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    Technology

    LessWrong (Curated & Popular)

    Audio narrations of LessWrong posts. Includes all curated posts and all posts with 125+ karma.

    If you’d like more, subscribe to the “Lesswrong (30+ karma)” feed.

    Advertise

    Copyright: © 2023 LessWrong Curated Podcast

    • Apple Podcasts
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    Latest Episodes:
    “How I Learned To Stop Trusting Prediction Markets and Love the Arbitrage” by orthonormal Aug 08, 2024
    Show notes

    This is a story about a flawed Manifold market, about how easy it is to buy significant objective-sounding publicity for your preferred politics, and about why I've downgraded my respect for all but the largest prediction markets.
    I've had a Manifold account for a while, but I didn't use it much until I saw and became irked by this market on the conditional probabilities of a Harris victory, split by VP pick.
    Jeb Bush? Really? That's not even a fun kind of wishful thinking for anyone. Please clap.The market quickly got cited by rat-adjacent folks on Twitter like Matt Yglesias, because the question it purports to answer is enormously important. But as you can infer from the above, it has a major issue that makes it nigh-useless: for a candidate whom you know won't be chosen, there is literally no way to come out ahead on mana (Manifold keeps [...]
    The original text contained 1 image which was described by AI.
    ---
    First published:
    August 6th, 2024
    Source:
    https://www.lesswrong.com/posts/awKbxtfFAfu7xDXdQ/how-i-learned-to-stop-trusting-prediction-markets-and-love
    ---
    Narrated by TYPE III AUDIO.
    ---

    Images from the article:
    undefinedundefinedApple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    “This is already your second chance” by Malmesbury Aug 07, 2024
    Show notes

    Cross-posted from Substack.
    1.
    And the sky opened, and from the celestial firmament descended a cube of ivory the size of a skyscraper, lifted by ten thousand cherubim and seraphim. And the cube slowly landed among the children of men, crushing the frail metal beams of the Golden Gate Bridge under its supernatural weight. On its surface were inscribed the secret instructions that would allow humanity to escape the imminent AI apocalypse. And these instructions were…

    1. On July 30th, 2024: print a portrait of Eliezer Yudkowsky and stick it on a wall near 14 F St NW, Washington DC, USA;
    2. On July 31th, 2024: tie paperclips together in a chain and wrap it around a pole in the Hobby Club Gnome Village on Broekveg 105, Veldhoven, NL;
    3. On August 1st, 2024: walk East to West along Waverley St, Palo Alto, CA, USA while wearing an AI-safety related T-shirt;
    4. ---
      First published:
      July 28th, 2024
      Source:
      https://www.lesswrong.com/posts/BgTsxMq5bgzKTLsLA/this-is-already-your-second-chance
      ---
      Narrated by TYPE III AUDIO.

    “0. CAST: Corrigibility as Singular Target” by Max Harms Aug 07, 2024
    Show notes

    Crossposted from the AI Alignment Forum. May contain more technical jargon than usual.What the heck is up with “corrigibility”? For most of my career, I had a sense that it was a grab-bag of properties that seemed nice in theory but hard to get in practice, perhaps due to being incompatible with agency.
    Then, last year, I spent some time revisiting my perspective, and I concluded that I had been deeply confused by what corrigibility even was. I now think that corrigibility is a single, intuitive property, which people can learn to emulate without too much work and which is deeply compatible with agency. Furthermore, I expect that even with prosaic training methods, there's some chance of winding up with an AI agent that's inclined to become more corrigible over time, rather than less (as long as the people who built it understand corrigibility and want that agent [...]
    ---
    Outline:
    (07:30) Overview
    (07:33) 1. The CAST Strategy
    (08:15) 2. Corrigibility Intuition (Coming Saturday)
    (08:49) 3a. Towards Formal Corrigibility (Coming Sunday)
    (09:27) 3. Formal (Faux) Corrigibility ← the mathy one (Also Sunday)
    (10:12) 4. Existing Writing on Corrigibility (Coming Monday)
    (10:33) 5. Open Corrigibility Questions (Also Monday)
    (10:58) Bibliography and Miscellany
    ---
    First published:
    June 7th, 2024
    Source:
    https://www.lesswrong.com/posts/NQK8KHSrZRF5erTba/0-cast-corrigibility-as-singular-target-1
    ---
    Narrated by TYPE III AUDIO.


