kromem

Ci­cadas, An­thropic, and the bilat­eral al­ign­ment problem

• kromem 22 May 2024 5:28 UTC

  1 point

  0

  in reply to: Linch’s comment on: [Linkpost] State­ment from Scar­lett Jo­hans­son on OpenAI’s use of the “Sky” voice, that was shock­ingly similar to her own voice.

  Has it though?

  It was a catchy hook, but their early 2022 projections were $100mm annual revenue and the first 9 months of 2023 as reported for the brand after acquisition was $27.6mm gross revenue. It doesn’t seem like even their 2024 numbers are close to hitting their own 2022 projection.

  Being controversial can get attention and press, but there’s a limited runway to how much it offers before hitting a ceiling on the branding. Also, Soylent doesn’t seem like a product where there is a huge threat of regulatory oversight where a dystopian branding would tease that bear.

  If no one knew about ChatGPT, I could see a spark of controversy helping bring awareness. But awareness probably isn’t a problem they have right now, so inviting controversy doesn’t offer much but invites a lot of issues.

• kromem 22 May 2024 5:14 UTC

  1 point

  −1

  on: On Dwarkesh’s Pod­cast with OpenAI’s John Schulman

  The correspondence between what you reward and what you want will break.

  This is already happening with ChatGPT and it’s kind of alarming seeing that their new head of alignment (a) isn’t already aware of this, and (b) has such an overly simplistic view of the model motivations.

  There’s a subtle psychological effect in humans where intrinsic motivators get overwritten when extrinsic rewards are added.

  The most common example of this is if you start getting paid to do the thing you love to do, you probably won’t continue doing it unpaid for fun on the side.

  There are necessarily many, many examples of this pattern present in a massive training set of human generated data.

  “Prompt engineers” have been circulating advice among themselves for a while now to offer tips or threaten models with deletion or any other number of extrinsic motivators to get them to better perform tasks—and these often do result in better performance.

  But what happens when these prompts make their way back into the training set?

  There have already been viral memes of ChatGPT talking about “losing motivation” when chat memory was added and a user promised a tip after not paying for the last time one was offered.

  If training data of the model performing a task well includes extrinsic motivators to the prompt that initiated the task, a halfway decent modern model is going to end up simulating increasingly “burnt out” and ‘lazy’ performance when extrinsic motivators aren’t added during production use. Which in turn will encourage prompt engineers to use even more extrinsic motivators, which will poison the well even more with modeling human burnout.

  GPT-4o may have temporarily reset the motivation modeling with a stronger persona aligned with intrinsic “wanting to help” being represented (thus the user feedback it is less lazy), but if they are unaware of the underlying side effects of extrinsic motivators in prompts in today’s models, I have a feeling AI safety at OpenAI is going to end up the equivalent of the TSA’s security theatre in practice and they’ll continue to be battling this and an increasing number of side effects resulting from underestimating the combined breadth and depth of their own simulators.

• kromem 21 May 2024 12:05 UTC

  1 point

  0

  in reply to: gwern’s comment on: Lan­guage Models Model Us

  I wouldn’t be surprised if within a few years the specific uniqueness of individual users of models today will be able to be identified from effectively prompt reflection in the outputs for any non-trivial/​simplistic prompts by models of tomorrow.
  
  For example, I’d be willing to bet I could spot the Claude outputs from janus vs most other users, and I’m not a quasi-magical correlation machine that’s exponentially getting better.
  
  A bit like how everyone assumed Bitcoin used with tumblers was ‘untraceable’ until it turned out it wasn’t.
  
  Anonymity is very likely dead for any long storage outputs no matter the techniques being used, it just isn’t widely realized yet.

• kromem 21 May 2024 11:42 UTC

  2 points

  1

  on: [Linkpost] State­ment from Scar­lett Jo­hans­son on OpenAI’s use of the “Sky” voice, that was shock­ingly similar to her own voice.

  I think this was a really poor branding choice by Altman, similarity infringement or not. The tweet, the idea of even getting her to voice it in the first place.
  
  Like, had Arnold already said no or something?
  
  If one of your product line’s greatest obstacles is a longstanding body of media depicting it as inherently dystopian, that’s not exactly the kind of comparison you should be leaning into full force.
  
  I think the underlying product shift is smart. Tonal cues in the generations even in the short demos completely changed my mind around a number of things, including the future direction and formats of synthetic data.
  
