PODCAST

LessWrong (30+ Karma)

LessWrong

Audio narrations of LessWrong posts.

technology philosophy

All Episodes

11:25

“Realistic Evaluations Will Not Prevent Evaluation...

LessWrong (30+ Karma) ·

2026/02/25

One Minute Summary I think there's a fundamental limit to behavioral alignment evaluations that gets worse as models improve: Humans control all inputs to a model and can snapshot, replay, or fabricate any scenario at will. An intelligent model could realize this and rationally treat every interaction as a potential evaluation. This means that even perfectly realistic evaluations, including ones sampled directly from deployment, may not prevent evaluation awareness. OpenAI has found this is already

en-gb

6:35

“A simple rule for causation” by Vivek Hebbar

LessWrong (30+ Karma) ·

2026/02/25

Here's a simple rule about causal inference: If everything related[1]to A is also related to B, we can conclude that A is causally upstream of B. Conversely, if we find even a single thing X which is related to A but independent of B, we can conclude that A is not causally upstream of B. For example, consider the claim "rain causes me to carry an umbrella": It should be impossible to think of a thing that is correlated with rain that isn't also correlated with me carrying an umbrella.[2] Whereas

en-gb

41:46

“Citrini’s Scenario Is A Great But Deeply Flawed...

LessWrong (30+ Karma) ·

2026/02/25

A viral essay from Citrini about how AI bullishness could be bearish was impactful enough for Bloomberg to give it partial responsibility for a decline in the stock market, and all the cool economics types are talking about it.So fine, let's talk. It's an excellent work of speculative fiction, in that it: Depicts a concrete scenario with lots of details and numbers. Introduces a bunch of underexplored and important mechanisms. Gets a lot of those mechanisms more right than you would

en-gb

50:55

“Wildlife Biology forgot how definitions work” by...

LessWrong (30+ Karma) ·

2026/02/24

TDLR: Biology has no consistently applied definition of "species." The field operates on vibes, reverse-engineered justifications, and conservation politics. I propose a litmus test: any species definition that, if applied consistently, would split Homo sapiens into multiple species is wrong. This kills the Biological Species Concept, the phylogenetic species concept, and most morphological/ecological criteria. What survives is something close to "gene flow between them is biologically impossible,"

en-gb

5:32

“Exclusive: Hegseth gives Anthropic until Friday to...

LessWrong (30+ Karma) ·

2026/02/24

Defense Secretary Pete Hegseth gave Anthropic CEO Dario Amodei until Friday evening to give the military unfettered access to its AI model or face harsh penalties, Axios has learned. The big picture: Hegseth told Amodei in a tense meeting on Tuesday that the Pentagon will either cut ties and declare Anthropic a "supply chain risk," or invoke the Defense Production Act to force the company to tailor its model to the military's needs. Why it matters: The Pentagon wants to punish Anthropic as the feud

en-gb

63:02

“Responsible Scaling Policy v3” by HoldenKarnofsky

LessWrong (30+ Karma) ·

2026/02/24

All views are my own, not Anthropic's. This post assumes Anthropic's announcement of RSP v3.0 as background. Today, Anthropic released its Responsible Scaling Policy 3.0. The official announcement discusses the high-level thinking behind it. This is a more detailed post giving my own takes on the update. First, the big picture: I expect some people will be upset about the move away from a “hard commitments”/”binding ourselves to the mast” vibe. (Anthropic has always had the ability to revise the

en-gb

3:36

“Open sourcing a browser extension that tells you...

LessWrong (30+ Karma) ·

2026/02/24

Example of OpenErrata nitting the Sequences I just published OpenErrata on GitHub, a browser extension that investigates the posts you read using your OpenAI API key and underlines any factual claims that are sourceably incorrect. Once finished, it caches the results for anybody else reading the same articles so that they get them on immediate visit. If you don't have an OpenAI key, you can still view the corrections on posts other people have viewed, but it doesn't start new investigations. I've

en-gb

8:14

“Large-Scale Online Deanonymization with LLMs” by...

LessWrong (30+ Karma) ·

2026/02/24

TL;DR: We show that LLM agents can figure out who you are from your anonymous online posts. Across Hacker News, Reddit, LinkedIn, and anonymized interview transcripts, our method identifies users with high precision – and scales to tens of thousands of candidates. While it has been known that individuals can be uniquely identified by surprisingly few attributes, this was often practically limited. Data is often only available in unstructured form and deanonymization used to require human

en-gb

20:05

“AI Impact Summit 2026 : A Field Report” by Aditya,...

LessWrong (30+ Karma) ·

2026/02/24

This post is detailing our experience attending the AI Impact Summit and its associated side events in Delhi, February 2026. We are both unfamiliar with the policy and governance domain. This is just an honest reaction attending these events, maybe there are 2nd order effects we are not privy to and we welcome feedback. Two events ran in parallel: the main AI Impact Summit and a separate, more curated side event called AI Safety Connect (AISC), co-hosted with the International Association for Safe

en-gb

5:48

“Secrets of the LessWrong RSS Feed” by Brendan Long

LessWrong (30+ Karma) ·

2026/02/24

LessWrong's RSS feed includes all recently published articles by default, but it has a bunch of undocumented features available with query params: You can request only posts above a certain karma (karmaThreshold), only with certain authors (userId), frontpage only (view=frontpage), curated-only (view=curated), and several other views. Just the frontpage: https://www.lesswrong.com/feed.xml?view=frontpage My posts: https://www.lesswrong.com/feed.xml?userId=piR3ZKGHEp6vqTo87[1] Comments have RSS

en-gb

7:32

“The ML ontology and the alignment ontology” by...

