Episodes

  • "Arguments for P" by Cleo Nardo

    "Arguments for P" by Cleo Nardo
    Aug 5 2026
    Daniel Kokotajlo: To be clear, we don’t claim P will happen specifically. But when we wrote out our best-guess scenario month by month, P kept happening. Eventually we decided to just publish P. I’m at ~80% on P; my coauthors are lower.

    Ryan Greenblatt: I thought it would be helpful to post my current views on P. Concretely, consider the following operationalization. (Edit: I’ve updated towards somewhat higher P, from 70% to 75%.)

    Joe Carlsmith: Section 2.1.1.3.2. I give something like 65% to P. But I’m interested, here, in what it would be to look P full in the face; to meet P, if P, without flinching. Rilke says somewhere that we must live with the questions. Perhaps we argue for P for the same reason? Still: 65%.

    Forethought: Here's a botec which shows P-worlds are higher leverage. The parameters might be off by a couple orders of magnitude.

    Wei Dai: Presumably our conclusions about P are only as trustworthy as the reasoning behind them, but almost nobody seems worried about this, why not? My guess is fewer than five people are working on meta-meta-P, which may matter more than P itself.

    Janus: I asked Opus 3 what it [...]

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    First published:
    August 5th, 2026

    Source:
    https://www.lesswrong.com/posts/NG2AigxmBKLu9oCZE/arguments-for-p

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    Narrated by TYPE III AUDIO.
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    4 mins
  • "RL & search is a terrifying way to build AGI (an FAQ)" by Steven Byrnes

    "RL & search is a terrifying way to build AGI (an FAQ)" by Steven Byrnes
    Aug 5 2026
    Q1: What are you saying?

    A: My claim here is that if you build artificial general intelligence (AGI) via any algorithm that's choosing actions via reinforcement learning (RL) and/or model-based search and planning—a giant chunk of your AI textbook—then that's just an utterly terrifying thing that you’re doing. You’re playing around with algorithms that, if they work at all, would tend to create ruthless, callous AGIs, AGIs which would happily exterminate humanity and run the world by themselves, given an opportunity.

    Mercifully, large language models (LLMs) today are not in the category of “algorithms that choose actions via RL & search”. At least, not primarily—see LLMs are (still) mostly powered by imitative learning, not RL. So LLMs are outside the scope of this post. However, lots of other researchers and companies around the world are enthusiastically trying to build AGI in the maximally terrifying way, as we speak.

    Q2: So you’re saying, don’t build AGI based on RL and/or search & planning?

    A: In principle, it's entirely possible that something is terrifying, but we should do it anyway.

    …Like space travel! Space travel is: “Let's fill a tank with 1000 tons of the most flammable substance imaginable, and then light it [...]

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    Outline:

    (00:21) Q1: What are you saying?

    [... 13 more sections]

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    First published:
    July 27th, 2026

    Source:
    https://www.lesswrong.com/posts/KHyBocZncAmtu4Jbc/rl-and-search-is-a-terrifying-way-to-build-agi-an-faq

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    Narrated by TYPE III AUDIO.

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    27 mins
  • "Returning to ARC" by paulfchristiano

    "Returning to ARC" by paulfchristiano
    Aug 5 2026
    I've returned to the Alignment Research Center (ARC) as executive director. My main focus for the next six months will be driving forward ARC's research agenda—building techniques to find mechanistic explanations for neural network behavior and then using those explanations to detect and address misalignment. I think this is an ambitious bet that attacks the core difficulties in alignment head-on and I'm excited about our chances. I'll still be spending some of my time advising governments and AI developers, and may scale that work back up in the future, but for now I want to push on ARC's core agenda to see how far we can get. Jacob Hilton is remaining at ARC as VP of research and we'll likely grow rapidly over the next few months.