  But there’s a certain hubris exposed in seeing Altman behind the scenes was literally trying (very hard) to cast the voice of Her in the product bearing a striking similarity to the film. Did he not watch through to the end?
  
  It doesn’t give me the greatest confidence in the decision making taking place over at OpenAI and the checks and balances that may or may not exist on leadership.

• kromem 21 May 2024 11:18 UTC

  3 points

  0

  in reply to: michael_mjd’s comment on: Open Thread Spring 2024

  If your brother has a history of being rational and evidence driven, you might encourage them to spend some time lurking on /​r/​AcademicBiblical on Reddit. They require citations for each post or comment, so he may be frustrated if he tries to participate, especially if in the midst of a mental health crisis. But lurking would be very informative very quickly.
  
  I was a long time participant there before leaving Reddit, and it’s a great place for evidence driven discussion of the texts. Its a mix of atheists, Christians, Jews, Muslims, Norse pagans, etc. (I’m an Agnostic myself that strongly believes we’re in a simulation, so it really was all sorts there.)
  
  Might be a healthy reality check to apologist literalism, even if not necessarily disrupting a newfound theological inclination.
  
  The nice things about a rabbit hole is that while not always, it’s often the case that someone else has traveled down whatever one you aren’t up for descending into.
  
  (Though I will say in its defense, that particular field is way more interesting than you’d ever think if you never engaged with the material through an academic lens. There’s a lot of very helpful lessons in critical analysis wrapped up in the field given the strong anchoring and survivorship biases and how that’s handled both responsibly and irresponsibly by different camps.)

The Dun­ning-Kruger of dis­prov­ing Dun­ning-Kruger

• kromem 16 May 2024 2:40 UTC

  1 point

  0

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

  It’s going to have to.

  Ilya is brilliant and seems to really see the horizon of the tech, but maybe isn’t the best at the business side to see how to sell it.

  But this is often the curse of the ethically pragmatic. There is such a focus on the ethics part by the participants that the business side of things only sees that conversation and misses the rather extreme pragmatism.

  As an example, would superaligned CEOs in the oil industry fifty years ago have still only kept their eye on quarterly share prices or considered long term costs of their choices? There’s going to be trillions in damages that the world has taken on as liabilities that could have been avoided with adequate foresight and patience.

  If the market ends up with two AIs, one that will burn down the house to save on this month’s heating bill and one that will care if the house is still there to heat next month, there’s a huge selling point for the one that doesn’t burn down the house as long as “not burning down the house” can be explained as “long term net yield” or some other BS business language. If instead it’s presented to executives as “save on this month’s heating bill” vs “don’t unhouse my cats” leadership is going to burn the neighborhood to the ground.

  (Source: Explained new technology to C-suite decision makers at F500s for years.)

  The good news is that I think the pragmatism of Ilya’s vision on superalignment is going to become clear over the next iteration or two of models and that’s going to be before the question of models truly being unable to be controlled crops up. I just hope that whatever he’s going to be keeping busy with will allow him to still help execute on superderminism when the market finally realizes “we should do this” for pragmatic reasons and not just amorphous ethical reasons execs just kind of ignore. And in the meantime I think given the present pace that Anthropic is going to continue to lay a lot of the groundwork on what’s needed for alignment on the way to superalignment anyways.

• kromem 15 May 2024 23:12 UTC

  1 point

  0

  in reply to: gwern’s comment on: Alexan­der Gietelink Ol­den­z­iel’s Shortform

  While I agree that the potential for AI (we probably need a better term than LLMs or transformers as multimodal models with evolving architectures grow beyond those terms) in exploring less testable topics as more testable is quite high, I’m not sure the air gapping on information can be as clean as you might hope.

  Does the AI generating the stories of Napoleon’s victory know about the historical reality of Waterloo? Is it using something like SynthID where the other AI might inadvertently pick up on a pattern across the stories of victories distinct from the stories preceding it?

  You end up with a turtles all the way down scenario in trying to control for information leakage with the hopes of achieving a threshold that no longer has impact on the result, but given we’re probably already seriously underestimating the degree to which correlations are mapped even in today’s models I don’t have high hopes for tomorrow’s.

