bokov

• bokov 20 Sep 2024 18:03 UTC

  2 points

  0

  in reply to: lc’s comment on: My sim­ple AGI in­vest­ment & in­surance strategy

  Would you mind sharing how you allocated the ratio of these positions?

• bokov 20 Sep 2024 17:37 UTC

  2 points

  0

  in reply to: Decaeneus’s comment on: My sim­ple AGI in­vest­ment & in­surance strategy

  Maybe the key is not to assume the entire economy will win, but make some attempt to distinguish winners from losers and then find ETFs and other instruments that approximate these sectors.

  So, some wild guesses...

  • AI labs and their big-tech partners: winners

  • Cloud hosting: winners

  • Commercial real estate specializing in server farms: winners

  • Whoever comes up with tractable ways to power all these server farms: winners

  • AI-enabling hardware companies: winners until the Chinese blockade Taiwan and impose an embargo on raw materials… after that… maybe losers except the ones that have already started diversifying their supply-chains?

  • Companies which inherently depend on aggregating and reselling labor: tricky, because if they do nothing, they’re toast, but some of them can turn themselves into resellers of AI… e.g. a temp agency rolling out AI services as a cheaper product line

  • Professional services: same as above but less exposed

  • Businesses that are needed only in proportion to other businesses having human employees: travel, office real estate, office furniture and supplies: losers

  As the effects ripple out and more and more workers are displaced...

  • Low to mid-end luxury goods and eventually anything that depends on mass discretionary spending: losers

  Though what I really would like to do is create some sort of rough model of an individual non-AI company with the following parameters:

  • Recurring costs attributable to employees

  • Other recurring costs

  • Revenue

  • Fraction of employees whose jobs can be automated at the current state of the art

  • Variables representing of how far along this company is in planning or implementing AI-driven consolidation and how quickly it is capable of cutting over to AI

  • Fixed costs of cut-over to AI

  • Variable costs of cut-over to AI (depending on aggregate workload being automated)

  • Whatever other variables people who unlike me actually know something about fundamental analysis would put in such a model.

  ...and then be able to make a principled guess about where on the AI-winners vs AI-losers spectrum a given company is. I even started sketching out a model like this until I realized that someone with relevant expertise must have already written a general-purpose model of this sort and I should find it and adapt it to the AI-automation scenario instead of making up my own.

• bokov 20 Sep 2024 17:00 UTC

  2 points

  0

  on: My sim­ple AGI in­vest­ment & in­surance strategy

  I’m trying out this strategy on Investopedia’s simulator (https://​​www.investopedia.com/​​simulator/​​trade/​​options)

  The January 15 2027 call options on QQQ look like this as of posting (current price 481.48):

  Strike	Black-Scholes	Ask
  485	64.244	77.4
  500	57.796	69.83
  …	…	…
  675	14.308	14
  680	13.693	13.5
  685	13.077	12.49
  …	…	…
  700	11.446	10.5
  …	…	…
  720	9.702	8.5

  So, if you were following this strategy and buying today, would you buy 485 because it has the lowest OOM strike price? Would you buy 675 because it’s the lowest strike price where the ask is lower than the theoretical Black-Sholes fair price? Would you go for 720 because it’s the cheapest available? Would you look for the out-of-money option with the largest difference between Black-Sholes and the ask?

  What would be your thought process? I’m definitely hoping to hear from @lc but am interested in hearing from anybody who found this line of reasoning worth investigating and has opinions about it.

• bokov 20 Sep 2024 1:30 UTC

  1 point

  0

  on: My sim­ple AGI in­vest­ment & in­surance strategy

  So, how can we improve this further?

  Some things I’m going to look into, please tell me if it’s a waste of time:

  • Seeing if there are any REITs that specialize in server farms or chip fabs and have long-term options

  • Apparently McKinsey has a report about what white-collar jobs are most amenable to automation. Tracking down this report (they have lots) if it’s not paywalled or at least learning enough about it to get the gist of which (non-AI) companies would save the most money by “intelligent automation”.

