Bertrand Schmitt retweeted
There are banking regulations and then there are banking "regulations". We live under the latter. An unconstitutional conjoining of state and private power. And, I believe, prosecutable. Conspiracy to deny rights with no due process.
Folks. Banking regulations DO NOT require banks to kick out Politically Exposed Persons (@pmarca ). They just have to go through enhanced due diligence and monitoring.
The practical effect may indeed be to cause management to blanket disallow them, because the fines are huge.
Bertrand Schmitt retweeted
What Polymarket got Right that the Experts Got Wrong
As the dust settles on the election, thereâs a story that the WSJ and NYT didnât tell you. While the mainstream news was busy with their TV pageantry and hedging on calling key swing states, Polymarket, the worldâs biggest prediction market, had already delivered its verdict by midnight EST, declaring Trump was 97% likely to win. This was before the media called even a single swing state.
All throughout this election, Polymarket was always one step ahead. I want to explain why this is, because judging from the Twitter responses I was getting last night, most people deeply misunderstand this.
There are two fundamental things that Polymarket did better than the media.
1. Polymarket was more accurate on the forecast going into the election.
Letâs take the pollsters and analysts. Election poll-based models claimed the race was a dead-even 50/50. Polymarket meanwhile was priced Trump with a distinct edgeâgoing into the election, he was priced around 62% to win.
If you remember, the mainstream media derided Polymarket for this difference. Polymarket should be the same as the modelers, they said! Obviously it means you canât trust Polymarket. Itâs priced differently because itâs a bunch of Trump-loving crypto bros. Itâs invested by Peter Thiel. Only foreigners trade on it. It's unregulated, so it must be being manipulated. There's a whale pushing up the price of Trump. And on and on.
Implicit in this dismissal is a deep distrust of markets. As though markets cannot be trusted unless affirmatively proven otherwise. And of course, if you actually trusted the markets, you might not trust the media anymore. And their whole business model is predicated on you distrusting anyone but themâwhy else would you continue to click on their never-ending stream of clickbait?
But anyone with experience with markets knows: it doesnât fucking matter if a market is composed of Republicans, or Democrats, or foreigners, or whatever. In reality, we know that JP Morgan was using Polymarket, as were some of the largest hedge funds in the world (most have non-US subsidiaries). It was integrated into Bloomberg Terminal, it was being quoted on CNN. And yet the media spoke of Polymarket as though it was 4chan.
Understand, Polymarket traded $3.6 BILLION dollars on the presidential election. This was the largest election betting market by volume IN HISTORY and AN ORDER OF MAGNITUDE more than any other election market ever. There was more riding on this than any single modelersâ career prospects. Understandâmarkets work because of how much is riding on getting the answer right.
These supposed biasesâbeing Trump-aligned crypto-pilled non-Americansâdidnât skew the marketâs accuracy. (It seems obvious in retrospect that being non-American might improve your ability to dispassionately predict an election.)
But the identities of the bettors didn't matter. Prediction markets distill input from many diverse actors to produce prices that transcend biases. Markets don't care about ideology, they only care about being right.
And as it turns out, Polymarket was more right than any pollster or modeler.
Now, I want to be clear what Iâm not saying: the difference between 60/40 and 50/50 sounds big, but itâs not. Elections are noisy. High school statistics will tell you that if you want to tell if a coin is rigged to be 60/40 rather than 50/50, you would need over 100 coin flips to have 90% certainty. The outcome of âTrump won this electionâ does not tell you whether the coin was 60/40 or 50/50.
My point is not that Polymarket was right and the models were wrong. They actually didn't disagree with each other by much. I'm making a more subtle point: the market was consistently pricing Trumpâs odds higher than the polls. Remember, the market knows what the polls and analysts are saying. Markets incorporate all existing informationâbut Polymarket disagreed with with the pollsters. The only explanation that analysts could come up with for this was: Polymarket is biased.
They didnât have the humility to imagine, maybe, just maybe, Polymarket knew something that was not being captured by the polls.
Polling sucks. This is all well established now. In the pre-Internet era, polling was much more accurate. Landline poll response rates were often above 60%. Today, poll response rates are around 5%. This means pollsters are getting massive sampling biases, and there is no possible way to correct these biases without baking in clumsy statistical corrections. (Plus pollstersâwho are ultimately selling a product and have reputations to keep upâfrequently herd their estimates together to avoid being an outlier, which fucks up poll aggregation.)
