All of Eliezer Yudkowsky's Comments + Replies
So if it's difficult to get amazing trustworthy work out of a machine actress playing an Eliezer-level intelligence doing a thousand years worth of thinking, your proposal to have AIs do our AI alignment homework fails on the first step, it sounds like?
I do not think that the initial humans at the start of the chain can "control" the Eliezers doing thousands of years of work in this manner (if you use control to mean "restrict the options of an AI system in such a way that it is incapable of acting in an unsafe manner")
That's because each step in the chain requires trust.
For N-month Eliezer to scale to 4N-month Eliezer, it first controls 2N-month Eliezer while it does 2 month tasks, but it trusts 2-Month Eliezer to create a 4N-month Eliezer.
So the control property is not maintained. But my argument is th...
So the "IQ 60 people controlling IQ 80 people controlling IQ 100 people controlling IQ 120 people controlling IQ 140 people until they're genuinely in charge and genuinely getting honest reports and genuinely getting great results in their control of a government" theory of alignment?
I'd replace "controlling" with "creating" but given this change, then yes, that's what I'm proposing.
I don't think you can train an actress to simulate me, successfully, without her going dangerous. I think that's over the threshold for where a mind starts reflecting on itself and pulling itself together.
I would not be surprised if the Eliezer simulators do go dangerous by default as you say.
But this is something we can study and work to avoid (which is what I view to be my main job)
My point is just that preventing the early Eliezers from "going dangerous" (by which I mean from "faking alignment") is the bulk of the problem humans need address (and insofar as we succeed, the hope is that future Eliezer sims will prevent their Eliezer successors from going dangerous too)
I'll discuss why I'm optimistic about the tractability of this problem in future posts.
I'm not saying that it's against thermodynamics to get behaviors you don't know how to verify. I'm asking what's the plan for getting them.
One of the most important projects in the world. Somebody should fund it.
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3At the end of 2023, MIRI had ~$19.8 mio. in assets. I don't know much about the legal restrictions of how that money could be used, or what the state for financial assets is now, but if it's similar then MIRI could comfortably fund Velychko's primate experiments, and potentially some additional smaller projects.
(Potentially relevant: I entered the last GWWC donor lottery with the hopes of donating the resulting money to intelligence enhancement, but wasn't selected.)
I think this project should receive more red-teaming before it gets funded.
Naively, it would seem that the "second species argument" matches much more strongly to the creation of a hypothetical Homo supersapiens than it does to AGI.
We've observed many warning shots regarding catastrophic human misalignment. The human alignment problem isn't easy. And "intelligence" seems to be a key part of the human alignment picture. Humans often lack respect or compassion for other animals that they deem intellectually inferior -- e.g. arguing that because those othe...
4Copying over Eliezer's top 3 most important projects from a tweet:
1. Avert all creation of superintelligence in the near and medium term.
2. Augment adult human intelligence.
3. Build superbabies.
Can you tl;dr how you go from "humans cannot tell which alignment arguments are good or bad" to "we justifiably trust the AI to report honest good alignment takes"? Like, not with a very large diagram full of complicated parts such that it's hard to spot where you've messed up. Just whatever simple principle you think lets you bypass GIGO.
Eg, suppose that in 2020 the Open Philanthropy Foundation would like to train an AI such that the AI would honestly say if the OpenPhil doctrine of "AGI in 2050" was based on groundless thinking ultimately dri...
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1Sure, I'll try.
I agree that you want AI agents to arrive at opinions that are more insightful and informed than your own. In particular, you want AI agents to arrive at conclusions that are at least as good as the best humans would if given lots of time to think and do work. So your AI agents need to ultimately generalize from some weak training signal you provide to much stronger behavior. As you say, the garbage-in-garbage-out approach of "train models to tell me what I want to hear" won't get you this.
Here's an alternative approach. I'll describe it in ...
the OpenPhil doctrine of "AGI in 2050"
(Obviously I'm biased here by being friends with Ajeya.) This is only tangentially related to the main point of the post, but I think you're really overstating how many Bayes points you get against Ajeya's timelines report. Ajeya gave 15% to AGI before 2036, with little of that in the first few years after her report; maybe she'd have said 10% between 2025 and 2036.
I don't think you've ever made concrete predictions publicly (which makes me think it's worse behavior for you to criticize people for their predictions), b...
You seem confused about my exact past position. I was arguing against EAs who were like, "We'll solve AGI with policy, therefore no doom." I am not presently a great optimist about the likelihood of policy being an easy solution. There is just nothing else left.