    • From first principles I’d expect companies/​industries which have a large proportion of their operating expenses going to salaries and benefits as the first in line to automate.

    • Industries that are essentially aggregators and resellers of labor would have to do this to survive at all

    • ...and the ones among them that lag in AI adoption would be candidates for short positions

• bokov 19 Sep 2024 22:35 UTC

  1 point

  0

  on: My sim­ple AGI in­vest­ment & in­surance strategy

  A risk I see is China blockading Taiwan and/​or limiting trade with the US and thus slowing AI development until a new equilibrium is reached through onshoring (and maybe recycling or novel sources of materials or something?)

  On the other hand maybe even the current LLMs already have the potential to eliminate millions of jobs and it’s just going to take companies a while to do the planning and integration work necessarily to actually do it.

  So one question is, will the resulting increase in revenue offset the revenue losses from a proxy war with China?

• bokov 4 Jun 2024 20:14 UTC

  1 point

  0

  in reply to: ChristianKl’s comment on: Is it time to talk about AI dooms­day prep­ping yet?

  I guess scenarios where humans occupy a niche analogous to animals that we don’t value but either cannot exterminate or choose not to.

• bokov 4 Jun 2024 18:33 UTC

  1 point

  0

  on: Another at­tempt to ex­plain UDT

  Parfitt’s Hitchhiker and transparent Newcomb: So is the interest in UDT motivated by the desire for a rigorous theory that explains human moral intuitions? Like, it’s not enough that feelings of reciprocity must have conveyed a selective advantage at the population level, we need to know whether/​how they also are net beneficial to the individuals involved?

• bokov 4 Jun 2024 18:26 UTC

  1 point

  0

  on: Another at­tempt to ex­plain UDT

  What should one do if in a Newcomb’s paradox situation but Omega is just a regular dude who thinks they can predict what you will choose, by analysing data from thousands of experiments on e.g. Mechanical Turk?

  Do UDT and CDT differ in this case? If they differ then does it depend on how inaccurate Omega’s predictions are and in what direction they are biased?

• bokov 4 Jun 2024 18:19 UTC

  1 point

  0

  in reply to: cousin_it’s comment on: Another at­tempt to ex­plain UDT

  Thank you for answering.

  I’m excluding simulations by construction.

  Amnesia: So does UDT roughly-speking direct you to weigh your decisions based on your guesstimate of what decision-relevant facts apply in that scenario? And then choose among available options randomly but weighted by how likely each option is to be optimal in whatever scenario you have actually found yourself in?

  Identical copies, (non-identical but very similar players?), players with aligned interests,: I guess this is a special case of dealing with a predictor agent where our predictions of each other’s decisions are likely enough to be accurate that they should be taken into account? So UDT might direct you to disregard causality because you’re confident that the other party will do so the same on their own initiative?

  But I don’t understand what this has in common with amnesia scenarios. Is it about disregarding causality?

  Non-perfect predictors: Most predictors of anything as complicated as behaviour are VERY imperfect both at the model level and the data-collection level. So wouldn’t the optimal thing to do be to down weigh your confidence in what the other player will do when deciding your own course of action? Unless you have information about how they model you in which case you could try to predict your own behaviour from their perspective?

• bokov 3 Jun 2024 23:37 UTC

  1 point

  0

  on: Another at­tempt to ex­plain UDT

  Are there any practical applications of UDT that don’t depend on uncertainty as to whether or not I am a simulation, nor on stipulating that one of the participants in a scenario is capable of predicting my decisions with perfect accuracy?

• bokov 24 May 2024 22:52 UTC

  1 point

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  in reply to: PhilosophicalSoul’s comment on: Re­quest for com­ments/​opinions/​ideas on safety/​ethics for use of tool AI in a large health­care sys­tem.

  I appreciate your feedback and take it in the spirit it is intended. You are in no danger of shitting on my idea because it’s not my idea. It’s happening with or without me.

  My idea is to cast a broad net looking for strategies for harm reduction and risk mitigation within these constraints.

  I’m with you that machines practising medicine autonomously is an bad idea, as do doctors. Because, idealistically, they got into this work in order to help people, and cynically, they don’t want to be rendered redundant.