    “Self-Other Overlap: A Neglected Approach to AI Alignment” by Marc Carauleanu, Mike Vaiana, Judd Rosenblatt, Diogo de Lucena Aug 07, 2024
    Show notes

    Figure 1. Image generated by DALL-3 to represent the concept of self-other overlapMany thanks to Bogdan Ionut-Cirstea, Steve Byrnes, Gunnar Zarnacke, Jack Foxabbott and Seong Hah Cho for critical comments and feedback on earlier and ongoing versions of this work.
    Summary
    In this post, we introduce self-other overlap training: optimizing for similar internal representations when the model reasons about itself and others while preserving performance. There is a large body of evidence suggesting that neural self-other overlap is connected to pro-sociality in humans and we argue that there are more fundamental reasons to believe this prior is relevant for AI Alignment. We argue that self-other overlap is a scalable and general alignment technique that requires little interpretability and has low capabilities externalities. We also share an early experiment of how fine-tuning a deceptive policy with self-other overlap reduces deceptive behavior in a simple RL environment. On top of that [...]
    The original text contained 1 footnote which was omitted from this narration.
    ---
    First published:
    July 30th, 2024
    Source:
    https://www.lesswrong.com/posts/hzt9gHpNwA2oHtwKX/self-other-overlap-a-neglected-approach-to-ai-alignment
    ---
    Narrated by TYPE III AUDIO.
    ---

    Images from the article:
    undefinedundefinedundefinedundefinedundefined

    “You don’t know how bad most things are nor precisely how they’re bad.” by Solenoid_Entity Aug 07, 2024
    Show notes

    TL;DR: Your discernment in a subject often improves as you dedicate time and attention to that subject. The space of possible subjects is huge, so on average your discernment is terrible, relative to what it could be. This is a serious problem if you create a machine that does everyone's job for them.
    See also: Reality has a surprising amount of detail. (You lack awareness of how bad your staircase is and precisely how your staircase is bad.) You don't know what you don't know. You forget your own blind spots, shortly after you notice them.
    An afternoon with a piano tuner
    I recently played in an orchestra, as a violinist accompanying a piano soloist who was playing a concerto. My 'stand partner' (the person I was sitting next to) has a day job as a piano tuner.
    I loved the rehearsal, and heard nothing at all wrong with [...]
    ---
    Outline:
    (00:42) An afternoon with a piano tuner
    (02:56) Hear how it rolls over?
    (03:43) Are any of these notes brighter than others?
    (04:31) Yeah the beats get slower, but they dont get slower at an even rate...
    (05:19) This string probably has some rust on it somewhere.
    (06:55) Please at least listen to this guy when you create a robotic piano tuner and put him out of business.
    ---
    First published:
    August 4th, 2024
    Source:
    https://www.lesswrong.com/posts/PJu2HhKsyTEJMxS9a/you-don-t-know-how-bad-most-things-are-nor-precisely-how
    ---
    Narrated by TYPE III AUDIO.


    “Recommendation: reports on the search for missing hiker Bill Ewasko” by eukaryote Aug 07, 2024
    Show notes

    This is a link post.Content warning: About an IRL death.
    Today's post isn’t so much an essay as a recommendation for two bodies of work on the same topic: Tom Mahood's blog posts and Adam “KarmaFrog1” Marsland's videos on the 2010 disappearance of Bill Ewasko, who went for a day hike in Joshua Tree National Park and dropped out of contact.
    2010 – Bill Ewasko goes missing

    • Tom Mahood's writeups on the search [Blog post, website goes down sometimes so if the site doesn’t work, check the internet archive]
    2022 – Ewasko's body found
    • ADAM WALKS AROUND Ep. 47 "Ewasko's Last Trail (Part One)" [Youtube video]
    • ADAM WALKS AROUND Ep. 48 "Ewasko's Last Trail (Part Two)" [Youtube video]
    And then if you’re really interested, there's a little more info that Adam discusses from the coroner's report:
    • Bill Ewasko update (1 of 2): The Coroner's Report
    • Bill [...]
    ---
    Outline:
    (03:44) Unknowns and the missing persons case
    (05:47) How do you look for someone in the wilderness?
    (10:30) Making hindsight useful
    (12:05) How deep the search got
    (14:50) A hostile information environment
    (17:31) Maps and territories
    (20:04) Endings
    ---
    First published:
    July 31st, 2024
    Source:
    https://www.lesswrong.com/posts/fPh2zamuPpBAq2rgD/recommendation-reports-on-the-search-for-missing-hiker-bill
    ---
    Narrated by TYPE III AUDIO.
    ---
    Images from the article:
    undefinedundefinedundefinedundefined

    “The ‘strong’ feature hypothesis could be wrong” by lsgos Aug 07, 2024
    Show notes

