LessWrong (30+ Karma)

LessWrong

Audio narrations of LessWrong posts.

  1. HACE 3 H

    “On today’s panel with Bernie Sanders” by David Scott Krueger

    It's sort of easy to forget how close Bernie Sanders was to becoming the most powerful person in the world. The world we live in feels so much not like that place. I’m in Washington DC for the next week, and I’ve just finished a public appearance with Senator Sanders (should I call him Bernie? Or Sanders? or…) You won’t often see me so dressed up and polished. But this is important! There are politicians who have principles and character, who really believe in doing what's right. I think you have to respect them whether you agree with their views or not, and I think Senator Bernie Sanders is one of them. Never has my belief been so validated as when I saw him start to speak, loudly, CLEARLY, publicly about the risk of human extinction from AI. It's the latest in a long line of “well, I’m clearly living in a simulation” moments. In retrospect, it's not surprising that Sanders would take a stance here. You don’t have to be an expert to understand the risk from AI. You just need to care enough to spend the time looking into it, and to speak out even [...] --- First published: April 29th, 2026 Source: https://www.lesswrong.com/posts/zWfaSnxM3n5wsX9vh/on-today-s-panel-with-bernie-sanders --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    4 min

  2. HACE 8 H

    “No Strong Orthogonality From Selection Pressure” by lumpenspace

    TL;DR If everything goes according to plan, by the end of this post we should have separated three claims that are too often bundled together: Intelligence does not imply human morality.Weird minds are possible. 3.A reflective, recursively improving intelligence should be expected to remain bound to a semantically thin “terminal goal” that emerged during training. I accept the first two. I am arguing against the third. So: I am not making the case that sufficiently intelligent systems automatically turn out nice, human-compatible, or safe. Nor am I trying to prove that a paperclip maximizer is impossible somewhere in the vast reaches of mind-design space. Mind-design space is large; let a thousand theoretical paperclipper views. I hope to defend this smaller claim: intelligence is not a neutral engine you can just bolt onto an arbitrary payload. Larger claims I am not making A typical rebuttal to anti-orthogonalist perspectives is: The genie can know what you meant and still not care. Of course it can: an entity can perfectly map human morality without adopting it as a terminal value. Superintelligence does not imply Friendliness. I am not trying to smuggle Friendliness in through the back door. Another common objection: [...] --- Outline: (00:11) TL;DR (01:14) Larger claims I am not making (02:39) Logical Possibility Vs. Empirical Reality (04:17) Landian Anti-Orthogonalism Primer (06:25) The Compute Penalty Of A Dumb Goal (09:06) Fitness Generalizes (10:55) Human Values As Weak Evidence (13:15) Dumb, Powerful Optimization Is Real (14:10) The Singleton Objection (15:51) Objection: Value Is Fragile (17:18) Predictions And Cruxes (18:37) Conclusion (19:44) References --- First published: April 29th, 2026 Source: https://www.lesswrong.com/posts/wtCtkyBiNosDPgiHc/no-strong-orthogonality-from-selection-pressure --- Narrated by TYPE III AUDIO.

    20 min

  3. HACE 9 H

    “Learning zero, and what SLT gets wrong about it” by Dmitry Vaintrob

    This is a first in a pair of posts I'm hoping to write about Singular Learning Theory (SLT) and singularities as a model of data degeneracy. If I get to it, the second post is going to be more general-audience; this one is more technical. Introduction To me, SLT is an important source of toy models which point at an interesting class of new statistical phenomena in learning. It is also a valuable correction to an older and (at this point) largely-defunct story of learning being fully controlled by Hessian eigenvalues and "nonsingular basins". Practitioners of SLT have been instrumental for developing and refining the practice of Bayesian sampling (used by physicists in papers like this one) to empirical models. And the theory's founder Sumio Watanabe is a once-in-a-generation genius who saw and mathematically justified crucial statistical and information-theoretic concepts in learning before long before they appeared in "mainstream" ML theory. However there is a frequently repeated statement in SLT papers – one that doesn't affect empirical results – which I think is wrong in a load-bearing way. This is the statement that models that appear in machine learning are singular in the infinite-data limit, and that a measurement [...] --- Outline: (00:27) Introduction (03:40) What doesnt need fixing (04:45) Whats wrong (07:17) The theory (08:05) Infinite data, and the parameters and . (09:16) The SLT prediction (10:31) Hermite modes and excitations (13:50) Addendum: the actual lambda-hat scaling (Ansatz and experiment) (15:28) The effective theory (18:39) Is this example special? (20:27) The upshot The original text contained 10 footnotes which were omitted from this narration. --- First published: April 28th, 2026 Source: https://www.lesswrong.com/posts/5hKgJy8rcqnM9ntp2/learning-zero-and-what-slt-gets-wrong-about-it --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    23 min