  The primary focus looks like workflow management, not diagnoses. E.g. how to reduce the amount of time various requests sit in a queue by figuring out which humans are most likely the ones who should be reading them.

  Also, predictive modelling, e.g. which patients are at elevated risk for bad outcomes. Or how many nurses to schedule for a particular shift. Though these don’t necessarily need AI/​ML and long predate AI/​ML.

  Then there are auto-suggestor/​auto-reminder use-cases: “You coded this patient as having diabetes without complications, but the text notes suggest diabetes with nephropathy, are you sure you didn’t mean to use that more specific code?”

  So, at least in the short term, AI apps will not have the opportunity to screw up in the immediately obvious ways like incorrect diagnoses or incorrect orders. It’s the more subtle screw-ups that I’m worried about at the moment.

[Question] Re­quest for com­ments/​opinions/​ideas on safety/​ethics for use of tool AI in a large health­care sys­tem.

• bokov 20 Sep 2023 11:24 UTC

  1 point

  on: Refram­ing Su­per­in­tel­li­gence: Com­pre­hen­sive AI Ser­vices as Gen­eral Intelligence

  Definition please.

  VNM

• bokov 3 Aug 2023 13:28 UTC

  15 points

  9

  on: What works for ADHD and/​or re­lated things?

  The first step is to see a psychiatrist and take the medication they recommend. For me it was an immediate night-and-day difference. I don’t know why the hell I wasted so much of my life before I finally went and got treatment. Don’t repeat my mistake.

• bokov 15 May 2023 15:53 UTC

  1 point

  0

  in reply to: the gears to ascension’s comment on: Con­trary to List of Lethal­ity’s point 22, al­ign­ment’s door num­ber 2

  Yes, OP

• bokov 11 Apr 2023 19:04 UTC

  1 point

  0

  on: Con­trary to List of Lethal­ity’s point 22, al­ign­ment’s door num­ber 2

  I actually tried running your essay through ChatGPT to make it more readable but it’s way too long. Can you at least break it into non-redundant sections not more than 3000 words each? Then we can do the rest.

• bokov 11 Apr 2023 18:57 UTC

  1 point

  0

  in reply to: the gears to ascension’s comment on: Con­trary to List of Lethal­ity’s point 22, al­ign­ment’s door num­ber 2

  I second that. I actually tried to read your other posts because I was curious to find out why you are getting downvoted—maybe I can learn something outside the LW party-line from you.

  But unfortunately, you don’t explain your position in clear, easy to understand terms so I’m going to have to put off sorting through your stuff until I have more time.

• bokov 5 Mar 2023 22:31 UTC

  1 point

  0

  in reply to: jimrandomh’s comment on: Is it time to talk about AI dooms­day prep­ping yet?

  I meant prepping metaphorically, in the see of being willing to delve into the specifics of a scenario most other people would dismiss as unwinnable. The reason I posted this is that though it’s obvious that the bunker approach isn’t really the right one, I’m drawing a blank for what the right approach would even look like.

  That being said, I figured into class of scenario might look identical to nuclear or biological war, only facilitated by AI. Are you saying scenarios where many but not all people die due to political/​economic/​environmental consequences of AI emergence are unlikely enough to disregard?

  So let’s talk about dystopias/​wierdtopias. Do you see any categories into which these can be grouped? The question then becomes, who will lose the most and who will lose the least under various types of scenarios.

Is it time to talk about AI dooms­day prep­ping yet?

• bokov 23 Nov 2022 19:20 UTC

  1 point

  0

  on: Why not more au­to­mated grenade drop UAVs in Ukraine?

  It’s ironic that you’re so excited about autonomous weapons but the first video you posted is a dramatic depiction created by a YouTube account called “Stop Autonomous Weapons”.

  I think the idea of this video was to scare the public by how powerful, precise, and possibly opaque these weapons are.

  But I agree with you—ethical or not, groups that limit their use of these weapons will be at a disadvantage against groups that do not. That’s a microcosm of the whole AI regulatory problem right there.