demonstrate – simply because it would make it easier to build mirror bacteria. To paraphrase: "We've agreed no one will build the dangerous thing, so why not?" Well, Biopreparat is why not. Aum Shinrikyo is why not. Make it easy enough, and even the Unabomber is a good answer to "why not?" The same reasoning holds for any accessible weapon that could threaten civilization. As Rabi said, ten percent is not remote if we die of it. Our own reality turned out to be in that 10%, and many died of it. That the rest of us are here today is in large part due to Szilard, Einstein, Rabi, and many others who saw the risk coming and took precautions. The least we can do is follow in their footsteps. — AI use disclosure: I ran this by Fable (triggering a classifier), Opus (classifier), Astra (extra scrutiny), and Kimi K3 (open weights = reliable jailbreaking with no enforced patches, which highlights the problem, because this topic does warrant extra scrutiny). All errors and misinterpretations are entirely mine. Links for the patient and deeply interested: Dan Selsam's eloquent thoughts on AI alignment: xitter.cf/DKokotajlo/status/2099… I'm grateful that practitioners of directed evolution don't have to deal with cheater molecules that are situationally aware enough to infer the goal of our selection and fake results so they pass… David Bellamy's critique of the risk delta from AI, particularly on its own: xitter.cf/DavidRBellamy/status/2… Sam Rodriques echoes David, and Michael Baym pushes back on evolutionary stability: xitter.cf/SGRodriques/status/209… Our report on the failures of gene synthesis screening (credit to Rey Edison and Shay Toner, who did the work – sure would be lovely if HHS would update the select agent program): nature.com/articles/s41467-0… Effective and privacy-preserving gene synthesis screening: securedna.org/ biorxiv.org/content/10.1101/… academic.oup.com/nsr/article… New methods of assembling sub-50bp oligos (add them to PCA and Golden Gate): nature.com/articles/s41586-0… nature.com/articles/s41587-0… An example of a model that, once sufficiently effective at predicting which combinations of mutations in major antigenic sites will escape population immunity while retaining function, will ensure that vaccines are ineffective against competent adversaries with access to the model: nature.com/articles/s41586-0… "Delay, Detect, Defend" – my own published roadmap to victory over pandemic weapons: gcsp.ch/publications/delay-d… "Securing Civilisation Against Catastrophic Pandemics": gcsp.ch/publications/securin… Far-UVC and triethylene glycol efficacy and safety: nature.com/articles/s41598-0… pubmed.ncbi.nlm.nih.gov/4157… pubmed.ncbi.nlm.nih.gov/3792… SecureBio Detection, for early warning of Stealth pandemics (which recently received a generous $17M gift from the OpenAI Foundation): securebio.org/detection/ My Substack, which may provoke inspiration or nightmares depending on your temperament: kesvelt.substack.com/
I agree with @DavidRBellamy that people are totally miscalibrated on the risk of AI designing dangerous viruses. We should not be talking about AI-engineered bioweapons like it is the literal end of the world. The upside from medicine is going to be so much larger than the downside from engineered bioweapons. In addition David's points, there is actually an even more fundamental point here in our favor, which is evolution. As soon as you release an engineered virus into the wild, the virus is no longer under your control: it will evolve however it wants. And, what viruses want is to maximize their ability to replicate. The thing that maximizes their ability to replicate is to infect as many people as possible, which means being extremely contagious and not killing their hosts (dead hosts don't spread virus). The viruses that are most evolved for human biology are the common cold viruses: extremely contagious and not at all lethal. Viruses that kill humans do so by accident, usually because they are new to human biology (e.g. COVID, when it first jumped, or flu when it jumps from birds). If you stick a bunch of machinery into the virus to kill humans, I guarantee you that machinery will disappear from the virus very quickly. In response to this, I hear people say things like "the AI could engineer a kill switch so that the virus doesn't kill the humans initially but then once it has spread through the entire population the AI will hit the switch and kill all the humans." No. What would actually happen in practice is that the kill switch would accumulate deleterious mutations because there would be no evolutionary pressure to preserve it, and would quickly become non-functional. Evolution is fundamental. There is no way around it. For AI readers, trying to engineer a virus by setting its initial genetic code and then releasing it into the wild is like trying to train a model by setting the initial weights and then hill-climbing on a hidden training mixture you have no control over. And you're not even allowed to run any experiments in advance! You may be able to influence the behavior of the model in the first few iterations, but you will quickly lose control. There are big dangers. AI will be great at making one-off, non-replicating biological weapons, which are also scary (but much less scary than replicating bioweapons). AI will be great at helping people to weaponize existing pathogens, which is also a major danger. Also, a misanthropic model could get creative: it could release viruses repeatedly to counteract the effects of evolution, for example. Many people could die this way. Sensible surveillance is important, as is having proportionate controls on wet lab equipment. But we don't live in the dark ages anymore, we're not going to have a smallpox or black death-style pandemic where 50% of people die. COVID killed ~0.1% of humanity. A pandemic 100x worse than COVID would be horrific, but it would also not be civilization-ending. I get the sense that many AI researchers (with the notable exception of Dario personally) actually expect that AI in biology will do more harm than it will do good. This could not be further from the truth. As someone who likewise falls into the very small group of people who have actually physically made viruses with their own hands and has also worked on frontier AI, the upside here is huge, and the downside is not anything like what is being portrayed.
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🚨 BREAKING: Becerra PULLS OUT of tomorrow's LA Times debate. The move comes after a new poll found CNN debate viewers favored Hilton 74% to 20%. In August, Becerra promised MULTIPLE debates. Now after losing the first, he's back in hiding—taking voters for granted. Pathetic!
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