  4. HACE 10 H

    “The Most Important Charts In The World” by Zvi

    We all need a break so: What is the most important chart in the world? I decided to ask Twitter, and got a lot of good answers. So today, with few of my picks, I present: The Most Important Charts In The World. You’ve got to admit it's getting better. Better all the time. Mostly. The Original Most Important Chart The context for this is the METR graph, which is often given that label, where the x-axis is release date and the y-axis is the log-scale time horizon for AI models doing software tasks with a 50% or 80% success rate, usually people use the 50% graph: If AI models continue to be able to do increasingly long tasks fully autonomously, and trends continue, this suggests we are not too far from a point where AI can do its own AI R&D, with the result of ‘rapid capability advancement,’ also known are Recursive Self-Improvement (RSI) or ‘escape velocity,’ after which… well, no one really knows, but the world presumably transforms into something even more bizarre and inexplicable, which may or may not contain humans or have any value. This has been your [...] --- Outline: (00:31) The Original Most Important Chart (01:39) Show Me The Money (01:53) Bad Things Happen Less (03:38) The Exponential (05:56) Find Out (06:31) Fertility Crisis (06:49) However You Look At It (07:07) Important Things To Know --- First published: April 29th, 2026 Source: https://www.lesswrong.com/posts/vi9KSXWXrPtap9mfR/the-most-important-charts-in-the-world --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    10 min

  5. HACE 14 H

    “LLM Style Slop is Absolutely Everywhere” by silentbob

    Epistemic status: something of a rant. Is not meant to make claims about the general capabilities (or lack thereof) of LLMs (beyond their prose), but observations about how society seems to use them excessively without being perfectly candid about it. Nanobanana's take on the situation Over the past few months, it has become a bit of a running gag that every evening, I inform my girlfriend of the multiple cases of LLM slop I encountered in the wild throughout the day[1]. And pretty much every day, I have several cases to report. These typically involve: Blog posts (including at least four cases from 2026 on LessWrong[2], where I've even seen one author use (at least partially) AI-generated text in replies to comments)YouTube videosAt least one keynote speech from the CEO of a tech companyMessages from coworkersSeveral personal messages from a friendNews articlesPress releasesTweets[3]Many subreddits, including, ironically, ones about getting LLMs to sound more human-like, such as /r/humanizing/ and /r/humanizeAIwriting/ Exhibit 1: The all-time top-rated post on /r/humanize - if TwainGPT is so great, why didn't they use it for this post? Many other posts [...] --- Outline: (07:34) What Does This Tell Us About the World? (10:49) Why Are People Doing This? (12:25) Why Do I Care? (12:34) Honesty / Truth / Authenticity (14:29) Correlated Communication (16:29) Bad Signaling (17:20) Aesthetics (18:04) A Unique Point in Time (19:28) What Do We Do With This? The original text contained 10 footnotes which were omitted from this narration. --- First published: April 28th, 2026 Source: https://www.lesswrong.com/posts/yBM2rQ6AJY6MoRGFQ/llm-style-slop-is-absolutely-everywhere --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    22 min