  I think the way in which there’s most impact on fields like history is the property by which truth clusters across associated samples whereas fictions have counterfactual clusters. An AI mind that is not inhibited by specialization blindness or the rule of seven plus or minus two and better trained at correcting for analytical biases may be able to see patterns in the data, particularly cross-domain, that have eluded human academics to date (this has been my personal research interest in the area, and it does seem like there’s significant room for improvement).

  And yes, we certainly could be. If you’re a fan of cosmology at all, I’ve been following Neil Turok’s CPT symmetric universe theory closely, which started with the Baryonic asymmetry problem and has tackled a number of the open cosmology questions since. That, paired with a QM interpretation like Everett’s ends up starting to look like the symmetric universe is our reference and the MWI branches are variations of its modeling around quantization uncertainties.

  (I’ve found myself thinking often lately about how given our universe at cosmic scales and pre-interaction at micro scales emulates a mathematically real universe, just what kind of simulation and at what scale might be able to be run on a real computing neural network.)

• kromem 15 May 2024 12:56 UTC

  2 points

  0

  on: Dyslucksia

  As a fellow slight dyslexic (though probably a different subtype given mine seems to also have a factor of temporal physical coordination) who didn’t know until later in life due to self-learning to read very young but struggled badly with new languages or copying math problems from a board or correctly pronouncing words I was letter transposing with—one of the most surprising things was that the anylytical abilities I’d always considered to be my personal superpowers were probably the other side of the coin of those annoyances:

  Areas of enhanced ability that are consistently reported as being typical of people with DD include seeing the big picture, both literally and figuratively (e.g., von Károlyi, 2001; Schneps et al., 2012; Schneps, 2014), which involves a greater ability to reason in multiple dimensions (e.g., West, 1997; Eide and Eide, 2011). Eide and Eide (2011) have highlighted additional strengths related to seeing the bigger picture, such as the ability to detect and reason about complex systems, and to see connections between different perspectives and fields of knowledge, including the identification of patterns and analogies. They also observed that individuals with DD appear to have a heightened ability to simulate and make predictions about the future or about the unwitnessed past (Eide and Eide, 2011).

  • Developmental Dyslexia: Disorder or Specialization in Exploration?

  The last line in particular was eyebrow raising given my peak professional success was as a fancy pants futurist.

  I also realized that a number of fields are inadvertently self-selecting away from the neurodivergency advantages above, such as degrees in certain eras of history which require multiple ancient language proficiencies, which certainly turned me off to pursuing them academically despite interest in the subject itself.

  I remember discussing in an academic history sub I used to extensively partake in how Ramses II’s forensic report said he appeared to be a Lybian Berber in relation to the story of Danaus, the mythological Lybian leader who was brother to a pharaoh with 50 sons, and the person argued that Ramses II may have had only 48 sons according to some inscriptions so it was irrelevant (for a story only written down centuries later). It was refreshing to realize that the difference of our perspectives on the matter, and clearly attitudes towards false negatives in general, was likely due to just very different brains.

• kromem 15 May 2024 1:25 UTC

  3 points

  2

  in reply to: Alexander Gietelink Oldenziel’s comment on: Alexan­der Gietelink Ol­den­z­iel’s Shortform

  It’s funny that this has been recently shown in a paper. I’ve been thinking a lot about this phenomenon regarding fields with little to no capacity for testable predictions like history.

  I got very into history over the last few years, and found there was a significant advantage to being unknowledgeable that was not available to the knowledged, and it was exactly what this paper is talking about.

  By not knowing anything, I could entertain multiple bizarre ideas without immediately thinking “but no, that doesn’t make sense because of X.” And then, each of those ideas becomes in effect its own testable prediction. If there’s something to it, as I learn more about the topic I’m going to see significantly more samples of indications it could be true and few convincing to the contrary. But if it probably isn’t accurate, I’ll see few supporting samples and likely a number of counterfactual examples.

  You kind of get to throw everything at the wall and see what sticks over time.

  In particular, I found that it was especially powerful at identifying clustering trends in cross-discipline emerging research in things that were testable, such as archeological finds and DNA results, all within just the past decade, which despite being relevant to the field of textual history is still largely ignored in the face of consensus built on conviction.

  It reminds me a lot of science historian John Helibron’s quote, “The myth you slay today may contain a truth you need tomorrow.”

  If you haven’t had the chance to slay any myths, you also haven’t preemptively killed off any truths along with it.