    NB. I am on the Google Deepmind language model interpretability team. But the arguments/views in this post are my own, and shouldn't be read as a team position.
    “It would be very convenient if the individual neurons of artificial neural networks corresponded to cleanly interpretable features of the input. For example, in an “ideal” ImageNet classifier, each neuron would fire only in the presence of a specific visual feature, such as the color red, a left-facing curve, or a dog snout” : Elhage et. al, Toy Models of Superposition
    Recently, much attention in the field of mechanistic interpretability, which tries to explain the behavior of neural networks in terms of interactions between lower level components, has been focussed on extracting features from the representation space of a model. The predominant methodology for this has used variations on the sparse autoencoder, in a series of papers [...]
    ---
    Outline:
    (09:56) Monosemanticity
    (19:22) Explicit vs Tacit Representations.
    (26:27) Conclusions
    The original text contained 12 footnotes which were omitted from this narration.
    The original text contained 1 image which was described by AI.
    ---
    First published:
    August 2nd, 2024
    Source:
    https://www.lesswrong.com/posts/tojtPCCRpKLSHBdpn/the-strong-feature-hypothesis-could-be-wrong
    ---
    Narrated by TYPE III AUDIO.
    ---

    Images from the article:
    undefinedApple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    “‘AI achieves silver-medal standard solving International Mathematical Olympiad problems’” by gjm Jul 30, 2024
    Show notes

    This is a link post.Google DeepMind reports on a system for solving mathematical problems that allegedly is able to give complete solutions to four of the six problems on the 2024 IMO, putting it near the top of the silver-medal category.
    Well, actually, two systems for solving mathematical problems: AlphaProof, which is more general-purpose, and AlphaGeometry, which is specifically for geometry problems. (This is AlphaGeometry 2; they reported earlier this year on a previous version of AlphaGeometry.)
    AlphaProof works in the "obvious" way: an LLM generates candidate next steps which are checked using a formal proof-checking system, in this case Lean. One not-so-obvious thing, though: "The training loop was also applied during the contest, reinforcing proofs of self-generated variations of the contest problems until a full solution could be found."[EDITED to add:] Or maybe it doesn't work in the "obvious" way. As cubefox points out in the comments [...]
    ---
    First published:
    July 25th, 2024
    Source:
    https://www.lesswrong.com/posts/TyCdgpCfX7sfiobsH/ai-achieves-silver-medal-standard-solving-international
    ---
    Narrated by TYPE III AUDIO.


    “Decomposing Agency — capabilities without desires” by owencb, Raymond D Jul 29, 2024
    Show notes

    This is a link post.What is an agent? It's a slippery concept with no commonly accepted formal definition, but informally the concept seems to be useful. One angle on it is Dennett's Intentional Stance: we think of an entity as being an agent if we can more easily predict it by treating it as having some beliefs and desires which guide its actions. Examples include cats and countries, but the central case is humans.
    The world is shaped significantly by the choices agents make. What might agents look like in a world with advanced — and even superintelligent — AI? A natural approach for reasoning about this is to draw analogies from our central example. Picture what a really smart human might be like, and then try to figure out how it would be different if it were an AI. But this approach risks baking in subtle assumptions — [...]
    The original text contained 5 footnotes which were omitted from this narration.
    The original text contained 7 images which were described by AI.
    ---
    First published:
    July 11th, 2024
    Source:
    https://www.lesswrong.com/posts/jpGHShgevmmTqXHy5/decomposing-agency-capabilities-without-desires
    ---
    Narrated by TYPE III AUDIO.
    ---

    Images from the article:
    undefinedundefinedundefinedundefined

    “Universal Basic Income and Poverty” by Eliezer Yudkowsky Jul 27, 2024
    Show notes

    (Crossposted from Twitter)
    I'm skeptical that Universal Basic Income can get rid of grinding poverty, since somehow humanity's 100-fold productivity increase (since the days of agriculture) didn't eliminate poverty.
    Some of my friends reply, "What do you mean, poverty is still around? 'Poor' people today, in Western countries, have a lot to legitimately be miserable about, don't get me wrong; but they also have amounts of clothing and fabric that only rich merchants could afford a thousand years ago; they often own more than one pair of shoes; why, they even have cellphones, as not even an emperor of the olden days could have had at any price. They're relatively poor, sure, and they have a lot of things to be legitimately sad about. But in what sense is almost-anyone in a high-tech country 'poor' by the standards of a thousand years earlier? Maybe UBI works the same way [...]
    ---
    First published:
    July 26th, 2024
    Source:
    https://www.lesswrong.com/posts/fPvssZk3AoDzXwfwJ/universal-basic-income-and-poverty
    ---
    Narrated by TYPE III AUDIO.


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