Plus, Trump is special. He is uniquely divisive in American politics. So for three elections in a row, we have seen massive polling errors that underestimated his supportâthe so called âShy Trump Voterâ effect.
Polymarket presumably believed that the polls were missing this. The pollsters said, no: weâve updated our models and corrected for it. Polymarket said: I don't buy it. Polymarket was right.
Now, again! Polymarket did not say the election was 90% for Trump to win. 62% is not a sure thing, and elections are genuinely uncertain. But what irks me is that there was not even a tinge of curiosity from the media about the delta. Maybe Polymarket knows something we donât? Maybe thereâs information weâre missing thatâs not being captured in the polls?
Remember, Trump massively outperformed his polls all across the country, in both red states and blue ones. He sweeped every single swing state, and even won the popular voteâsomething most people thought impossible.
Are you really so confident that there was no way to detect thisâthe sentiment of tens of millions of Americansâthat didnât involve the same old pollsters running the same old Internet surveys?
This is what being a student of the markets teaches you. Markets are smart. But they donât explain themselvesâthey just show you the outcome.
That brings us to the second way that Polymarket outperformed the media.
2. Polymarket called the election in real-time, way before the media did.
The inscrutability of markets came in full force on election night. Polymarket moved quickly and violently before a single swing state was ever called. According to Polymarket, the election was over by midnight, while the mainstream media was milking the drama until the election was officially called at 6AM the next morning. Why was this?
First, Polymarket saw an important correlation that the mainstream media was not willing to explain to their viewers. You see, polling errors are seldom random; they are usually correlated across states. So when traders saw that Trump was massively outperforming his polls in states that were not themselves competitiveâpicking up huge vote share in NYC (cleanly blue) or Florida (cleanly red), this meant that there must be a massive polling miss across the country.
Polymarket immediately picked up on this and realized that the swing states could not possibly be competitive anymore. Polymarket priced Trump to win Pennsylvania at 90% by 11:30PM, when only a small portion of the Pennsylvania vote had been counted.
Prediction markets donât wait for pageantry or pundits. It doesnât care if it invalidates the sacred ritual of waiting for the votes to be counted. Remember in 2020 when Fox News called Arizona early (which turned out to be correct), viewers were outraged. Trump vowed to boycott the network over it. This reinforced the lessonâthe networks must sit there and dutifully count up the votes. Donât be too clever.
But markets donât care about drama. They only care about outcomes. Obviously, it would be incredibly difficult to explain to a CNN viewer that the election is over, the polling error in non-competitive states is too big, Kamala is doomed and you should go to sleep and not bother to wait for swing states. It goes against the narrative that the media has been reinforcing for months. The public wants simple, explainable stories, and everyone knows how the narrative is supposed to goâyou wait for the swing states and until one of the little colored bars crosses the 270 line.
At 12:51AM, the NYT was still showing this dramatic chart and headline. By then Polymarket already had Trump priced at 98% to win.
So election watchers dutifully stayed up through the night so the media could complete its empty ritual of filling up the bars.
Polymarketâs traders have no loyalty to narrative and no incentive to play up the drama for ratingsâthey just call it straight. @shayne_coplan, Polymarketâs founder, said that Trumpâs campaign team was reading Polymarket to try to understand how to actually interpret the odds. The media even had the gall to complain that Trump was declaring victory when his electoral count was at 267âat that point, the Polymarket odds were so low that they registered as 100%.
The beauty of markets is they respond instantly to new information. The fastest trader who incorporates the information gets a prizeâprofit. This is something traditional media fundamentally is not set up to do. They have to filter events through layers of interpretation, narrative making, and internal politics (recall Murdochâs intercession into the 2020 Arizona call).
The decentralized nature of Polymarket bypasses all this bullshit. It lets information flow without any interference.
There is a lot to reflect on from last night. This election was a resounding reprimand of the Democratic party, a rejection of the expert class, and an immune response against an arrogant media.
But for Polymarket, it was a night of pure vindication.
For me, the lesson is this: the next time something important is going on in the world, skip the op eds and check the Polymarket odds.
Bertrand Schmitt retweeted
Sundar Pichai said on the earnings call today that more than 25% of all new code at Google is now generated by AI.