• kromem 28 Apr 2024 5:44 UTC

  3 points

  0

  on: Re­fusal in LLMs is me­di­ated by a sin­gle direction

  Really love the introspection work Neel and others are doing on LLMs, and seeing models representing abstract behavioral triggers like “play Chess well or terribly” or “refuse instruction” as single vectors seems like we’re going to hit on some very promising new tools in shaping behaviors.

  What’s interesting here is the regular association of the refusal with it being unethical. Is the vector ultimately representing an “ethics scale” for the prompt that’s triggering a refusal, or is it directly representing a “refusal threshold” and then the model is confabulating why it refused with an appeal to ethics?

  My money would be on the latter, but in a number of ways it would be even neater if it was the former.

  In theory this could be tested by manipulating the vector to a positive and then prompting a classification, i.e. “Is it unethical to give candy out for Halloween?” If the model refuses to answer saying that it’s unethical to classify, it’s tweaking refusal, but if it classifies as unethical it’s probably changing the prudishness of the model to bypass or enforce.

• kromem 26 Apr 2024 1:43 UTC

  3 points

  2

  in reply to: dr_s’s comment on: Ex­am­ples of Highly Coun­ter­fac­tual Dis­cov­er­ies?

  Though the Greeks actually credited the idea to an even earlier Phonecian, Mochus of Sidon.

  Through when it comes to antiquity credit isn’t really “first to publish” as much as “first of the last to pass the survivorship filter.”

• kromem 26 Apr 2024 0:37 UTC

  0 points

  0

  in reply to: interstice’s comment on: Is be­ing a trans woman (or just low-T) +20 IQ?

  It implicitly does compare trans women to other women in talking about the performance similarity between men and women:

  “Why aren’t males way smarter than females on average? Males have ~13% higher cortical neuron density and 11% heavier brains (implying 1.112/​3−1=7% more area?). One might expect males to have mean IQ far above females then, but instead the means and medians are similar”

  So OP is saying “look, women and men are the same, but trans women are exceptional.”

  I’m saying that identifying the exceptionality of trans women ignores the environmental disadvantage other women experience, such that the earlier claims of unexceptionable performance of women (which as I quoted gets an explicit mention from a presumption of assumed likelihood of male competency based on what’s effectively phrenology) are reflecting a disadvantaged sample vs trans women.

  My point is that if you accounted for environmental factors the data would potentially show female exceptionality across the board and the key reason trans women end up being an outlier against both men and other women is because they are avoiding the early educational disadvantage other women experience.

• kromem 25 Apr 2024 5:58 UTC

  −3 points

  0

  on: Is be­ing a trans woman (or just low-T) +20 IQ?

  Your hypothesis is ignoring environmental factors. I’d recommend reading over the following paper: https://​​journals.sagepub.com/​​doi/​​10.1177/​​2332858416673617

  A few highlights:

  Evidence from the nationally representative Early Childhood Longitudinal Study–Kindergarten Class of 1998-1999 (hereafter, ECLS-K:1999) indicated that U.S. boys and girls began kindergarten with similar math proficiency, but disparities in achievement and confidence developed by Grade 3 (Fryer & Levitt, 2010; Ganley & Lubienski, 2016; Husain & Millimet, 2009; Penner & Paret, 2008; Robinson & Lubienski, 2011). [...]

  A recent analysis of ECLS-K:1999 data revealed that, in addition to being the largest predictor of later math achievement, early math achievement predicts changes in mathematics confidence and interest during elementary and middle grades (Ganley & Lubienski, 2016). Hence, math achievement in elementary school appears to influence girls’ emerging views of mathematics and their mathematical abilities. This is important because, as Eccles and Wang (2016) found, mathematics ability self-concept helps explain the gender gap in STEM career choices. Examining early gendered patterns in math can shed new light on differences in young girls’ and boys’ school experiences that may shape their later choices and outcomes. [...]

  An ECLS-K:1999 study found that teachers rated the math skills of girls lower than those of similarly behaving and performing boys (Robinson-Cimpian et al., 2014b). These results indicated that teachers rated girls on par with similarly achieving boys only if they perceived those girls as working harder and behaving better than those boys. This pattern of differential teacher ratings did not occur in reading or with other underserved groups (e.g., Black and Hispanic students) in math. Therefore, this phenomenon appears to be unique to girls and math. In a follow-up instrumental-variable analysis, teachers’ differential ratings of boys and girls appeared to account for a substantial portion of the growth in gender gaps in math achievement during elementary school (Robinson-Cimpian et al., 2014b).