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1(I affirm this as my intended reading.)
It certainly bears upon AI, but it bears that way by making a point about the complexity of a task rather than talking about an intelligent mechanism which is purportedly aligned on that task. It does this by talking about an unintelligent mechanism, which is meant to be a way of talking about the task itself rather than any particular machine for doing it.
Your distinction between "outer alignment" and "inner alignment" is both ahistorical and unYudkowskian. It was invented years after this post was written, by someone who wasn't me; and though I've sometimes used the terms in occasions where they seem to fit unambiguously, it's not something I see as a clear ontological division, especially if you're talking about questions like "If we own the following kind of blackbox, would alignment get any easier?" which on my view breaks that ontology. So I strongly reject your frame that this post was "cl...
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1What this post is trying to illustrate is that if you try putting crisp physical predicates on reality, that won't work to say what you want. This point is true!
Matthew is not disputing this point, as far as I can tell.
Instead, he is trying to critique some version of[1] the "larger argument" (mentioned in the May 2024 update to this post) in which this point plays a role.
You have exhorted him several times to distinguish between that larger argument and the narrow point made by this post:
...[...] and if you think that some larger thing is not corr
The post is about the complexity of what needs to be gotten inside the AI. If you had a perfect blackbox that exactly evaluated the thing-that-needs-to-be-inside-the-AI, this could possibly simplify some particular approaches to alignment, that would still in fact be too hard because nobody has a way of getting an AI to point at anything. But it would not change the complexity of what needs to be moved inside the AI, which is the narrow point that this post is about; and if you think that some larger thing is not correct, you should not confuse...
1Wish there was a system where people could pay money to bid up what they believed were the "top arguments" that they wanted me to respond to. Possibly a system where I collect the money for writing a diligent response (albeit note that in this case I'd weigh the time-cost of responding as well as the bid for a response); but even aside from that, some way of canonizing what "people who care enough to spend money on that" think are the Super Best Arguments That I Should Definitely Respond To. As it stands, whatever I respond to, there's somebody...
157I do think such a system would be really valuable, and is the sort of the thing the LW team should try to build. (I'm mostly not going to respond to this idea right now but I've filed it away as something to revisit more seriously with Lightcone. Seems straightforwardly good)
But it feels slightly orthogonal to what I was trying to say. Let me try again.
(this is now official a tangent from the original point, but, feels important to me)
It would be good if the world could (deservedly) trust, that the best x-risk thinkers have a good group epistemic process f...
I note that I haven't said out loud, and should say out loud, that I endorse this history. Not every single line of it (see my other comment on why I reject verificationism) but on the whole, this is well-informed and well-applied.
5If you had to put a rough number on how likely it is that a misaligned superintelligence would primarily value "small molecular squiggles" versus other types of misaligned goals, would it be more like 1000:1 or 1:1 or 1000:1 or something else?
Value them primarily? Uhhh... maybe 1:3 against? I admit I have never actually pondered this question before today; but 1 in 4 uncontrolled superintelligences spending most of their resources on tiny squiggles doesn't sound off by, like, more than 1-2 orders of magnitude in either direction.
...Clocks ar
Not obviously stupid on a very quick skim. I will have to actually read it to figure out where it's stupid.
(I rarely give any review this positive on a first skim. Congrats.)
Did you figure out where it's stupid?
From the top of my head:
While the overall idea is great if they can actually get something like it to work, it certainly won't with the approach described in this post.
We have no way of measuring when an agent is thinking about itself versus others, and no way of doing that has been proposed here.
The authors propose optimizing not for the similarity of activations between "when it thinks about itself" and "when it thinks about others", but for the similarity of activations between "when there's a text apparently referencing the author-character of some tex...
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1By "dumb player" I did not mean as dumb as a human player. I meant "too dumb to compute the pseudorandom numbers, but not too dumb to simulate other players faithfully apart from that". I did not realize we were talking about humans at all. This jumps out more to me as a potential source of misunderstanding than it did 15 years ago, and for that I apologize.
I don't always remember my previous positions all that well, but I doubt I would have said at any point that sufficiently advanced LDT agents are friendly to each other, rather than that they coordinate well with each other (and not so with us)?
Actually, to slightly amend that: The part where squiggles are small is a more than randomly likely part of the prediction, but not a load-bearing part of downstream predictions or the policy argument. Most of the time we don't needlessly build our own paperclips to be the size of skyscrapers; even when having fun, we try to do the fun without vastly more resources, than are necessary to that amount of fun, because then we'll have needlessly used up all our resources and not get to have more fun. We buy cookies that cost a dollar instead ...
