Logan Riggs

Veo-2 Can Pro­duce Real­is­tic Ads

• Logan Riggs 21 Jan 2025 17:52 UTC

  2 points

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  in reply to: dabbing.’s comment on: [Ex­er­cise] Four Ex­am­ples of Notic­ing Confusion

  I didn’t either, but on reflection it is!

  I did change the post based off your comment, so thanks!

• Logan Riggs 19 Jan 2025 15:22 UTC

  2 points

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  in reply to: habryka’s comment on: Lo­gan Riggs’s Shortform

  I think the fuller context,

  Anthropic has put WAY more effort into safety, way way more effort into making sure there are really high standards for safety and that there isn’t going to be danger what these AIs are doing

  implies it’s just the amount of effort is larger than other companies (which I agree with), and not the Youtuber believing they’ve solved alignment or are doing enough, see:

  but he’s also a realist and is like “AI is going to really potentially fuck up our world”

  and

  But he’s very realistic. There is a lot of bad shit that is going to happen with AI. I’m not denying that at all.

  So I’m not confident that it’s “giving people a false impression of how good we are doing on actually making things safe.” in this case.

  I do know DougDoug has recommended Anthropic’s Alignment Faking paper to another youtuber, which is more of a “stating a problem” paper than saying they’ve solved it.

• Logan Riggs 19 Jan 2025 15:11 UTC

  2 points

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  in reply to: dabbing.’s comment on: [Ex­er­cise] Four Ex­am­ples of Notic­ing Confusion

  Did you listen to the song first?

• Logan Riggs 18 Jan 2025 21:17 UTC

  LW: 4 AF: 2

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  AF

  in reply to: TsviBT’s comment on: Thane Ruthe­nis’s Shortform

  Thinking through it more, Sox2-17 (they changed 17 amino acids from Sox2 gene) was your linked paper’s result, and Retro’s was a modified version of factors Sox AND KLF. Would be cool if these two results are complementary.

• Logan Riggs 18 Jan 2025 21:00 UTC

  LW: 4 AF: 2

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  in reply to: TsviBT’s comment on: Thane Ruthe­nis’s Shortform

  You’re right! Thanks
  For Mice, up to 77%

  Sox2-17 enhanced episomal OKS MEF reprogramming by a striking 150 times, giving rise to high-quality miPSCs that could generate all-iPSC mice with up to 77% efficiency

  For human cells, up to 9% (if I’m understanding this part correctly).
  

  SOX2-17 gave rise to 56 times more TRA1-60⁺ colonies compared with WT-SOX2: 8.9% versus 0.16% overall reprogramming efficiency.

  So seems like you can do wildly different depending on the setting (mice, humans, bovine, etc), and I don’t know what the Retro folks were doing, but does make their result less impressive.

• Logan Riggs 18 Jan 2025 20:39 UTC

  2 points

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  in reply to: quila’s comment on: [Ex­er­cise] Four Ex­am­ples of Notic­ing Confusion

  You’re actually right that this is due to meditation for me. AFAIK, it’s not a synesthesia-esque though (ie I’m not causing there to be two qualia now), more like the distinction between mental-qualia and bodily-qualia doesn’t seem meaningful upon inspection.

  So I believe it’s a semantic issue, and I really mean “confusion is qualia you can notice and act on” (though I agree I’m using “bodily” in non-standard ways and should stop when communicating w/​ non-meditators).

• Logan Riggs 18 Jan 2025 20:29 UTC

  2 points

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  in reply to: jbash’s comment on: [Ex­er­cise] Four Ex­am­ples of Notic­ing Confusion

  This is great feedback, thanks! I added another example based off what you said.

  For how obvious the first one, at least two folks I asked (not from this community) didn’t think it was a baby initially (though one is non-native english and didn’t know “2 birds of a feather” and assumed “our company” meant “the singers and their partner”). Neither are parents.
  
  I did select these because they caused confusion in myself when I heard/​saw them years ago, but they were “in the wild” instead of in a post on noticing confusion.
  
  I did want a post I could link [non rationalist friends] to that’s a more fun intro to noticing confusion, so more regular members might not benefit!