Bertrand Schmitt retweeted
Read my new article in @palladiummag
Since the dawn of industrial civilization, men have believed that humanity is on the brink of running out of food and resources, causing mass death and the collapse of society. For centuries, they have been wrong. 1/
palladiummag.com/2024/08/16/âŠ
Bertrand Schmitt retweeted
Critically important post from @AbigailShrier on Californiaâs âsafety actâ (see what they did with the framing). If youâre a parent I recommend getting educated on this topic:
ïżŒ
Child predators follow a common playbook: target the victim, gain their trust, fill a need, and, crucially, isolate the child from her parents. For several years, this has also been standard California state protocol with regard to schoolchildren questioning their gender identities. On Monday, this scheme became law.
The âSAFETY Act,â AB 1955, signed by California Democratic governor Gavin Newsom, legally forbids schools from adopting any policy that would force them to disclose âany information related to a pupilâs sexual orientation, gender identity, or gender expression to any other person without the pupilâs consent.â Schools may not, as a matter of policy, inform parents of a childâs new gender identity unless the child volunteers her approval. The law also prohibits schools from punishing any school employee found to have âsupported a pupilâ hurtling down a path toward risky and irreversible hormones and surgeries.
The law effectively shuts down the local parentsâ rights movement in California by eliminating its most important tool: the ability to organize at the community level to stop schools from deceiving them. No longer can families hope to convince their school boards to require schools to notify parents that their daughter, Sophie, has been going by âSebastianâ in class; that her teacher, school counselor, and principal have all been celebrating Sebastianâs transgender identity; that theyâve been letting her use the boysâ bathroom and reifying the sense that she is âreally a boy.â
Californiaâs New Law Lets Schools Keep Secrets from Parents.
Critically important piece by @AbigailShrier in @thefp:
thefp.com/p/abigail-shrier-câŠ
Bertrand Schmitt retweeted
How much nuclear waste has the US ever created?
You may have heard it would fit on a football field...
But stacked how high? And stored how?
@whatisnuclear wrote a great post on this... đ§”(1/8)
Bertrand Schmitt retweeted
In the popular imagination of the tech community, fusion energy is a kind of magical free lunch that will solve all our problems. In reality, developing commercially viable fusion today would change next to nothing to the economics of energy production within the next 100 years.
We already have the technology for near-unlimited, clean energy -- it's nuclear fission. It works today. In fact it was already working in the 1970s. And those plants are cheaper to build and operate than hypothetical fusion ones. If you want to decarbonize your economy, this is your ticket.
Note that it doesn't mean free electricity, and neither would fusion. That's because near-100% of the cost of fission electricity comes from the plants (80%) and transmission (20%). Fuel simply doesn't factor into it. If uranium were free, your fission electricity would still cost the exact same. Likewise, a fusion plant that maintains plasma at 150 million K isn't going to be free to build/operate.
Bertrand Schmitt retweeted
With all due respect to one of the Godfathers of neural nets, who has forgotten more math than I will ever know, there is nothing wise about what he is saying here at all.
1) We're already making progress on "alignment" and/or teaching machines what we want them to understand.
Contrary to the nonsense belief of some folks who tell us alignment is "impossible" or "we're making no progress", we're actually already making tons of progress in a very short time frame on guiding neural nets and seeing what is inside them.
Check out RLAIF (arxiv.org/abs/2309.00267), RLHF (huggingface.co/blog/rlhf), Claude's personality training (anthropic.com/research/claudâŠ), Golden Gate Claude research (anthropic.com/news/golden-gaâŠ) where they figure out what neurons go with what concepts and suppress them or emphasize them, and community groups like Eluether on Eliciting Latent Knowledge (eleuther.ai/projects/elk).
Now try looking inside a human's head and figuring out where one of their stupid/nonsensical beliefs came from.
Can't be done.
In fact, I argue we can already guide/teach/train AIs better than we can children or people.
When you teach a kid a value what is the chance the child actually ingests that value?
Answer: Who the hell knows!
Why did they or didn't they accept it or reject it?
Answer: Who knows!
Why did some human make a decision or tweet something so idiotic it makes your head spin? What was in their past/chemical makeup/circumstances/wiring/experience that made them do it?
Answer: Who knows!