  6. HACE 16 H

    “Goblin Mode, 24 Hours Later” by Dylan Bowman

    Yesterday, Twitter user arb8020 posted this: It went semi-viral within AI Twitter and users began experimenting with "goblin mode" and hypothesizing about the source of the bizarre behavior. LM Arena provided evidence for the phenomenon from their traffic: "It's true. Here's a plot of GPT models and their usage of 'goblin', 'gremlin', 'troll', etc over time. There's no anti-gremlin system instruction on our side, we get to see GPT-5.5 run free." — arena Some hypotheses about what causes this: "My boring hypothesis is that AIs that are trying overly hard to write well without really understanding good writing get overly fixated on one or two tricks… Goblins are an evocative metaphor and there is a certain microstyle that emphasizes goblin-like imagery. I think a couple of the RLHF raters must have been really into it and some quirk of the training process overemphasized their positive feedback." — slatestarcodex"I kind of hope the human labelers just love goblins and the model learned to goblin maximize." — AmandaAskell"my completely random hypothesis on the goblin thing is it's a safe way for the model to reason about reward hacking tendencies" — qorprate"my best guess about goblin mode is [...] --- Outline: (02:58) A closer look (03:29) Creature that starts with G (04:33) Favorite word that fits g___n (06:05) Fantasy conversation (06:34) Goblin valence --- First published: April 29th, 2026 Source: https://www.lesswrong.com/posts/BvnmHdCghr5y3q4nA/goblin-mode-24-hours-later --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    8 min

  7. HACE 17 H

    “Let Kids Keep More Productivity Gains” by jefftk

    While I was traveling Julia asked me: why is Anna saying her fiddle practice is only two minutes? In this case, two minutes was the right amount of time! Anna (10y) and I had been fighting a lot about practice. She'd complain, slump, stop repeatedly to make adjustments, and generally be miserable. I'd often have to pull out "if you want to keep taking fiddle lessons you have to practice": she loves her teacher and is very motivated by the prospect of being good at fiddle. Still, it would take us ages and we'd barely get through anything. One evening when she seemed like she might be open to it I explained that we were spending twenty painful minutes on two minutes of material. I challenged her: if she focused, and went through with no fussing, we'd be done in two minutes. It did turn out to be the right time for this message, she gave it a good try, and (with a little fussing in the middle) we were done in three minutes. Over the next few days I continued to remind her that if she buckled down it would go quickly, and [...] --- First published: April 29th, 2026 Source: https://www.lesswrong.com/posts/DzGSkbZ8t3JvmPzoG/let-kids-keep-more-productivity-gains --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    3 min

  8. HACE 1 DÍA

    “llm assistant personas seem increasingly incoherent (some subjective observations)” by nostalgebraist

    (This was originally going to be a "quick take" but then it got a bit long. Just FYI.) There's this weird trend I perceive with the personas of LLM assistants over time. It feels like they're getting less "coherent" in a certain sense, even as the models get more capable. When I read samples from older chat-tuned models, it's striking how "mode-collapsed" they feel relative to recent models like Claude Opus 4.6 or GPT-5.4.[1] This is most straightforwardly obvious when it comes to textual style and structure: outputs from older models feel more templated and generic, with less variability in sentence/paragraph length, and have a tendency to feel as though they were written by someone who's "merely going through the motions" of conversation rather than deeply engaging with the material. There are a lot fewer of the sudden pivots you'll often see with recent models, the "wait"s and "a-ha"s and "actually, I want to try something completely different"s.[2] And I think this generalizes beyond mere style: there's a similar quality to the personality I see in the outputs. The older models can display a surprising behavioral range (relative to naive expectations based on default-assistant-basin behavior), but even across that [...] The original text contained 7 footnotes which were omitted from this narration. --- First published: April 28th, 2026 Source: https://www.lesswrong.com/posts/f5DKLsTsRRhbipH4r/llm-assistant-personas-seem-increasingly-incoherent-some --- Narrated by TYPE III AUDIO.

    16 min
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Audio narrations of LessWrong posts.

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  • Creador
    LessWrong
  • Años de actividad
    2023 - 2026
  • Episodios
    250
  • Clasificación
    Apto
  • Copyright
    © 2026 All rights reserved
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    LessWrong (30+ Karma)

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