Building gears-level models is expensive - often prohibitively expensive. Black-box approaches are usually cheaper and faster. But black-box approaches rarely generalize - they need to be rebuilt when conditions change, don’t identify unknown unknowns, and are hard to build on top of. Gears-level models, on the other hand, offer permanent, generalizable knowledge which can be applied to many problems in the future, even if conditions shift.
With the end of the world nigh, and a public panic about to start, this seems an ideal time to worry about weight loss and the obesity epidemic.
Coincidentally, for the first time in my life, I'm getting fat.
SlimeMoldTimeMold's 'Chemical Hunger' series
https://slimemoldtimemold.com/2021/07/07/a-chemical-hunger-part-i-mysteries/
seemed to draw a lot of interest round these parts, and even if it's not lithium
https://www.lesswrong.com/posts/7iAABhWpcGeP5e6SB/it-s-probably-not-lithium
it does seem to me that the molds raise some most interesting questions.
I find the whole 'seed oil' craziness to be a compellingly interesting argument, although, as Scott Alexander wrote:
https://slatestarcodex.com/2020/03/10/for-then-against-high-saturated-fat-diets/
it does seem to be flat wrong. But I think it's important to be interested in ideas that look like they have to be right but aren't.
I want to draw everyone's attention to the 'Experimental Fat Loss' substack
https://exfatloss.substack.com
Which seems to me the very...
You may be interested in the what Tucker Goodrich is doing, he's been reviewing the literature, and it's probably the Linoleic acid. He's pointed at the research on the direct stimulation of the endocanabinoid system by omega6. He's interviewed someone who studied Tributyl tin, an obesogen present at relevant doses in all of our environments, it also happens to agonize the same receptors omega6s do, and also has canabinoid activity.
Imagine trying to lose weight while smoking weed all day every day.
Say you want to plot some data. You could just plot it by itself:
Or you could put lines on the left and bottom:
Or you could put lines everywhere:
Or you could be weird:
Which is right? Many people treat this as an aesthetic choice. But I’d like to suggest an unambiguous rule.
First, try to accept that all axis lines are optional. I promise that readers will recognize a plot even without lines around it.
So consider these plots:
Which is better? I claim this depends on what you’re plotting. To answer, mentally picture these arrows:
Now, ask yourself, are the lengths of these arrows meaningful? When you draw that horizontal line, you invite people to compare those lengths.
You use the same principle for deciding if you should draw a y-axis line. As...
Lex Fridman posts timestamped transcripts of his interviews. It's an 83 minute read here and a 115 minute watch on Youtube.
It's neat to see Altman's side of the story. I don't know whether his charisma is more like +2SD or +5SD above the average American (concept origin: planecrash, likely doesn't follow a normal distribution), and I only have a vague grasp of what kinds of shenanigans +5SDish types can do when they pull out the stops in face-to-face interactions, so maybe you'll prefer to read the transcript over watching the video (although they're largely related to reading and responding to your facial expression and body language on the fly, not projecting their own).
If you've missed it, Gwern's side of the story is here.
...Lex Fridman(00:01:05) Take me through
Ah, neat, thanks! I had never heard of that paper or the Conger-Kanungo scale, when I referred to charisma I intended it in the planecrash sense of charisma that's focused on social dominance and subterfuge, rather than business management which is focused on leadership and maintaining the status quo which means something completely different and which I had never heard of. I was also using the terminology common to planecrash and planecrash-focused forums (+x SD).
I'm looking for computer games that involve strategy, resource management, hidden information, and management of "value of information" (i.e. figuring out when to explore or exploit), which:
This is for my broader project of "have a battery of exercises that train/test people's general reasoning on openended problems." Each exercise should ideally be pretty different from the other ones.
In this case, I don't expect anyone to have such a game that they have beaten on their first try, but, I'm looking for games where this seems at least plausible, if you were taking a long time to think each turn, or pausing a lot.
The strategy/resource/value-of-information aspect is meant to correspond to some real world difficulties of running longterm ambitious planning.
(One example game that's been given to me in this category is "Luck Be a Landlord")
Some concepts that I use:
Randomness is when the game tree branches according to some probability distribution specified by the rules of the game. Examples: rolling a die; cutting a deck at a random card.