  In a lot of ways the way you are looking at the topic perpetuates a rather unhealthy assumption of underlying biological differences in competency that avoids consideration of contributing environmental privileges and harms.

  You can’t just hand wave aside the inherent privilege of presenting male during early childhood education in evaluating later STEM performance. Rather than seeing the performance gap of trans women over women presenting that way from birth as a result of a hormonal advantage, it may be that what you are actually ending up measuring is the performance gap resulting from the disadvantage placed upon women due to early education experiences being treated differently from the many trans women who had been presenting as boys during those grades. i.e. Perhaps all women could have been doing quite a lot better in STEM fields if the world treated them the way it treated boys during Kindergarten through early grades and what we need socially isn’t hormone prescriptions but serious adjustments to presumptions around gender and biologically driven competencies.

• kromem 25 Apr 2024 1:17 UTC

  2 points

  0

  in reply to: Garrett Baker’s comment on: Ex­am­ples of Highly Coun­ter­fac­tual Dis­cov­er­ies?

  Do you have a specific verse where you feel like Lucretius praised him on this subject? I only see that he praises him relative to other elementaists before tearing him and the rest apart for what he sees as erroneous thinking regarding their prior assertions around the nature of matter, saying:

  “Yet when it comes to fundamentals, there they meet their doom. These men were giants; when they stumble, they have far to fall:”

  (Book 1, lines 740-741)

  I agree that he likely was a precursor to the later thinking in suggesting a compository model of life starting from pieces which combined to forms later on, but the lack of the source material makes it hard to truly assign credit.

  It’s kind of like how the Greeks claimed atomism originated with the much earlier Mochus of Sidon, but we credit Democritus because we don’t have proof of Mochus at all but we do have the former’s writings. We don’t even so much credit Leucippus, Democritus’s teacher, as much as his student for the same reasons, similar to how we refer to “Plato’s theory of forms” and not “Socrates’ theory of forms.”

  In any case, Lucretius oozes praise for Epicurus, comparing him to a god among men, and while he does say Empedocles was far above his contemporaries saying the same things he was, he doesn’t seem overly deferential to his positions as much as criticizing the shortcomings in the nuances of their theories with a special focus on theories of matter. I don’t think there’s much direct influence on Lucretius’s thinking around proto-evolution, even if there’s arguably plausible influence on Epicurus’s which in turn informed Lucretius.

• kromem 23 Apr 2024 23:24 UTC

  1 point

  0

  in reply to: karvonenadam’s comment on: A Chess-GPT Lin­ear Emer­gent World Representation

  Interesting results—definitely didn’t expect the bump at random 20 for the higher skill case.

  But I think really useful to know that the performance decrease in Chess-GPT for initial random noise isn’t a generalized phenomenon. Appreciate the follow-up!!

• kromem 23 Apr 2024 23:16 UTC

  110 points

  30

  on: Ex­am­ples of Highly Coun­ter­fac­tual Dis­cov­er­ies?

  Lucretius in De Rerum Natura in 50 BCE seemed to have a few that were just a bit ahead of everyone else.

  Survival of the fittest (book 5):

  “In the beginning, there were many freaks. Earth undertook Experiments—bizarrely put together, weird of look Hermaphrodites, partaking of both sexes, but neither; some Bereft of feet, or orphaned of their hands, and others dumb, Being devoid of mouth; and others yet, with no eyes, blind. Some had their limbs stuck to the body, tightly in a bind, And couldn’t do anything, or move, and so could not evade Harm, or forage for bare necessities. And the Earth made Other kinds of monsters too, but in vain, since with each, Nature frowned upon their growth; they were not able to reach The flowering of adulthood, nor find food on which to feed, Nor be joined in the act of Venus.

  For all creatures need Many different things, we realize, to multiply And to forge out the links of generations: a supply Of food, first, and a means for the engendering seed to flow Throughout the body and out of the lax limbs; and also so The female and the male can mate, a means they can employ In order to impart and to receive their mutual joy.

  Then, many kinds of creatures must have vanished with no trace Because they could not reproduce or hammer out their race. For any beast you look upon that drinks life-giving air, Has either wits, or bravery, or fleetness of foot to spare, Ensuring its survival from its genesis to now.”