LessWrong (30+ Karma) ·

2026/02/24

This post contains some rough reflections on the alignment community trying to make its ontology legible to the mainstream ML community, and the lessons we should take from that experience. Historically, it was difficult for the alignment community to engage with the ML community because the alignment community was using a fundamentally different ontology—featuring concepts like inner vs outer alignment, mesa-optimizers, corrigibility, situational awareness, and so on. Even a concept as simple as

en-gb

13:29

“Bioanchors 2: Electric Bacilli” by TsviBT

LessWrong (30+ Karma) ·

2026/02/24

Crosspost from my blog. [Previously: "Views on when AGI comes and on strategy to reduce existential risk", "Do confident short timelines make sense?"] [Whenever discussing when AGI will come, it bears repeating: If anyone builds AGI, everyone dies; no one knows when AGI will be made, whether soon or late; a bunch of people and orgs are trying to make it; and they should stop and be stopped.] Arguments for fast AGI progress Many arguments about "when will AGI come" focus on reasons to think

en-gb

94:25

“The persona selection model” by Sam Marks

LessWrong (30+ Karma) ·

2026/02/23

TL;DR We describe the persona selection model (PSM): the idea that LLMs learn to simulate diverse characters during pre-training, and post-training elicits and refines a particular such Assistant persona. Interactions with an AI assistant are then well-understood as being interactions with the Assistant—something roughly like a character in an LLM-generated story. We survey empirical behavioral, generalization, and interpretability-based evidence for PSM. PSM has consequences for AI development,

en-gb

8:10

“Fact-checking an AI optimist article in The...

LessWrong (30+ Karma) ·

2026/02/23

On 26 January 2026, The Economist (a very well-respected, mainstream publication) published an optimistic article arguing that AI won’t displace white collar jobs. Specifically, the article claimed: Rather than wipe out office jobs, artificial intelligence will expand their scope and raise their value. — “Why AI won’t wipe out white-collar jobs” in The Economist (26 Jan 2026) They followed that up with a podcast on 19 February making the same points. Some of the numbers in that article (and

en-gb

3:00

[Linkpost] “The 2028 Global Intelligence Crisis - a...

LessWrong (30+ Karma) ·

2026/02/23

This is a link post. A popular (#1 in Substack's Finance category) financial analyst - Citrini - published a "Macro Memo from June 2028" plotting a potential future of increasing AI capabilities, with a focus on financial markets. This is not a person who has typically engaged in the usual LW discourse, making this an interesting outsider's perspective. Some extracts: The unemployment rate printed 10.2% this morning, a 0.3% upside surprise. The market sold off 2% on the number, bringing the

en-gb

4:41

“Storing Food” by jefftk

LessWrong (30+ Karma) ·

2026/02/23

I think more people should be storing a substantial amount of food. It's not likely you'll need it, but as with reusable masks the cost is low enough I think it's usually worth it. It's hard for me to really imagine living through a famine. The world as I have experienced it has been one of abundant calories, where people are generally more worried about getting too many than too few. Essentially no one dies in the US from food unavailability. Globally, however, it's different: each year

en-gb

7:17

“InsanityBench: Cryptic Puzzles as a Probe for...

LessWrong (30+ Karma) ·

2026/02/23

TLDR: InsanityBench is a benchmark of handcrafted cryptic puzzles trying to measure creative conceptual leaps as required in, for example, scientific breakthroughs - SOTA models score around 10% - the benchmark is very much in its earliest form and will need to be properly scaled to reduce variance. You are given this image and prompted to "solve" it, only left with the title Timely Journey. What are you thinking of? (In case you genuinely wanna try, stop reading for now, here's the link to the

en-gb

2:56

“My RSS Reader is Done” by Brendan Long

LessWrong (30+ Karma) ·

2026/02/23

I posted a few months ago about vibe-coding an RSS reader. The mood on the internet seems to be that these apps are buggy and never get finished, so I figured it was worth posting an update. Another thousand commits later, Lion Reader supports every feature I care about, works reliably, has very good performance, and is open for public signups[1]. I've actually been using it for a while, and mostly kept signups closed because of some expensive features like AI summaries (now handled by making users

en-gb

5:07

“Changing the world for the worse” by mingyuan

LessWrong (30+ Karma) ·

2026/02/23

When I was 21, I was sucked into a world of ambition. Starting my adult life in the Bay Area, I was surrounded by the sense that I was supposed to start a startup, change the world. I never wanted to start a startup. Reading stories of famous founders, and living and working with startup founders myself, it seemed to me that the amount of belief you’d have to have in yourself and your idea bordered on insanity. Raised to value humility, and unable to even speak up for myself, it was a level of

en-gb

9:31

“Reporting Tasks as Reward-Hackable: Better Than...

LessWrong (30+ Karma) ·

2026/02/22

Epistemic status: untested but seems plausible TL;DR: making honesty the best policy during RL reasoning training Reward hacking during Reinforcement Learning (RL) reasoning training[1] in insecure or poorly-judged training environments not only allows the model to cheat on tasks rather than learning to solve them, and teaches the model to try to cheat on tasks given to it (evidently not desirable behavior from an end-user/capabilities point of view), but it also damages the model's alignment,

en-gb

3,496 results

LessWrong (30+ Karma)

All Episodes

Similar Podcasts

Lead With AI

Tamara Nall

Linux in the Ham Shack

Black Sparrow Media

Data Engineering Podcast

Tobias Macey

Eye On A.I.

Craig S. Smith

Reflections

Livewire Labs