The part where squiggles are small and simple is unimportant. They could be bigger and more complicated, like building giant mechanical clocks. The part that matters is that squiggles/paperclips are of no value even from a very cosmopolitan and embracing perspective on value.
2Actually, to slightly amend that: The part where squiggles are small is a more than randomly likely part of the prediction, but not a load-bearing part of downstream predictions or the policy argument. Most of the time we don't needlessly build our own paperclips to be the size of skyscrapers; even when having fun, we try to do the fun without vastly more resources, than are necessary to that amount of fun, because then we'll have needlessly used up all our resources and not get to have more fun. We buy cookies that cost a dollar instead ...
I think that the AI's internal ontology is liable to have some noticeable alignments to human ontology w/r/t the purely predictive aspects of the natural world; it wouldn't surprise me to find distinct thoughts in there about electrons. As the internal ontology goes to be more about affordances and actions, I expect to find increasing disalignment. As the internal ontology takes on any reflective aspects, parts of the representation that mix with facts about the AI's internals, I expect to find much larger differences -- not just that the AI ha...
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2So, would you also say that two random humans are likely to have similar misalignment problems w.r.t. each other? E.g. my brain is different from yours, so the concepts I associate with words like "be helpful" and "don't betray Eliezer" and so forth are going to be different from the concepts you associate with those words, and in some cases there might be strings of words that are meaningful to you but totally meaningless to me, and therefore if you are the principal and I am your agent, and we totally avoid problem #2 (in which you give me instructions and I just don't follow them, even the as-interpreted-by-me version of them) you are still screwed? (Provided the power differential between us is big enough?)
Corrigibility and actual human values are both heavily reflective concepts. If you master a requisite level of the prerequisite skill of noticing when a concept definition has a step where its boundary depends on your own internals rather than pure facts about the environment -- which of course most people can't do because they project the category boundary onto the environment
Actual human values depend on human internals, but predictions about systems that strongly couple to human behavior depend on human internals as well. I thus expect efficient r...
Entirely separately, I have concerns about the ability of ML-based technology to robustly point the AI in any builder-intended direction whatsoever, even if there exists some not-too-large adequate mapping from that intended direction onto the AI's internal ontology at training time. My guess is that more of the disagreement lies here.
I doubt much disagreement between you and I lies there, because I do not expect ML-style training to robustly point an AI in any builder-intended direction. My hopes generally don't route through targeting via ML-style ...
1What the main post is responding to is the argument: "We're just training AIs to imitate human text, right, so that process can't make them get any smarter than the text they're imitating, right? So AIs shouldn't learn abilities that humans don't have; because why would you need those abilities to learn to imitate humans?" And to this the main post says, "Nope."
The main post is not arguing: "If you abstract away the tasks humans evolved to solve, from human levels of performance at those tasks, the tasks AIs are being trained to solve are harder than those tasks in principle even if they were being solved perfectly." I agree this is just false, and did not think my post said otherwise.
Unless I'm greatly misremembering, you did pick out what you said was your strongest item from Lethalities, separately from this, and I responded to it. You'd just straightforwardly misunderstood my argument in that case, so it wasn't a long response, but I responded. Asking for a second try is one thing, but I don't think it's cool to act like you never picked out any one item or I never responded to it.
EDIT: I'm misremembering, it was Quintin's strongest point about the Bankless podcast. https://www.lesswrong.com/posts/wAczufCpMdaamF9fy/my-objections-to-we-re-all-gonna-die-with-eliezer-yudkowsky?commentId=cr54ivfjndn6dxraD
If Quintin hasn't yelled "Empiricism!" then it's not about him. This is more about (some) e/accs.
Wow, that's fucked up.
I am denying that superintelligences play this game in a way that looks like "Pick an ordinal to be your level of sophistication, and whoever picks the higher ordinal gets $9." I expect sufficiently smart agents to play this game in a way that doesn't incentivize attempts by the opponent to be more sophisticated than you, nor will you find yourself incentivized to try to exploit an opponent by being more sophisticated than them, provided that both parties have the minimum level of sophistication to be that smart.
If faced with an opponent stupid enoug...
1You have misunderstood (1) the point this post was trying to communicate and (2) the structure of the larger argument where that point appears, as follows:
First, let's talk about (2), the larger argument that this post's point was supposed to be relevant to.
Is the larger argument that superintelligences will misunderstand what we really meant, due to a lack of knowledge about humans?
