Recent progress in AI has led to rapid saturation of most capability benchmarks - MMLU, RE-Bench, etc. Even much more sophisticated benchmarks such as ARC-AGI or FrontierMath see incredibly fast improvement, and all that while severe under-elicitation is still very salient.

As has been pointed out by many, general capability involves more than simple tasks such as this, that have a long history in the field of ML and are therefore easily saturated. Claude Plays Pokemon is a good example of something somewhat novel in terms of measuring progress, and thereby benefited from being an actually good proxy of model capability.

Taking inspiration from examples such as this, we considered domains of general capacity that are even further decoupled from existing exhaustive generators. We introduce BenchBench, the first standardized...

Hey Everyone,

It is with a sense of... considerable cognitive dissonance that I am letting you all know about a significant development for the future trajectory of LessWrong. After extensive internal deliberation, projections of financial runways, and what I can only describe as a series of profoundly unexpected coordination challenges, the Lightcone Infrastructure team has agreed in principle to the acquisition of LessWrong by EA.

I assure you, nothing about how LessWrong operates on a day to day level will change. I have always cared deeply about the robustness and integrity of our institutions, and I am fully aligned with our stakeholders at EA. 

To be honest, the key thing that EA brings to the table is money and talent. While the recent layoffs in EAs broader industry have been...

I'm not writing this to alarm anyone, but it would be irresponsible not to report on something this important. On current trends, every car will be crashed in front of my house within the next week. Here's the data:

Until today, only two cars had crashed in front of my house, several months apart, during the 15 months I have lived here. But a few hours ago it happened again, mere weeks from the previous crash. This graph may look harmless enough, but now consider the frequency of crashes this implies over time:

The car crash singularity will occur in the early morning hours of Monday, April 7. As crash frequency approaches infinity, every car will be involved. You might be thinking that the same car could be involved in multiple crashes. This is true! But the same car can only withstand a finite number of crashes before it is no longer able to move. It follows that every car will be involved in at least one crash. And who do you think will be driving your car? 

In the debate over AI development, two movements stand as opposites: PauseAI calls for slowing down AI progress, and e/acc (effective accelerationism) calls for rapid advancement.  But what if both sides are working against their own stated interests?  What if the most rational strategy for each would be to adopt the other's tactics—if not their ultimate goals?

AI development speed ultimately comes down to policy decisions, which are themselves downstream of public opinion.  No matter how compelling technical arguments might be on either side, widespread sentiment will determine what regulations are politically viable.

Public opinion is most powerfully mobilized against technologies following visible disasters.  Consider nuclear power: despite being statistically safer than fossil fuels, its development has been stagnant for decades.  Why?  Not because of environmental activists, but because...

Introduction

Decision theory is about how to behave rationally under conditions of uncertainty, especially if this uncertainty involves being acausally blackmailed and/or gaslit by alien superintelligent basilisks.

Decision theory has found numerous practical applications, including proving the existence of God and generating endless LessWrong comments since the beginning of time.

However, despite the apparent simplicity of "just choose the best action", no comprehensive decision theory that resolves all decision theory dilemmas has yet been formalized. This paper at long last resolves this dilemma, by introducing a new decision theory: VDT.

Decision theory problems and existing theories

Some common existing decision theories are:

• Causal Decision Theory (CDT): select the action that *causes* the best outcome.
• Evidential Decision Theory (EDT): select the action that you would be happiest to learn that you had taken.
• Functional Decision Theory

After ~3 years as the ACX Meetup Czar, I've decided to resign from my position, and I intend to scale back my work with the LessWrong community as well. While this transition is not without some sadness, I'm excited for my next project.

I'm the Meetup Czar of the new Fewerstupidmistakesity community.

We're calling it Fewerstupidmistakesity because people get confused about what "Rationality" means, and this would create less confusion. It would be a stupid mistake to name your philosophical movement something very similar to an existing movement that's somewhat related but not quite the same thing. You'd spend years with people confusing the two. 

What's Fewerstupidmistakesity about? It's about making fewer stupid mistakes, ideally down to zero such stupid mistakes. Turns out, human brains have lots of scientifically proven...

I think rationalists should consider taking more showers.

As Eliezer Yudkowsky once said, boredom makes us human. The childhoods of exceptional people often include excessive boredom as a trait that helped cultivate their genius:

A common theme in the biographies is that the area of study which would eventually give them fame came to them almost like a wild hallucination induced by overdosing on boredom. They would be overcome by an obsession arising from within.

Unfortunately, most people don't like boredom, and we now have little metal boxes and big metal boxes filled with bright displays that help distract us all the time, but there is still an effective way to induce boredom in a modern population: showering.

When you shower (or bathe, that also works), you usually are cut off...