Claude is smarter than you. Deal with it. 

There is an incredible amount of cope about the current abilities of AI. 

AI isn't infallible. Of course. And yet...

For 90% of queries a well-prompted AI has better responses than 99% of people.For some queries the number of people that could match the kind of deep, broad knowledge that AI has can be counted on two hands. Finally, obviously, there is no man alive on the face of the earth that comes even close to the breadth and depth of crystallized intelligence that AIs now have. 

People have developped a keen apprehension and aversion for " AI slop". The truth of the matter is that  LLMs are incredible writers and if you had presented AI slop as human writing to somebody ten six years ago they would say it is good if somewhat corporate writing all the way to inspired, eloquent, witty. 

Does AI sometimes make mistakes? Of course. So do humans. To be human is to err.

There is an incredible amount of cope about the current abilities of AI. Frankly, I find it embarassing. Witness the absurd call to flag AI-assisted writing. The widespread disdain for " @grok is this true?" . Witness how llm psychosis has gone from perhaps... (read more)

Reward is not the optimization target. 

The optimization target is the Helmholtz free energy functional in the conductance-corrected Wasserstein metric for the step-size effective loss potential in the critical batch size regime for the weight-initialization distribution as prior up to solenoidal flux corrections

Additive versus Multiplicative model of AI-assisted research

Occasionally one hears somebody say "most of the relevant AI-safety work will be done at crunch time. Most work being done now at present is marginal". 

One cannot shake the suspicion that this statement merely reflects the paucity of ideas & vision of the speaker. Yet it cannot be denied that their reasoning has a certain logic: if, as seems likely, AI will become more and more dominant in AI alignment research than maybe we should be focusing on how to safely extract work from future superintelligent machines rather than hurting our painfully slow mammalian walnuts to crack AI safety research today. I understand this to be a key motivation for several popular agendas AI safety.

Similarly, many Pause advocates argue that pause advocacy  is more impactful than direct research. Most will admit that a Pause cannot be maintained indefinitely. The aim of a Pause would be to buy time to figure out alignment. Unless one believes in very long pauses, implicitly it seems there is an assumption that research progress will be faster in the future. 

Implicitly, we might say there is underlying " Additive" model of AI-... (read more)

Assuming a Chinese invasion of Taiwan in 2027/2028 what is the most sensible investment strategy?

TSMC puts seem sensible. What are others?

Highly recommended video on drone development in the Ukraine-Russia war, interview with a Russian private military drone developer. 

some key takeaways

• Drones now account for >70% of kills on the battlefields.
• There are few to none effective counters to drones. The on
  • Electronic jamming is a rare exception but drones carrying 5-15km fiber optic cables are immune to jamming. In the future AI-controlled drones will be immune to jamming.
  • 'Laser is currently a joke. It works in theory, not in practice. Western demonstrations at expos are always in ideal conditions. ' but he also says that both Russia and Ukraine are actively working on the technology and he thinks it could be an effective weapon.
  • Nets can be effective but fiber-optic drones can fly very low and not lose connection are increasingly used to slip under the nets.
  • Soldiers are increasingly opting for bikes instead of vehicles as the latter don't offer much protection to drones.
• The big elephant in the room: AI drones.
  • It seems like the obvious next step - why hasn't it happened yet?
  • 'at Western military expos everybody is talking AI-controlled drones. This is nonsense of course' Apparently the limitation is that it's currentl

Did the Classical Greeks have any conception of when the Iliad happened?

According to Claude the Classical Greeks not only believed in the historicity of the Iliad - they also had surprisingly accurate dating! 

The ancient Greeks generally did believe the Iliad described real historical events, though their understanding of it was more nuanced than simply accepting every detail as literal fact.

Belief in Historical Reality

Most classical Greeks, including prominent historians and philosophers, treated the Trojan War as a genuine historical event. Herodotu

Is there interest in an anthropics arcana festival ? Reply with party react for yes

Large Language Models, Small Labor Market Effects?

We examine the labor market effects of AI chatbots using two large-scale adoption surveys (late 2023 and 2024) covering 11 exposed occupations (25,000 workers, 7,000 workplaces), linked to matched employer-employee data in Denmark. AI chatbots are now widespread—most employers encourage their use, many deploy in-house models, and training initiatives are common. These firm-led investments boost adoption, narrow demographic gaps in take-up, enhance workplace utility, and create new job tasks. Yet, despite substantial investments, economic impacts remain minimal. Using difference-in-differences and employer policies as quasi-experimental variation, we estimate precise zeros: AI chatbots have had no significant impact on earnings or recorded hours in any occupation, with confidence intervals ruling out effects larger than 1%. Modest productivity gains (average time savings of 2.8%), combined with weak wage pass-through, help explain these limited labor market effects. Our findings challenge narratives of imminent labor market transformation due to Generative AI.