It is incredibly unlikely that Eliezer Yudkowsky in particular would have constructed an argument like this, whether in 2007, 2017, or even 1997. At all of these points i...
The old paradox: to care it must first understand, but to understand requires high capability, capability that is lethal if it doesn't care
But it turns out we have understanding before lethal levels of capability. So now such understanding can be a target of optimization. There is still significant risk, since there are multiple possible internal mechanisms/strategies the AI could be deploying to reach that same target. Deception, actual caring, something I've been calling detachment, and possibly others.
This is where the discourse should be focusing...
I agree with cubefox: you seem to be misinterpreting the claim that LLMs actually execute your intended instructions as a mere claim about whether LLMs understand your intended instructions. I claim there is simply a sharp distinction between actual execution and correct, legible interpretation of instructions and a simple understanding of those instructions; LLMs do the former, not merely the latter.
Honestly, I think focusing on this element of the discussion is kind of a distraction because, in my opinion, the charitable interpretation of your posts is s...
I'm well aware of and agree there is a fundamental difference between knowing what we want and being motivated to do what we want. But as I wrote in the first paragraph:
...Already LaMDA or InstructGPT (language models fine-tuned with supervised learning to follow instructions, essentially ChatGPT without any RLHF applied), are in fact pretty safe Oracles in regard to fulfilling wishes without misinterpreting you, and an Oracle AI is just a special kind of Genie whose actions are restricted to outputting text. If you tell InstructGPT what you want, it will
This deserves a longer answer than I have time to allocate it, but I quickly remark that I don't recognize the philosophy or paradigm of updatelessness as refusing to learn things or being terrified of information; a rational agent should never end up in that circumstance, unless some perverse other agent is specifically punishing them for having learned the information (and will lose of their own value thereby; it shouldn't be possible for them to gain value by behaving "perversely" in that way, for then of course it's not "perverse"). Updatelessnes...
2Thank you for engaging, Eliezer.
I completely agree with your point: an agent being updateless doesn't mean it won't learn new information. In fact, it might perfectly decide to "make my future action A depend on future information X", if the updateless prior so finds it optimal. While in other situations, when the updateless prior deems it net-negative (maybe due to other agents exploiting this future dependence), it won't.
This point is already observed in the post (see e.g. footnote 4), although without going deep into it, due to the post being meant for ...
1They can solve it however they like, once they're past the point of expecting things to work that sometimes don't work. I have guesses but any group that still needs my hints should wait and augment harder.
I have guesses but any group that still needs my hints should wait and augment harder.
I think this is somewhat harmful to there being a field of (MIRI-style) Agent Foundations. It seems pretty bad to require that people attempting to start in the field have to work out the foundations themselves, I don’t think any scientific fields have worked this way in the past.
Maybe the view is that if people can’t work out the basics then they won’t be able to make progress, but this doesn’t seem at all clear to me. Many physicists in the 20th century were unabl...
I disagree with my characterization as thinking problems can be solved on paper, and with the name "Poet". I think the problems can't be solved by twiddling systems weak enough to be passively safe, and hoping their behavior generalizes up to dangerous levels. I don't think paper solutions will work either, and humanity needs to back off and augment intelligence before proceeding. I do not take the position that we need a global shutdown of this research field because I think that guessing stuff without trying it is easy, but because guessing it even with some safe weak lesser tries is still impossibly hard. My message to humanity is "back off and augment" not "back off and solve it with a clever theory".
Thank you for the clarification.
How do you expect augmented humanity will solve the problem? Will it be something other than "guessing it with some safe weak lesser tries / clever theory"?
Not what comes up for me, when I go incognito and google AI risk lesswrong.
I rather expect that existing robotic machinery could be controlled by ASI rather than "moderately smart intelligence" into picking up the pieces of a world economy after it collapses, or that if for some weird reason it was trying to play around with static-cling spaghetti It could pick up the pieces of the economy that way too.
It's false that currently existing robotic machinery controlled by moderately smart intelligence can pick up the pieces of a world economy after it collapses. One well-directed algae cell could, but not existing robots controlled by moderate intelligence.
What does this operationalize as? Presumably not that if we load a bone and a diamond rod under equal pressures, the diamond rod breaks first? Is it more about if we drop sudden sharp weights onto a bone rod and a diamond rod, the diamond rod breaks first? I admit I hadn't expected that, despite a general notion that diamond is crystal and crystals are unexpectedly fragile against particular kinds of hits, and if so that modifies my sense of what's a valid metaphor to use.