[Ex­er­cise] Four Ex­am­ples of Notic­ing Confusion

• Logan Riggs 18 Jan 2025 2:33 UTC

  LW: 5 AF: 3

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  AF

  in reply to: Thane Ruthenis’s comment on: Thane Ruthe­nis’s Shortform

  For those also curious, Yamanaka factors are specific genes that turn specialized cells (e.g. skin, hair) into induced pluripotent stem cells (iPSCs) which can turn into any other type of cell.
  
  This is a big deal because you can generate lots of stem cells to make full organs^[1] or reverse aging (maybe? they say you just turn the cell back younger, not all the way to stem cells).
  
  You can also do better disease modeling/​drug testing: if you get skin cells from someone w/​ a genetic kidney disease, you can turn those cells into the iPSCs, then into kidney cells which will exhibit the same kidney disease because it’s genetic. You can then better understand how the [kidney disease] develops and how various drugs affect it.
  
  So, it’s good to have ways to produce lots of these iPSCs. According to the article, SOTA was <1% of cells converted into iPSCs, whereas the GPT suggestions caused a 50x improvement to 33% of cells converted. That’s quite huge!, so hopefully this result gets verified. I would guess this is true and still a big deal, but concurrent work got similar results.

  Too bad about the tumors. Turns out iPSCs are so good at turning into other cells, that they can turn into infinite cells (ie cancer). iPSCs were used to fix spinal cord injuries (in mice) which looked successful for 112 days, but then a follow up study said [a different set of mice also w/​ spinal iPSCs] resulted in tumors.
  
  My current understanding is this is caused by the method of delivering these genes (ie the Yamanaka factors) through retrovirus which

  is a virus that uses RNA as its genomic material. Upon infection with a retrovirus, a cell converts the retroviral RNA into DNA, which in turn is inserted into the DNA of the host cell.

  which I’d guess this is the method the Retro Biosciences uses.
  
  I also really loved the story of how Yamanaka discovered iPSCs:

  Induced pluripotent stem cells were first generated by Shinya Yamanaka and Kazutoshi Takahashi at Kyoto University, Japan, in 2006.^[1] They hypothesized that genes important to embryonic stem cell (ESC) function might be able to induce an embryonic state in adult cells. They chose twenty-four genes previously identified as important in ESCs and used retroviruses to deliver these genes to mouse fibroblasts. The fibroblasts were engineered so that any cells reactivating the ESC-specific gene, Fbx15, could be isolated using antibiotic selection.

  Upon delivery of all twenty-four factors, ESC-like colonies emerged that reactivated the Fbx15 reporter and could propagate indefinitely. To identify the genes necessary for reprogramming, the researchers removed one factor at a time from the pool of twenty-four. By this process, they identified four factors, Oct4, Sox2, cMyc, and Klf4, which were each necessary and together sufficient to generate ESC-like colonies under selection for reactivation of Fbx15.

  1. ^

     These organs would have the same genetics as the person who supplied the [skin/​hair cells] so risk of rejection would be lower (I think)

• Logan Riggs 16 Jan 2025 12:49 UTC

  7 points

  0

  on: Lo­gan Riggs’s Shortform

  A trending youtube video w/​ 500k views in a day brings up Dario Amodei’s Machines of Loving Grace (Timestamp for the quote):
  [Note: I had Claude help format, but personally verified the text’s faithfulness]

  I am an AI optimist. I think our world will be better because of AI. One of the best expressions of that I’ve seen is this blog post by Dario Amodei, who is the CEO of Anthropic, one of the biggest AI companies. I would really recommend reading this—it’s one of the more interesting articles and arguments I have read. He’s basically saying AI is going to have an incredibly positive impact, but he’s also a realist and is like “AI is going to really potentially fuck up our world”
  
  He’s notable and more trustworthy because his company Anthropic has put WAY more effort into safety, way way more effort into making sure there are really high standards for safety and that there isn’t going to be danger what these AIs are doing. So I really really like Dario and I’ve listened to a lot of what he’s said. Whereas with some other AI leaders like Sam Altman who runs OpenAI, you don’t know what the fuck he’s thinking. I really like [Dario] - he also has an interesting background in biological work and biotech, so he’s not just some tech-bro; he’s a bio-tech-bro. But his background is very interesting.
  