From marginal revolution. 

What does this crowd think? These effects ar... (read more)

The Marginal Returns of Intelligence

A lot of discussion of intelligence considers it as a scalar value that measures a general capability to solve a wide range of tasks. In this conception of intelligence it is primarily a question of having a ' good Map' . This is a simplistic picture since it's missing the intrinsic limits imposed on prediction by the Territory.  Not all tasks or domains have the same marginal returns to intelligence - these can vary wildly. 

Let me tell you about a 'predictive efficiency' framework that I find compelling & deep and that will hopefully give you some mathematical flesh to these intuitions. I initially learned about these ideas in the context of Computational Mechanics, but I realized that there underlying ideas are much more general. 

Let $X$ be a predictor variable that we'd like to use to predict a target variable $Y$ under a joint distribution $p(x,y)$. For instance $X$ could be the contex window and $Y$ could be the next hundred tokens, or $X$ could be the past market data and $Y$ is the future market data. 

 In any prediction task there are three fundamental and independently varying quantities that you need to think of:

•  $H(Y\mid$

Is Superhuman Persuasion a thing?

Sometimes I see discussions of AI superintelligence developping superhuman persuasion and extraordinary political talent. 

Here's some reasons to be skeptical of the existence of 'superhuman persuasion'. 

1. We don't have definite examples of extraordinary political talent.
   
   Famous politicians rose to power only once or twice. We don't have good examples of an individual succeeding repeatedly in different political environments. 
   Examples of very charismatic politicans can be better explained by ' the right person at the right time or place'. 
    
2. Neither do we have strong examples of extraordinary persuasion. 
   >> For instance hypnosis is mostly explained by people wanting to be persuaded by the hypnotist. If you don't want to be persuaded it's very hard to change your mind. There is some skill in persuasion required for sales, and sales people are explicitly trained to do so but beyond a fairly low bar the biggest predictors for salesperson success is finding the correct audience and making a lot of attempts. 

Another reason has to do with the ' intrinsic skill ceiling of a domain' .

For an agent A to have a very high skil... (read more)

Ryan Greenblatt on steering the AI paradigm:

I'm skeptical of strategies which look like "steer the paradigm away from AI agents + modern generative AI paradigm to something else which is safer". Seems really hard to make this competitive enough and I have other hopes that seem to help a bunch while being more likely to be doable.

(This isn't to say I expect that the powerful AI systems will necessarily be trained with the most basic extrapolation of the current paradigm, just that I think steering this ultimate paradigm to be something which is quite differ

In an anthropically selected world one would expect to see some conspicuous coincidences - especially related to events and people that are highly counterfactual. Most events are not highly counterfactual. How this or that person lived and died - for the grand course of history it didn't matter. 

A small group of individuals plausibly did change the course of history, at least somewhat. Unfortunately, it seems it much more likely to be counterfactually impactful by being very evil than being very good. It is easier to break things and easier murder en ... (read more)

Voters are irrational. 

Voters want better health care, a powerful military, a strong social security net, but also lower taxes. There's 120% demands but only 100% to go around. 

Voters also often believe their pet issue voting bloc is more powerful than it actually is. It’s an interesting question to ask why people like to believe their voting bloc is larger than it really is. One reason might be that the people that are ill-calibrated on their own causal impact are more likely to show up as a voter. 

It follows that an effective politician lies. There is no blame to go to politicans really. The average politician is a Christ-like figure that takes on the karmic burden of dishonesty for the dharma, because voters are children. 

A conventional politician lies sure - but he or she would not want to be known as a liar. Being known as a liar seems bad. But there is another type of politician: the 'Brazen Liar Politican' who is known to be a liar, who lies blatantly and lies often, who puts no effort in hiding their lies. 

How could this possibly be a good political strategy? Well the voters know that he's a liar but paradoxically that may make them more l... (read more)

Forecasting and scenario building has become quite popular and prestigious in EA-adjacent circles. I see extremely detailed scenario building & elaborate narratives. 

Yes AI will be big, AGI plausibly close. But how much detail can one really expect to predict? There were a few large predictions that some people got right, but once one zooms in the details don't fit while the correct predictions were much more widespread within the group of people that were paying attention. 

I can't escape the feeling that we're quite close to the limits of the knowable and 80% of EA discourse on this is just larp.  

Does anybody else feel this way?