As an physicist who is also an (unpublished) SF author, if I was trying to describe an ultimate nanoengineered physically strong material, it would be a carbon-carbon composite, using a combination of interlocking structures made out of diamond, maybe with some fluorine passivization, separated by graphene-sheet bilayers, building a complex crack-diffusing structure to achieve toughness in ways comparable to the structures of jade, nacre, or bone. It would be not quite as strong or hard as pure diamond, but a lot tougher. And in a claw-vs-armor fight, yeah...
6"Pandemics" aren't a locally valid substitute step in my own larger argument, because an ASI needs its own manufacturing infrastructure before it makes sense for the ASI to kill the humans currently keeping its computers turned on. So things that kill a bunch of humans are not a valid substitute for being able to, eg, take over and repurpose the existing solar-powered micron-diameter self-replicating factory systems, aka algae, and those repurposed algae being able to build enough computing substrate to go on running the ASI after the humans die.
It's...
11"Pandemics" aren't a locally valid substitute step in my own larger argument, because an ASI needs its own manufacturing infrastructure before it makes sense for the ASI to kill the humans currently keeping its computers turned on.
When people are highly skeptical of the nanotech angle yet insist on a concrete example, I've sometimes gone with a pandemic coupled with limited access to medications that temporarily stave off, but don't cure, that pandemic as a way to force a small workforce of humans preselected to cause few problems to maintain the AI's hard...
31Why is flesh weaker than diamond? Diamond is made of carbon-carbon bonds. Proteins also have some carbon-carbon bonds! So why should a diamond blade be able to cut skin?
I reply: Because the strength of the material is determined by its weakest link, not its strongest link. A structure of steel beams held together at the vertices by Scotch tape (and lacking other clever arrangements of mechanical advantage) has the strength of Scotch tape rather than the strength of steel.
Or: Even when the load-bearing forces holding larg...
7Minor point about the strength of diamond:
bone is so much weaker than diamond (on my understanding) ... Bone cleaves along the weaker fault line, not at its strongest point.
While it is true that the ultimate strength of diamond is much higher than bone, this is relevant primarily for its ability to resist continuously applied pressure (as is its hardness enabling cutting). The point about fault lines seems more relevant for toughness, another material property that describes how much energy can be absorbed without breaking, and there bone beats diamond eas...
Depends on how much of a superintelligence, how implemented. I wouldn't be surprised if somebody got far superhuman theorem-proving from a mind that didn't generalize beyond theorems. Presuming you were asking it to prove old-school fancy-math theorems, and not to, eg, arbitrarily speed up a bunch of real-world computations like asking it what GPT-4 would say about things, etc.
Solution (in retrospect this should've been posted a few years earlier):
let
'Na' = box N contains angry frog
'Ng' = N gold
'Nf' = N's inscription false
'Nt' = N's inscription true
consistent states must have 1f 2t or 1t 2f, and 1a 2g or 1g 2a
then:
1a 1t, 2g 2f => 1t, 2f
1a 1f, 2g 2t => 1f, 2t
1g 1t, 2a 2f => 1t, 2t
1g 1f, 2a 2t => 1f, 2f
I currently guess that a research community of non-upgraded alignment researchers with a hundred years to work, picks out a plausible-sounding non-solution and kills everyone at the end of the hundred years.
2I don't think that faster alignment researchers get you to victory, but uploading should also allow for upgrading and while that part is not trivial I expect it to work.
1AI happening through deep learning at all is a huge update against alignment success, because deep learning is incredibly opaque. LLMs possibly ending up at the center is a small update in favor of alignment success, because it means we might (through some clever sleight, this part is not trivial) be able to have humanese sentences play an inextricable role at the center of thought (hence MIRI's early interest in the Visible Thoughts Project).
The part where LLMs are to predict English answers to some English questions about values, and show common-se...
3I have never since 1996 thought that it would be hard to get superintelligences to accurately model reality with respect to problems as simple as "predict what a human will thumbs-up or thumbs-down". The theoretical distinction between producing epistemic rationality (theoretically straightforward) and shaping preference (theoretically hard) is present in my mind at every moment that I am talking about these issues; it is to me a central divide of my ontology.
If you think you've demonstrated by clever textual close reading that Eliezer-2018 or Elieze...
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1Getting a shape into the AI's preferences is different from getting it into the AI's predictive model.
It seems like you think that human preferences are only being "predicted" by GPT-4, and not "preferred." If so, why do you think that?