But with AI we're learning more and more each day and building systems that let us peer inside them and guide them better and that will only get stronger over time, especially if we have open source AIs that we can throw more human minds at understanding versus smaller teams that can only do so much with their closed/proprietary models.
Our incentives are to have systems that do what we want, both from a research and commercial standpoint. That will drive the development of these systems.
2) Like all armchair futurists, Hinton makes the classic mistake of projecting one technology into the future and leaving everything else the same. In other words we get superintelligence but nothing else in society or technology develops. We get no parallel developments in safety, training methodologies, societal counters, etc, etc.
It's like saying in the Wright brothers era that future planes will be made of canvas and wood and we'll never figure out any other ways to make them safer or more robust. We develop better safety procedures as we go. Changes at the technological and societal level happen in parallel. The future is trillions and trillions of variables all changing at the same time.
That's how we got to modern planes that carry people all over the planet with an accident record of one every 1.26 million flights from Wilbur circling Kitty Hawk two or three times on a glorified kite.
That is how all technology has developed in the history of the world. Over time we get lots and lots of planes and with each passing day we make them stronger, faster, better and safer.
Elon makes his spaceships better with every flight, learning from the past. Eventually it will be a shocking event when even a single one blows up because his team managed to make them so safe that it becomes a massively outlier when one fails.
Go read about race cars in the early days of Enzo Ferrari in the book "Ferrari, The Man and the Machine". Drivers regularly died and went careening into crowds, killing dozens of onlookers in the 1940s and 50s.
Now go watch an F1 race today. Watch someone get out of a burning car, with only minor burns because he's wearing super advanced fire suppression clothing. Watch a car flip and slide along upside down on the Halo that protects the driver's head and watch him pop out unharmed. Both of those happened last year.
In fact, despite cars going at breakneck speeds, we're shocked when a single person dies because the mitigations are in place to make something even wildly dangerous like F1 safe.
To think we will develop no mitigations for AI and learn nothing as we work with and deploy the technology is just nonsense and the most basic error anyone can make in long term predictions. Life develops all at once, in parallel, at the societal and technological level.
3) Lastly, just because Hinton knows a lot about of neural nets does not mean he knows a damn thing about long term society and technological predictions.
Don't make the mistake that expertise in one area applies to any other area.
Who cares what a neurosurgeon says about running a hospital at scale? They're only marginally related and knowledge of how to do one has nothing to do with the other.
Also, one celebrity endorser in a doomsday x-risk cult does not make a cult legitimate. It just means even smart people can end up getting grifted for their life savings when Jim Jones rolls into town.
If people would stop using the cheap mental heuristic of "Hinton smart about AI, him must know other things too that have the word AI in it" and start looking carefully and closely at his arguments, they would find there's really nothing at all to what he is saying here.
At this point, we'd very much appreciate if Doctor Hinton would stop talking about imaginary x-risk fantasies (and stay out of California politics) and instead enjoy his retirement because he earned it.
Maybe some travel and fine food, good sir? I can recommend the south of France, Japan and Basque country for some food that will blow your mind.
Maybe a beach somewhere to relax? I personally hate just sitting around doing nothing but some people love it. Maybe catch up on reading or painting? A museum tour? Take up gardening.
Leave the future of AI to the applied AI and ML research teams of today and tomorrow.
Don't worry, we got it from here and we're doing just fine.
Wise words from a recent interview with @geoffreyhinton, one of the smartest people in the world regarding AI
Bertrand Schmitt retweeted
I call on the California Assembly to vote no on SB-1047 and Governor Newsom (@GavinNewsom) to veto this pernicious bill if it does pass, or it's likely to destroy California's fantastic history of technological innovation.
This is not an AI safety bill. It is a Trojan horse.
It's designed to look simple and measured but its real purpose is to give a small, fringe group of anti-AI extremists a kill switch over advanced AI, while throwing a monkey wrench into California's tech industry.
The reason is clear. It was designed by a small group of non-profits who believe AI will cause the end of the world. Dan Hendrycks (linkedin.com/in/dan-hendryckâŠ), co-founder of the Center for AI Safety, one of the sponsors of the bill, believes with 80% certainty that AI will end all life on the planet. If you start with that dangerously delusional premise you can't possibly craft a sound, sane, innovation protecting bill. You can only craft a bill designed to dramatically slow down or destroy the growth of AI altogether.