Why no large hive intelligences?
Ants, social wasps, bees, termites dominate vertebrate biomass. On the insect level these are incredibly dominant in the biosphere. Eusociality is a game-changing tech. Yet with a single exception there are no large hive intelligence. That single exception is the naked mole rat - a rare non-dominant species. Why?

Claude suggests:

• Genetic predisposition: Hymenopteran insects (ants, bees, wasps) have a haplodiploid genetic system where females share 75% of their genes with sisters but only 50% with their own offspring. This crea

The Ammann Hypothesis: Free Will as a Failure of Self-Prediction

A fox chases a hare. The hare evades the fox. The fox tries to predict where the hare is going - the hare tries to make it as hard to predict as possible. 

Q: Who needs the larger brain? 

A: The fox. 

This is a little animal tale meant to illustrate the following phenomenon: 

Generative complexity can be much smaller than predictive complexity under partial observability. In other words, when partially observing a blackbox there are simple internal mechanism that create complex patterns that require very large predictors to predict well. 

Consider the following simple 2-state HMM 

Note that the symbol 0 is output in three different ways: A -> A, A-> B, and B -> B. This means that if we see the symbol 0 we don't know where we are. We can use Bayesian updating to  guess where we are but starting from a stationary distribution our belief states can become extremely complicated - in fact, the data sequence generated by the simple nonunifalar source has an optimal predictor HMM that requires infinitely many states :

This simple example illustrates the gap between generative complexity an... (read more)

Why Do the French Dominate Mathematics?

France has an outsized influence in the world of mathematics despite having significantly fewer resources than countries like the United States. With approximately 1/6th of the US population and 1/10th of its GDP, and French being less widely spoken than English, France's mathematical achievements are remarkable.

This dominance might surprise those outside the field. Looking at prestigious recognitions, France has won 13 Fields Medals compared to the United States' 15 a nearly equal achievement despite the vast difference in population and resources. Other European nations lag significantly behind, with the UK having 8, Russia/Soviet Union 6/9, and Germany 2.

France's mathematicians are similarly overrepresented in other mathematics prizes and honors, confirming this is not merely a statistical anomaly.

I believe two key factors explain France's exceptional performance in mathematics while remaining relatively average in other scientific disciplines:

1. The "Classes Préparatoires" and "Grandes Écoles" System

The French educational system differs significantly from others through its unique "classes préparatoires" (preparatory classes) and "grandes ... (read more)

ADHD is about the Voluntary vs Involuntary actions

The way I conceptualize ADHD is as a constraint on the quantity and magnitude of voluntary actions I can undertake. When others discuss actions and planning, their perspective often feels foreign to me—they frame it as a straightforward conscious choice to pursue or abandon plans. For me, however, initiating action (especially longer-term, less immediately rewarding tasks) is better understood as "submitting a proposal to a capricious djinn who may or may not fulfill the request." The more delayed the gratification and the longer the timeline, the less likely the action will materialize.

After three decades inhabiting my own mind, I've found that effective decision-making has less to do with consciously choosing the optimal course and more with leveraging my inherent strengths (those behaviors I naturally gravitate toward, largely outside my conscious control) while avoiding commitments that highlight my limitations (those things I genuinely intend to do and "commit" to, but realistically never accomplish).

ADHD exists on a spectrum rather than as a binary condition. I believe it serves an adaptive purpose—by restricting the number of... (read more)

Is Tesla currently overvalued ?

P/e ratio is 188. The ceo has made himself deeply unpopular with many potential customers. Latest sales figures don't look good. Chinese competitors sell more total cars and seem to have caught up in terms of tech.

Can somebody ELI5 how much I should update on the recent SAE = dead salmon news?

On priors I would expect the SAE bear news to be overblown. 50% of mechinterp is SAEs - a priori, it seems unlikely to me that so many talented people went astray. But I'm an outsider and curious about alternate views. 

You May Want to Know About Locally Decodable Codes

In AI alignment and interpretability research, there's a compelling intuition that understanding equals compression. The idea is straightforward: if you truly understand a system, you can describe it more concisely by leveraging that understanding. This philosophy suggests that better interpretability techniques for neural networks should yield better compression of their behavior or parameters.

jake_mendel asks: if understanding equals compression, then shouldn't ZIP compression of neural network weights count as understanding? After all, ZIP achieves remarkable compression ratios on neural network weights - likely better than any current interpretability technique. Yet intuitively, having a ZIP file of weights doesn't feel like understanding at all! We wouldn't say we've interpreted a neural network just because we've compressed its weights into a ZIP file.

Compressing a bit string means finding a code for that string, and the study of such codes is the central topic of both algorithmic and Shannon information theory. Just compressing the set of weights as small as possible is too naive - we probably want to impose additional proper... (read more)