LessWrong (Curated & Popular)

Thanks to Jesse Richardson for discussion. Polymarket asks: will Jesus Christ return in 2025? In the three days since the market opened, traders have wagered over $100,000 on this question. The market traded as high as 5%, and is now stably trading at 3%. Right now, if you wanted to, you could place a bet that Jesus Christ will not return this year, and earn over $13,000 if you're right. There are two mysteries here: an easy one, and a harder one. The easy mystery is: if people...

03-25

07:48

TL;DR Having a good research track record is some evidence of good big-picture takes, but it's weak evidence. Strategic thinking is hard, and requires different skills. But people often conflate these skills, leading to excessive deference to researchers in the field, without evidence that that person is good at strategic thinking specifically. Introduction I often find myself giving talks or Q&As about mechanistic interpretability research. But inevitably, I'll get questions about t...

03-23

06:58

When my son was three, we enrolled him in a study of a vision condition that runs in my family. They wanted us to put an eyepatch on him for part of each day, with a little sensor object that went under the patch and detected body heat to record when we were doing it. They paid for his first pair of glasses and all the eye doctor visits to check up on how he was coming along, plus every time we brought him in we got fifty bucks in Amazon gift credit. I reiterate, he was three. (To begin ...

03-22

03:45

I’m releasing a new paper “Superintelligence Strategy” alongside Eric Schmidt (formerly Google), and Alexandr Wang (Scale AI). Below is the executive summary, followed by additional commentary highlighting portions of the paper which might be relevant to this collection of readers. Executive Summary Rapid advances in AI are poised to reshape nearly every aspect of society. Governments see in these dual-use AI systems a means to military dominance, stoking a bitter race to maximize AI capab...

03-22

09:03

This is a link post. Summary: We propose measuring AI performance in terms of the length of tasks AI agents can complete. We show that this metric has been consistently exponentially increasing over the past 6 years, with a doubling time of around 7 months. Extrapolating this trend predicts that, in under a decade, we will see AI agents that can independently complete a large fraction of software tasks that currently take humans days or weeks. Full paper | Github repo --- First...

03-19

01:19

I have, over the last year, become fairly well-known in a small corner of the internet tangentially related to AI. As a result, I've begun making what I would have previously considered astronomical amounts of money: several hundred thousand dollars per month in personal income. This has been great, obviously, and the funds have alleviated a fair number of my personal burdens (mostly related to poverty). But aside from that I don't really care much for the money itself. My long term ambit...

03-19

02:17

Note: this is a research note based on observations from evaluating Claude Sonnet 3.7. We’re sharing the results of these ‘work-in-progress’ investigations as we think they are timely and will be informative for other evaluators and decision-makers. The analysis is less rigorous than our standard for a published paper. Summary We monitor Sonnet's reasoning for mentions that it is in an artificial scenario or an alignment test. Claude Sonnet 3.7 appears to be aware of being tested for alig...

03-18

18:05

Scott Alexander famously warned us to Beware Trivial Inconveniences. When you make a thing easy to do, people often do vastly more of it. When you put up barriers, even highly solvable ones, people often do vastly less. Let us take this seriously, and carefully choose what inconveniences to put where. Let us also take seriously that when AI or other things reduce frictions, or change the relative severity of frictions, various things might break or require adjustment. This applies to all...

03-18

22:43

There's this popular trope in fiction about a character being mind controlled without losing awareness of what's happening. Think Jessica Jones, The Manchurian Candidate or Bioshock. The villain uses some magical technology to take control of your brain - but only the part of your brain that's responsible for motor control. You remain conscious and experience everything with full clarity. If it's a children's story, the villain makes you do embarrassing things like walk through the street na...

03-17

06:58

This research was conducted at AE Studio and supported by the AI Safety Grants programme administered by Foresight Institute with additional support from AE Studio. Summary In this post, we summarise the main experimental results from our new paper, "Towards Safe and Honest AI Agents with Neural Self-Other Overlap", which we presented orally at the Safe Generative AI Workshop at NeurIPS 2024. This is a follow-up to our post Self-Other Overlap: A Neglected Approach to AI Alignment, which in...

03-17

12:22

We study alignment audits—systematic investigations into whether an AI is pursuing hidden objectives—by training a model with a hidden misaligned objective and asking teams of blinded researchers to investigate it. This paper was a collaboration between the Anthropic Alignment Science and Interpretability teams. Abstract We study the feasibility of conducting alignment audits: investigations into whether models have undesired objectives. As a testbed, we train a language model with a hidd...

03-16

24:14

The Most Forbidden Technique is training an AI using interpretability techniques. An AI produces a final output [X] via some method [M]. You can analyze [M] using technique [T], to learn what the AI is up to. You could train on that. Never do that. You train on [X]. Only [X]. Never [M], never [T]. Why? Because [T] is how you figure out when the model is misbehaving. If you train on [T], you are training the AI to obfuscate its thinking, and defeat [T]. You will rapidly lose your ability t...

03-14

32:12

You learn the rules as soon as you’re old enough to speak. Don’t talk to jabberjays. You recite them as soon as you wake up every morning. Keep your eyes off screensnakes. Your mother chooses a dozen to quiz you on each day before you’re allowed lunch. Glitchers aren’t human any more; if you see one, run. Before you sleep, you run through the whole list again, finishing every time with the single most important prohibition. Above all, never look at the night sky. You’re a precocious child. Y...

03-13

22:28

Exciting Update: OpenAI has released this blog post and paper which makes me very happy. It's basically the first steps along the research agenda I sketched out here. tl;dr: 1.) They notice that their flagship reasoning models do sometimes intentionally reward hack, e.g. literally say "Let's hack" in the CoT and then proceed to hack the evaluation system. From the paper: The agent notes that the tests only check a certain function, and that it would presumably be “Hard” to implement a g...

03-11

07:21

LLM-based coding-assistance tools have been out for ~2 years now. Many developers have been reporting that this is dramatically increasing their productivity, up to 5x'ing/10x'ing it. It seems clear that this multiplier isn't field-wide, at least. There's no corresponding increase in output, after all. This would make sense. If you're doing anything nontrivial (i. e., anything other than adding minor boilerplate features to your codebase), LLM tools are fiddly. Out-of-the-box solutions don'...