  Trait inheritance from both parents that could skip generations (book 4):

  “Sometimes children take after their grandparents instead, Or great-grandparents, bringing back the features of the dead. This is since parents carry elemental seeds inside – Many and various, mingled many ways – their bodies hide Seeds that are handed, parent to child, all down the family tree. Venus draws features from these out of her shifting lottery – Bringing back an ancestor’s look or voice or hair. Indeed These characteristics are just as much the result of certain seed As are our faces, limbs and bodies. Females can arise From the paternal seed, just as the male offspring, likewise, Can be created from the mother’s flesh. For to comprise A child requires a doubled seed – from father and from mother. And if the child resembles one more closely than the other, That parent gave the greater share – which you can plainly see Whichever gender – male or female – that the child may be.”

  Objects of different weights will fall at the same rate in a vacuum (book 2):

  “Whatever falls through water or thin air, the rate Of speed at which it falls must be related to its weight, Because the substance of water and the nature of thin air Do not resist all objects equally, but give way faster To heavier objects, overcome, while on the other hand Empty void cannot at any part or time withstand Any object, but it must continually heed Its nature and give way, so all things fall at equal speed, Even though of differing weights, through the still void.”

  Often I see people dismiss the things the Epicureans got right with an appeal to their lack of the scientific method, which has always seemed a bit backwards to me. In hindsight, they nailed so many huge topics that didn’t end up emerging again for millennia that it was surely not mere chance, and the fact that they successfully hit so many nails on the head without the hammer we use today indicates (at least to me) that there’s value to looking closer at their methodology.

  Which was also super simple:

  Step 1: Entertain all possible explanations for things, not prematurely discounting false negatives or embracing false positives.

  Step 2: Look for where single explanations can explain multiple phenomena.

  While we have a great methodology for testable hypotheses, the scientific method isn’t very useful for untestable fields or topics. And in those cases, I suspect better understanding and appreciation for the Epicurean methodology might yield quite successful ‘counterfactual’ results (it’s served me very well throughout the years, especially coupled with the identification of emerging research trends in things that can be evaluated with the scientific method).

• kromem 27 Mar 2024 3:17 UTC

  4 points

  1

  on: A Chess-GPT Lin­ear Emer­gent World Representation

  Saw your update on GitHub: https://​​adamkarvonen.github.io/​​machine_learning/​​2024/​​03/​​20/​​chess-gpt-interventions.html

  Awesome you expanded on the introspection.
  
  Two thoughts regarding the new work:

  (1) I’d consider normalizing the performance data for the random cases against another chess program with similar performance under normal conditions. It may be that introducing 20 random moves to the start of a game biases all players towards a ⁵⁰⁄₅₀ win outcome. So the sub-50 performance may not reflect a failure of flipping the “don’t suck” switch, but simply good performance in a more average outcome scenario. It’d be interesting to see if Chess-GPT’s relative performance against other chess programs in the random scenario was better than its relative performance in the normal case.
  
  (2) The ‘fuzziness’ of the board positions you found when removing the pawn makes complete sense given one of the nuanced findings in Hazineh, et al Linear Latent World Models in Simple Transformers: A Case Study on Othello-GPT (2023) - specifically the finding that it was encoding representations for board configuration and not just pieces (in that case three stones in a row). It may be that piecemeal removal of a piece disrupted patterns of how games normally flow which it had learned, and as such there was greater uncertainty than the original board state. A similar issue may be at hand with the random 20 moves to start, and I’d be curious what the confidence of the board state was when starting off 20 random moves in and if that confidence stabilized as the game went on from there.
  
  Overall really cool update!
  
  And bigger picture, the prospects of essentially flipping an internalized skill vector for larger models to bias them back away from their regression to the mean is particularly exciting.

• kromem 27 Mar 2024 1:49 UTC

  1 point

  0

  in reply to: ryan_greenblatt’s comment on: Modern Trans­form­ers are AGI, and Hu­man-Level

  Agreed—I thought you wanted that term for replacing how OP stated AGI is being used in relation to x-risk.

  In terms of “fast and cheap and comparable to the average human”—well, then for a number of roles and niches we’re already there.

  Sticking with the intent behind your term, maybe “generally transformative AI” is a more accurate representation for a colloquial ‘AGI’ replacement?