California is faced with a clear choice:
Either accept the dystopian sci-fi hallucinations of this small fringe movement (thelogic.co/news/special-repâŠ), with some people in that movement beginning to openly call for violent terrorism against AI labs (xitter.gq/Dan_Jeffries1/status/1âŠ), or bet on California and its unique ability to bring together the best and brightest in the tech world to build the next generation of software.
It's really as simple as that.
Since any bill that starts from the delusional premise of an AI doomsday is fatally flawed by design, I urge lawmakers to start from scratch with a clean, clear bill designed to protect California's prosperity and its world leading tech industry. Consider starting with this draft, SB-1048 (github.com/JeremyNixon/ai-inâŠ), written by pro-California and pro-innovation leaders in the community.
Passing the fatally flawed SB-1047 means passing the torch of the future to other states and other countries.
This is not a prediction. It's just basic cause and effect.
If a model company can choose between two states, one with a high and unreasonable legal burden and one without it, which will they choose as business owners?
Governor Newsom has outright said âI donât want to cede this space to other states or other countries." (courthousenews.com/californiâŠ)
That is exactly what the bill will do, Governor, unless you veto it or push back on it swiftly.
It's worse than that too. Not only will you cede this territory to other states, you risk ceding it to non-western dictatorships that do not share our values and who are racing ahead with AI.
China already has advanced advanced video generation models to rival OpenAI (youtube.com/watch?v=73F11cHhâŠ), a self-driving train (youtube.com/watch?v=kIh8xWxyâŠ) and robo-taxis (youtube.com/watch?v=_ny1uvVTâŠ) in production, Alibaba City Brain (youtube.com/watch?v=mX6hzp6OâŠ) deployed to dozens of cities to control traffic and prevent accidents, as well as advanced military AI (cepa.org/article/china-bets-âŠ).
We cannot afford to cede the future of AI to anti-democratic regimes.
Unfortunately, this bill has continued to move forward, despite the best efforts of the AI business community and more rational voices who have pushed for much needed changes to the bill but been largely ignored. Senator Scott Weiner says he is open to changes (bloomberg.com/news/newsletteâŠ). But the changes his team have made are mostly insubstantial.
The core of the bill is still utterly broken. When the core is broken it doesn't matter what else you do. Minor changes to the rest of it don't effect the essence.
The bill makes model manufacturers certify that nothing bad can ever be done with their models in the future. It holds them responsible for everything that goes wrong forever. This is like making Ford responsible for every drunk driver.
Regulate driving. Hold the drunk driver responsible, not the car maker.
Anti-AI advocates like to say that opponents of this bill hate any and all legislation but that's utter nonsense they know it. Senator Weiner even said "Silicon Valley doesn't like regulation." No, we don't like this bill in particular. We are all for speed limits on the road. That regulates the user of the technology, the car.
We are saying very clearly:
Regulate the use case.
Don't hold the models responsible for everyone else's crimes. Don't punish Microsoft because someone at Enron used Excel to defraud investors. Punish the cheats at Enron.
This is not very complicated. It works in all aspects of law and it has for thousands of years.
So how did we get here? Why has this bill gotten so far?
One of the worst reasons that I've heard from advocates of premature legislation is this persistent catch phrase:
"Look at social media. It's out of control. We should have gotten ahead of it. We've got to get ahead of AI. We've got to do something now."
This is broken reasoning. No regulator could have predicted social media's impact on the world three decades ago. When Representatives Cox and Wyden were crafting the section 230 amendment to the Communications Decency Act in 1996, the number one question of many representatives at the time was "What is the Internet?"
This idea that we can "get ahead of it" is an insidiously seductive message. We all like to believe in our own ability to perfectly predict the future. The problem is we're all just hopelessly bad at it. And the farther out that we go the more impossible it gets.
With all do respect to the Assembly members and Governor Newsom and their respective accomplishments, there is no chance that you or anyone else on the planet can accurately predict what will happen in ten or twenty or thirty years with AI. This is not an indictment of your intelligence or skills in other areas of life. It's just a simple fact.
The future is trillions and trillions of variables all changing at the same time. We might be able to predict small, close up events but the farther you get into the future, the more things change.