  But he’s very realistic. There is a lot of bad shit that is going to happen with AI. I’m not denying that at all. It’s about how we maximize the positive while reducing the negatives. I really want AI to solve all of our diseases. I would really like AI to fix cancer—I think that will happen in our lifetimes. To me, I’d rather we fight towards that future rather than say ‘there will be problems, let’s abandon the whole thing.’

  Other notes: This is youtuber/​Streamer DougDoug (2.8M subscribers), with this video posted on his other channel DougDougDoug (“DougDoug content that’s too rotten for the main channel”) who often streams/​posts coding/​AI integrated content.
  
  The full video is also an entertaining summary of case law on AI generated art/​text copyright.

How do you deal w/​ Su­per Stim­uli?

• Logan Riggs 6 Jan 2025 14:38 UTC

  3 points

  0

  on: Speedrun­ning Ra­tion­al­ity: Day II

  Hey Midius!

  My recommended rationality habit is noticing confusion, by which I mean a specific mental feeling that’s usually quick & subtle & easy to ignore.

  David Chapman has a more wooey version called Eating Your Shadow, which was very helpful for me since it pointed me towards acknowledging parts of my experience that I was denying due to identity & social reasons (hence the easy to ignore part).

• Logan Riggs 28 Dec 2024 2:07 UTC

  4 points

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  in reply to: Chris_Leong’s comment on: When AI 10x’s AI R&D, What Do We Do?

  Could you go into more details into what skills these advisers would have or what situations to navigate?
  
  Because I’m baking in the “superhuman in coding/​maths” due to the structure of those tasks, and other tasks can either be improved through:
  1. general capabilies
  2. Specific task
  
  And there might be ways to differentially accelarate that capability.

• Logan Riggs 22 Dec 2024 15:19 UTC

  9 points

  2

  on: What o3 Be­comes by 2028

  I really appreciate your post and all the links! This and your other recent posts/​comments have really helped make a clearer model of timelines.

• Logan Riggs 22 Dec 2024 12:28 UTC

  6 points

  2

  in reply to: keltan’s comment on: keltan’s Shortform

  In my experience, most of the general public will verbally agree that AI X-risk is a big deal, but then go about their day (cause reasonably, they have no power). There’s no obvious social role/​action to do in response to that.

  For climate, people understand that they should recycle, not keep the water running, and if there’s a way to donate to clean the ocean on a Mr. Beast video, then some will even donate (sadly, none of these are very effective for solving the climate problem though! Gotta avoid that for our case).

  Having a clear call-to-action seems relevant. For example, educating the public about AI taking jobs for the purpose of building support for UBI. It’s then clear what to communicate and the call-to-action.

  I’d be curious to hear what you think an ask should be?

  Alternatively, you could argue that generally informing folks on a wide scale about the risks involved will then allow general public to do what they believe is locally best. This could involve a documentary or realistic movie.

• Logan Riggs 22 Dec 2024 12:08 UTC

  2 points

  0

  in reply to: Karl Krueger’s comment on: Karl Krueger’s Shortform

  Claude 3.5 seems to understand the spirit of the law when pursuing a goal X.

  A concern I have is that future training procedures will incentivize more consequential reasoning (because those get higher reward). This might be obvious or foreseeable, but could be missed/​ignored under racing pressure or when lab’s LLMs are implementing all the details of research.

• Logan Riggs 22 Dec 2024 11:48 UTC

  5 points

  0

  in reply to: CBiddulph’s comment on: When AI 10x’s AI R&D, What Do We Do?

  Thanks!

  I forgot about faithful CoT and definitely think that should be a “Step 0”. I’m also concerned here that AGI labs just don’t do the reasonable things (ie training for briefness making the CoT more steganographic).

  For Mech-interp, ya, we’re currently bottlenecked by:

  1. Finding a good enough unit-of-computation (which would enable most of the higher-guarantee research)

  2. Computing Attention_in--> Attention_out (which Keith got the QK-circuit → Attention pattern working a while ago, but haven’t hooked up w/​ the OV-circuit)

• Logan Riggs 21 Dec 2024 23:58 UTC

  22 points

  4

  on: When AI 10x’s AI R&D, What Do We Do?

  This is mostly a “reeling from o3”-post. If anyone is doom/​anxiety-reading these posts, well, I’ve been doing that too! At least, we’re in this together:)

When AI 10x’s AI R&D, What Do We Do?