Slay the Spire has randomness; Chess doesn't.
Hidden Information is when some variable that you can't directly observe influences the evolution of the game. Examples: a card in an opponent's hand, which they can see but you can't; the 3 solution cards set aside at the start of a game of Clue; the winning pattern in a game of Mastermind.
Peop...
Is the era of AI agents writing complex code systems without humans in the loop upon us?
Cognition is calling Devin ‘the first AI software engineer.’
Here is a two minute demo of Devin benchmarking LLM performance.
Devin has its own web browser, which it uses to pull up documentation.
Devin has its own code editor.
Devin has its own command line.
Devin uses debugging print statements and uses the log to fix bugs.
Devin builds and deploys entire stylized websites without even being directly asked.
What could possibly go wrong? Install this on your computer today.
Padme.
I would by default assume all demos were supremely cherry-picked. My only disagreement with Austen Allred’s statement here is that this rule is not new:
...Austen Allred: New rule:
If someone only shows their AI model in tightly
Is Devin using GPT-4, GPT-4T, or one of the 2 currently available long context models, Claude Opus 200k or Gemini 1.5?
March 14, 2023 is GPT-4, but the "long" context was expensive and initially unavailable to anyone
Reason that matters is November 6, 2023 is the announcement for GPT-4T, which is 128k context.
Feb 15, 2024 is Gemini 1.5 LC
March 4, 2024 is Claude 200k is
That makes the timeline less than 4 months, and remember there's a few weeks generally between "announcement" and "here's your opportunity to pay for tokens with an API key"...
Meet inside The Shops at Waterloo Town Square - we will congregate in the seating area next to the Valu-Mart with the trees sticking out in the middle of the benches at 7pm for 15 minutes, and then head over to my nearby apartment's amenity room. If you've been around a few times, feel free to meet up at my apartment front door for 7:30 instead. (There is free city parking at Bridgeport and Regina, 22 Bridgeport Rd E.)
A KWR member is going to teach the rest of us some sleight of hand tricks! Just show up.
Thanks to Rohin Shah, Ajeya Cotra, Richard Ngo, Paul Christiano, Jon Uesato, Kate Woolverton, Beth Barnes, and William Saunders for helpful comments and feedback.
Evaluating proposals for building safe advanced AI—and actually building any degree of confidence in their safety or lack thereof—is extremely difficult. Previously, in “An overview of 11 proposals for building safe advanced AI,” I tried evaluating such proposals on the axes of outer alignment, inner alignment, training competitiveness, and performance competitiveness. While I think that those criteria were good for posing open questions, they didn’t lend themselves well to actually helping us understand what assumptions needed to hold for any particular proposal to work. Furthermore, if you’ve read that paper/post, you’ll notice that those evaluation criteria don’t even work for some of the proposals...
Anyone -- and in particular Evhub -- have updated views on this post with the benefit of hindsight?
I intuitively don't like this approach, but I have trouble articulating exactly why. I've tried to explain a bit in this comment, but I don't think I'm quite saying the right thing.
One issue I have is that it doesn't seem to nicely handle interactions between the properties of the AI and how it's used. You can have an AI which is safe when used in some ways, but not always. This could be due to approaches like control (which mostly route around mechanistic...
Today, the AI Extinction Statement was released by the Center for AI Safety, a one-sentence statement jointly signed by a historic coalition of AI experts, professors, and tech leaders.
Geoffrey Hinton and Yoshua Bengio have signed, as have the CEOs of the major AGI labs–Sam Altman, Demis Hassabis, and Dario Amodei–as well as executives from Microsoft and Google (but notably not Meta).
The statement reads: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”
We hope this statement will bring AI x-risk further into the overton window and open up discussion around AI’s most severe risks. Given the growing number of experts and public figures who take risks from advanced AI seriously, we hope to improve epistemics by encouraging discussion and focusing public and international attention toward this issue.
That's a good example of my point. Instead of a petition, a more impactful document would be a survey of risks and their probability of occurring in the opinion of these notable public figures.
In addition, there should be a disclaimer regarding who has accepted money from Open Philanthropy or any other EA-affiliated non-profit for research.