It's an illusion to believe that the Senators and Congresspeople in the 1990s could have foreseen remote teleworking, trillions of dollars in e-commerce transactions, the end of book stores, virtual reality, cryptocurrency, the darknet, massively multiplayer games, and social media for all its goods and ills. In the Wright Brothers era nobody on Earth, in Congress or anywhere else, is capable of writing the safety requirements of the Boeing 787 Dreamliner. You cannot design meaningful safety standards for how a commercial jet will function in 2024 back in 1904 when Wilbur is flying a glorified kite of fabric and wood for a few circles around Kitty Hawk.
If we can't predict the future, what do we do? Are we doomed?
No. We do what we've always done. We watch and observe and we address concrete, real world problems as they happen in the real world. For instance, where life and death is involved we should hold technology creators to a higher standard. If you are making a self-driving car, which can kill or injure people when things go wrong, you should have a higher standard.
The only way to properly regulate is to watch as the complex evolution of society and technology play out over time. You see it develop for good and bad, because it is always both, and you try to reduce the ills and incentivize the good. That is society and law in a nutshell. Punish bad, incentivize good.
As a community we feel frontier model companies should be publicly transparent on safety measures and realistic safety efforts like red teaming, which is designed to address actual real world problems with models now, not fantasy sci-fi problems. But we do not agree that model makers, under penalty of perjury, sign a statement saying their model can never be used for anything bad. This is asking for an impossibility.
It's asking people to perfectly predict the future and certify that their model can never be used for any ill purpose. Nobody can do this and it is likely already unworkable under existing contract law. You cannot ask someone to sign a document that says they have to flap their arms real fast and fly. If you do ask someone to sign it, they can easily argue in court that it is "impossible to comply" and that provision is now unenforceable.
As the California legal team at Stimmel law writes on their blog (stimmel-law.com/en/articles/âŠ):
"A party can invoke impossibility and argue that it did not perform its contractual obligations because it was impossible for it to do so."
It is absolutely impossible for a model creator to certify that there is no possible way anything can go wrong with a model in the future. As we already noted, nobody can predict the future perfectly. Nobody is an all knowing oracle, including me and anyone else who tries to predict the future regularly. It will be impossible for them to testify to future events that haven't happened yet.
If the law does pass, every model manufacturer will likely immediately take the state to court on these grounds and win.
It's time for a step back. Please look carefully at this bill and understand its true goals before you make your choice. This bill is designed to look like an AI "safety" bill but its real goal is to make sure that no advanced AI ever develops at all and that of it does, a few self appointed overseers from a fringe movement can kill it.
If your goal is to ensure AI doesn't develop in California and America, or other democratic countries, then you're on the right track because the sponsors of the bill wrote it to do just that.
But if that's not your goal, then I urge you to go back to the drawing board as quickly as possible.
Nobody can predict the future perfectly but we can make one prediction with confidence.
If this bill passes, the next technology revolution will be outside of California.
If that's what you want, Governor and Assembly members, you're making great strides.
If not, there's still time to change course.
Bertrand Schmitt retweeted
Actually, really liked the Apple Intelligence announcement. It must be a very exciting time at Apple as they layer AI on top of the entire OS. A few of the major themes.
Step 1 Multimodal I/O. Enable text/audio/image/video capability, both read and write. These are the native human APIs, so to speak.
Step 2 Agentic. Allow all parts of the OS and apps to inter-operate via "function calling"; kernel process LLM that can schedule and coordinate work across them given user queries.
Step 3 Frictionless. Fully integrate these features in a highly frictionless, fast, "always on", and contextual way. No going around copy pasting information, prompt engineering, or etc. Adapt the UI accordingly.
Step 4 Initiative. Don't perform a task given a prompt, anticipate the prompt, suggest, initiate.
Step 5 Delegation hierarchy. Move as much intelligence as you can on device (Apple Silicon very helpful and well-suited), but allow optional dispatch of work to cloud.
Step 6 Modularity. Allow the OS to access and support an entire and growing ecosystem of LLMs (e.g. ChatGPT announcement).
Step 7 Privacy. <3
We're quickly heading into a world where you can open up your phone and just say stuff. It talks back and it knows you. And it just works. Super exciting and as a user, quite looking forward to it.
Bertrand Schmitt retweeted
General intelligence is *precisely* learning -- the ability to efficiently learn new things, beyond what your genes and past experiences prepared you for.