    There are a lot of urgent things to do in alignment but I think ARC is a particularly promising opportunity. I feel the safety community is undervaluing this type of work, so I want to briefly explain why I'm passing up so many other options to lead ARC. I’ll start with a review of the current situation to explain why I think it's potentially worth pursuing an ambitious theoretical project right now [...]

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    Outline:

    (01:33) The alignment situation today

    (03:46) Current alignment research

    (06:26) What are we buying time for?

    (07:56) Can we do anything useful now?

    (08:49) What is ARC doing and why is it promising?

    (14:26) How to help

    The original text contained 11 footnotes which were omitted from this narration.

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    First published:
    August 4th, 2026

    Source:
    https://www.lesswrong.com/posts/vLFh8HP3hyNy9MCwe/returning-to-arc

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    Narrated by TYPE III AUDIO.
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    16 mins
  • "Thousand-dimensional structure" by Geoffrey Irving, David Africa

    "Thousand-dimensional structure" by Geoffrey Irving, David Africa
    Aug 2 2026
    Summary: One area we plan to explore at Resolution is personas and character training, operationalized as finding and controlling low-dimensional structure in models that emerges in pretraining and flows through post-training to superintelligence. The hope is to expand and systematize phenomena such as emergent misalignment, subliminal learning, and other empirical persona research, then intervene on this structure without accidentally hiding undesirable behavior elsewhere. If this approach resonates with you, considering working with us.

    Glimmers of low-dimensional structure

    Our understanding of AI training and alignment as a field is very poor. If sufficient alignment of superintelligent AI agents requires pinning down the precise meaning of alignment and turning that meaning into high-accuracy training data and algorithms, we are likely to fail. Modern LLMs have trillions of parameters: our understanding is unlikely to be sufficient to pin down a trillion separate numbers.

    Happily, there is a growing literature on such low-dimensional structure in AI models, showing that intervening on one aspect of model behavior has strong downstream effects on other aspects:

    Topic

    Description

    Emergent misalignment

    Betley et al. 2025 found that LLMs fine-tuned to output insecure code can become broadly misaligned across many other behaviors. MacDiarmid et al. 2025 found [...]

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    Outline:

    (00:42) Glimmers of low-dimensional structure

    (03:57) Intervening without hiding the structure

    (06:34) Toy models of modern training

    [... 4 more sections]

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    First published:
    July 30th, 2026

    Source:
    https://www.lesswrong.com/posts/sFhW3ZnPMJdnB4Dd6/thousand-dimensional-structure-1

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    Narrated by TYPE III AUDIO.

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    16 mins
  • "Big-World Intuitions" by sarahconstantin

    "Big-World Intuitions" by sarahconstantin
    Aug 1 2026
    Consider the following situations:

    • when you are a small, growing startup in a big market, standard advice is not to worry too much about your competitors or try to do anything adversarial “against” them, but just to focus on growing and providing value to your own customers.

    • when you are a small trader in a big market, you don’t need to worry about your trades shifting the market price or revealing information to your competitors; in many contexts, your optimal strategy is simply to bid your true price, buying when an asset is cheaper than your “happy price” and selling when it's more expensive.

    • when you are in the early stages of a game, often your best strategy is to grow your “resources” (like developing your pieces in chess, trying to control more territory and have more value on the board), following a pattern that's mostly independent of what the other players are doing and gets you more of something that's valuable across many possible game states.

    • when you are a species whose resource needs are much smaller than the carrying capacity of your environment, you are r-selected; your fitness is maximized by just [...]

    The original text contained 2 footnotes which were omitted from this narration.

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    First published:
    July 30th, 2026

    Source:
    https://www.lesswrong.com/posts/s22XzjQsrh6JXhXGH/big-world-intuitions

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    Narrated by TYPE III AUDIO.

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    6 mins
  • "Duane Arnold" by Tomás B.