I commonly encounter people expressing sentiments like "prosaic alignment work isn't real alignment, because we aren't actually getting the AI to care about X." To which I say: How do you know that? What does it even mean for that claim to be true or false? What do you think you know, and why do you think you know it? What e...
3...Getting a shape into the AI's preferences is different from getting it into the AI's predictive model. MIRI is always in every instance talking about the first thing and not the second.
You obviously need to get a thing into the AI at all, in order to get it into the preferences, but getting it into the AI's predictive model is not sufficient. It helps, but only in the same sense that having low-friction smooth ball-bearings would help in building a perpetual motion machine; the low-friction ball-bearings are not the main problem, they are a kin
Your comment focuses on GPT4 being "pretty good at extracting preferences from human data" when the stronger part of the argument seems to be that "it will also generally follow your intended directions, rather than what you literally said".
I agree with you that it was obvious in advance that a superintelligence would understand human value.
However, it sure sounded like you thought we'd have to specify each little detail of the value function. GPT4 seems to suggest that the biggest issue will be a situation where:
1) The AI has an option that would produce ...
I'm not going to comment on "who said what when", as I'm not particularly interested in the question myself, though I think the object level point here is important:
This makes the nonstraightforward and shaky problem of getting a thing into the AI's preferences, be harder and more dangerous than if we were just trying to get a single information-theoretic bit in there.
The way I would phrase this is that what you care about is the relative complexity of the objective conditional on the world model. If you're assuming that the model is highly capable, an...
441Getting a shape into the AI's preferences is different from getting it into the AI's predictive model. MIRI is always in every instance talking about the first thing and not the second.
Why would we expect the first thing to be so hard compared to the second thing? If getting a model to understand preferences is not difficult, then the issue doesn't have to do with the complexity of values. Finding the target and acquiring the target should have the same or similar difficulty (from the start), if we can successfully ask the model to find the target fo...
1I think you missed some basic details about what I wrote. I encourage people to compare what Eliezer is saying here to what I actually wrote. You said:
If you think you've demonstrated by clever textual close reading that Eliezer-2018 or Eliezer-2008 thought that it would be hard to get a superintelligence to understand humans, you have arrived at a contradiction and need to back up and start over.
I never said that you or any other MIRI person thought it would be "hard to get a superintelligence to understand humans". Here's what I actually wrote:
...Non-MIRI p
But if you had asked us back then if a superintelligence would automatically be very good at predicting human text outputs, I guarantee we would have said yes. [...] I wish that all of these past conversations were archived to a common place, so that I could search and show you many pieces of text which would talk about this critical divide between prediction and preference (as I would now term it) and how I did in fact expect superintelligences to be able to predict things!
Quoting myself in April:
..."MIRI's argument for AI risk depended on AIs being bad at n
Historically you very clearly thought that a major part of the problem is that AIs would not understand human concepts and preferences until after or possibly very slightly before achieving superintelligence. This is not how it seems to have gone.
Everyone agrees that you assumed superintelligence would understand everything humans understand and more. The dispute is entirely about the things that you encounter before superintelligence. In general it seems like the world turned out much more gradual than you expected and there's information to be found in what capabilities emerged sooner in the process.
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311There's perhaps more detail in Project Lawful and in some nearby stories ("for no laid course prepare", "aviation is the most dangerous routine activity").
Have you ever seen or even heard of a person who is obese who doesn't eat hyperpalatable foods? (That is, they only eat naturally tasting, unprocessed, "healthy" foods).
Tried this for many years. Paleo diet; eating mainly broccoli and turkey; trying to get most of my calories from giant salads. Nothing.
Received $95.51. :)
I am not - $150K is as much as I care to stake at my present weath levels - and while I refunded your payment, I was charged a $44.90 fee on the original transmission which was not then refunded to me.
Oh, that's suboptimal, sending 100$ to cover the fee charge (the extra in case they take another fee for some reason).
Again, apologies for the inconvenience. (wire sent)
Though I disagree with @RatsWrongAboutUAP (see this tweet) and took the other side of the bet, I say a word of praise for RatsWrong about following exactly the proper procedure to make the point they wanted to make, and communicating that they really actually think we're wrong here. Object-level disagreement, meta-level high-five.
Glad to have made this bet with you!
Received.
Cool. What's the actual plan and why should I expect it not to create machine Carissa Sevar? I agree that the Textbook From The Future Containing All The Simple Tricks That Actually Work Robustly enables the construction of such an AI, but also at that point you don't need it.