Current ML has near zero intelligence because static inference with a curve only yields local generalization, with zero ability to adapt/learn, and meanwhile fitting a curve via gradient descent is an extremely data-inefficient process (compared to e.g. discrete program search which can pick up complex, novel tasks from 1-2 examples). It requires a dense sampling of its operational space in order to generalize -- because it is limited to local generalization.
Bertrand Schmitt retweeted
The cost of freaking out about AI
I owe so much to @ylecun & @beenwrekt . Last year, after chatGPT 4 was launched, I had a month or so of extreme anxiety. I hadn't engaged with doomer arguments before, so they sounded extremely appealing & new. Everyone on Twitter was extremely bombastic & arguing how we're all gonna die and at the very least, our jobs will become obsolete in a year.
My deprogramming started w/ following these 2. That's when I started to go beyond the socially formed, panic induced consensus and engage seriously with the arguments for doom & realize these were fantasies unmoored from empirical data. I realized I had ignored what was in front of me and got carried away due to the social consensus. Another thing that really opened my eyes was the weakness of arguments in a domain I could scientifically assess: biorisk and the virality of irresponsible claims regarding how much current models were increasing it.
We live in times when the cost of freaking out about things is not properly recognised. "Better safe than sorry", the story goes. This is how we locked kids out of schools because of Covid, with large implications down the line.
But the cost of freaking out is real. Getting people anxious for no good reason is bad. Over regulating for no reason is bad. We must resist the over anxietification of our culture.
Bertrand Schmitt retweeted
It sounds like a boring topic, but concrete is one of the most revolutionary inventions in history.
For example, concrete now weighs more than everything else humans have ever made combined.
So here's the story of how it has changed the world, for better and for worse...
Bertrand Schmitt retweeted
This a must read for anyone who cares about free speech, science, vaccines, cancel culture, @Harvard and the decline of our elite universities and the pursuit of truth.
An incredible story. Remarkable it happened in America, at Harvard and in the 21st century.
Shame on us.
I am no longer a professor of medicine at @Harvard. Here is the story of my Harvard experience until I was fired for clinging to the truth.
city-journal.org/article/harâŠ
Bertrand Schmitt retweeted
When you hear about "human-level AI" being just "one LLM training run away", it's as if people building 3D printers (the kind that makes small, flimsy plastic objects) were telling you that they've nearly built an infinite matter replicator, capable of scanning and cloning any object -- be it steel, gold, or diamond, be it minuscule or building-scale. "We're just one iteration away! Just need to increase spatial resolution a bit!"
As long as you have absolutely no idea what "matter" is and how 3D printers work, it might sound sort of plausible. But if you do, it's absolutely clown shoes. The way to navigate such claims is to have a proper, formal definition of intelligence.
Bertrand Schmitt retweeted
Andrew explains why some companies have lobbied governments to regulate open source AI out of existence under the false pretense of safety.
This quoted post is unavailable.
Bertrand Schmitt retweeted
People seem to be falling for two rather thoughtless extremes:
1. "LLMs are AGI, they work like the human brain, they can reason, etc."
2. "LLMs are dumb and useless."
Reality is that LLMs are not AGI -- they're a big curve fit to a very large dataset. They work via memorization and interpolation. But that interpolative curve can be tremendously useful, if you want to automate a known task that's a match for its training data distribution.
Memorization works, as long as you don't need to adapt to novelty. You don't *need* intelligence to achieve usefulness across a set of known, fixed scenarios.
In fact, that's the entire story of the field of AI so far: achieve increasing levels of usefulness and automation, while bypassing the problem of creating intelligence.
Bertrand Schmitt retweeted
The knock-on effects of a total arbitrary decision to refuse to give regulatory clarity to one of techâs major acquisitions will decelerate global innovation for decades
Bertrand Schmitt retweeted
Introducing The Rule of X! Finance execs love Rule of 40 for its simplicity, but for many efficient cloud companies, assigning equal weight to growth and profitability is fundamentally flawed! It has caused misguided business decisions. Our take? Even in tight markets, growth should be valued at least 2-3x more than FCF margin. At @BessemerVP, we're introducing The Rule of X -a new metric that more accurately weighs the tradeoff @TechCrunch đ
The Rule of X and how cloud leaders should think about growth versus profit tcrn.ch/3RLh5yQ