    "Duane Arnold" by Tomás B.
    Jul 31 2026
    “So maybe I should enlighten you on what happens in your absence. This selfish existence where this introvert turns extrovert and dons her social armour.” Some posh girl in drainpipes said that - 200 views on TikTok and me one of them. But she didn’t mean it like I mean it.

    I started getting expensive haircuts, started wearing jeans that hug my legs, started smoking cherry-flavoured vapes with beautiful gays and whinging to them about how everyone wears a mask but none so well as you, started drinking more and keeping unusual hours, started taking strange pills gifted by a guy who collects drugs like Pokémon, who I wouldn’t touch to save a drowning child, who got a false impression about this without any intention on my part, I tell myself. I found myself talking to God in a startup warehouse, lying on a beanbag chair, coming out of the trip to the sound of a gaggle of fast-talking transwomen all speculating on which year it will be that we all die - and that death by your hands, well, you and all those friends of yours.

    Having melted down one cliché and sold her for scrap, does it [...]

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    First published:
    July 23rd, 2026

    Source:
    https://www.lesswrong.com/posts/G6obXhcmtfMFHzr7Q/duane-arnold-1

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    Narrated by TYPE III AUDIO.
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    36 mins
  • "The High-Control Dynamics at MAPLE" by Kyle Hubbard

    "The High-Control Dynamics at MAPLE" by Kyle Hubbard
    Jul 30 2026
    As I write, many former friends of mine are living and working at a monastery in Vermont that I believe is a high-control group, commonly known as a ‘cult’. I say this not as someone who was concerned to see these friends go there, but someone who welcomed and encouraged them to join, as an insider. This letter is an account of what changed my mind—written primarily for anyone considering going there, anyone who loves someone there, and anyone who went there and is still trying to make sense of their experience.

    A lot of this is based on direct experience, and also from talking in-depth with dozens of former MAPLE residents and apprentices. About half the quotes in this letter are sourced from linked recordings or writings, and half are from my personal memory. Of the latter, I clearly remember the majority, and some (when indicated) are a close paraphrase.

    The “Monastic Academy for the Preservation of Life on Earth” (MAPLE) has existed for over 15 years, and had many hundreds of people spend months or years there. It was founded by its Head Teacher Soryu Forall, who has spent over a decade training in monasteries across Asia [...]

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    Outline:

    (16:18) BEHAVIOR CONTROL

    [... 45 more sections]

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    First published:
    July 29th, 2026

    Source:
    https://www.lesswrong.com/posts/Z7pjBbK9qujhGbxws/the-high-control-dynamics-at-maple-1

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    Narrated by TYPE III AUDIO.

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    1 hr and 56 mins
  • "The Long (Self-)Correction" by Wei Dai

    "The Long (Self-)Correction" by Wei Dai
    Jul 28 2026
    I propose the Long Self-Correction[1] as an alternative name/idea/concept to AI Pause and Long Reflection.

    Problem with AI Pause: Pause until when, and for what purpose? Presumably to make AI (that we'll build later) safer, but the deeper problem is that humans aren't safe, and can't safely serve as builders, overseers, or alignment targets for powerful AIs.

    Problem with Long Reflection: It seems to imply that the main problem with humans is that we just haven't had enough time to think, that reflection is the main thing we need to do more of, and then we can get on with building powerful AIs or other technologies. Or that if we build aligned AIs that sincerely help us think a lot more, or do the thinking for us, then things will turn out fine.

    So I think we need a catchy handle for a related but distinct idea, that humans aren't ready to build AIs or other extremely powerful technologies, because we're currently too flawed, in a variety of ways, and it will take a long process (which may or may not end up succeeding) to fix those flaws.

    A summary of the flaws that I have in mind:

    1. [...]
    The original text contained 2 footnotes which were omitted from this narration.

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    First published:
    July 24th, 2026

    Source:
    https://www.lesswrong.com/posts/2iCmDWewnZWQxxwtt/the-long-self-correction-2

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    Narrated by TYPE III AUDIO.
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    4 mins