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AI is a floor raiser, not a ceiling raiser

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Re: AI is a floor raiser, not a ceiling raiser

#121

Post by exasperaited »

jjk166 wrote: post #102
exasperaited wrote: post #45

Earlier quoted context omitted.

Opposite of "inter-" is "intra-". Intraloper, weirdly enough, is a word in use.

"inter-" means between, "intra-" means within, "extra-" means outside. "intra-" and "inter" aren't quite synonyms but they definitely aren't opposites of eachother.

Inter- implies relationships between entities, intra- implies relationships within entities.

In any single sentence context they cannot refer to the same relationships, and that which they are not is precisely the domain of the other word: they are true antonyms.

Re: AI is a floor raiser, not a ceiling raiser

#122

Post by hirvi74 »

pcrh wrote: post #41
andrenotgiant wrote: post #8

This tracks for other areas of AI I am more familiar with. Below average people can use AI to get average results.

This is in line with another quip about AI: You need to know more than the LLM in order to gain any benefit from it.

I am not certain that is entirely true.

I suppose it's all a matter of what one is using an LLM for, no?

GPT is great at citing sources for most of my requests -- even if not always prompted to do so. So, in a way, I kind of use LLMs as a search engine/Wikipedia hybrid (used to follow links on Wiki a lot too). I ask it what I want, ask for sources if none are provided, and just follow the sources to verify information. I just prefer the natural language interface over search engines. Plus, results are not cluttered with SEO ads and clickbait rubbish.

Re: AI is a floor raiser, not a ceiling raiser

#123

Post by leptons »

falcor84 wrote: post #38
itsoktocry wrote: post #12

Earlier quoted context omitted.

That explains why people here are against it, because everyone is above average I guess.

I'm not against it. I wonder where in the distribution it puts me.

At the "Someone willing to waste their time with slop" end?

Re: AI is a floor raiser, not a ceiling raiser

#124

Post by stillpointlab »

recursive wrote: post #119
stillpointlab wrote: post #92

Earlier quoted context omitted.

Not to slip too far into analogy, but that argument feels a bit like a horse-drawn carriage operator saying he can't wait to pick up all of the stranded car operators when their mechanical contraptions break down on the side of the road. But what happened instead was the creation of a brand new job: the mechanic. I don't have a crystal ball and I can't predict the actual future. But I can see the list of potential fu…

Both can be true. There were probably a significant number of stranded motorists that were rescued by horse-powered conveyance. And eventually cars got more convenient and reliable. I just wouldn't want to be responsible for servicing a guarantee about the reliability of early cars. And I'll feel no sense of vindication if I do get that support case. I will probably just sigh and feel a little more tired.

Yes, the whole point that it is true. But only for a short window.

So consider differing perspectives. Like a teenage kid that is hanging around the stables, listening to the veteran coachmen laugh about the new loud, smoky machines. Proudly declaring how they'll be the ones mopping up the mess, picking up the stragglers, cashing it in.

The career advice you give to the kid may be different than the advice you'd give to the coachman. That is the context of my post: Andrew Ng isn't giving you advice, he is giving advice to people at the AI school who hope to be the founders of tomorrow.

And you are probably mistaken if you think the solution to the problems that arise due to LLMs will result in those kids looking at the past. Just like the ultimate solution to car reliability wasn't a return to horses but rather the invention of mechanics, the solution to problems caused by AI may not be the return to some software engineering past that the old veterans still hold dear.

Re: AI is a floor raiser, not a ceiling raiser

#125

Post by michaelhoney »

I think all of this is true, but the shape of the chart changes as AI gets better.

Think of how a similar chart for chess/go/starcraft-playing proficiency has changed over the years.

There will come a time when the hardest work is being done by AI. Will that be three years from now or thirty? We don't know yet, but it will come.

Re: AI is a floor raiser, not a ceiling raiser

#126

Post by [deleted] »

esafak wrote: post #63
nwienert wrote: post #26

Earlier quoted context omitted.

Let's look: GPT-1 June 2018 GPT-2 February 2019 GPT-3 November 2021 GPT-4 March 2023 Claude tells me this is the rough improvement of each: GPT-1 to 2: 5-10x GPT-2 to 3: 10-20x GPT 3 to 4: 2-4x Now it's been 2.5 years since 4. Are you expecting 5 to be 2-4x better, or 10-20x better?

How are you measuring this improvement factor? We have numerous benchmarks for LLMs and they are all saturating. We are rapidly approaching AGI by that measure, and headed towards ASI. They still won't be "human" but they will be able to do everything humans can, and more.

[deleted]

Re: AI is a floor raiser, not a ceiling raiser

#127

Post by emporas »

smiley1437 wrote: post #31
LeftHandPath wrote: post #27

There are some things that you still can't do with LLMs. For example, if you tried to learn chess by having the LLM play against you, you'd quickly find that it isn't able to track a series of moves for very long (usually 5-10 turns; the longest I've seen it last was 18) before it starts making illegal choices. It also generally accepts invalid moves from your side, so you'll never be corrected if you're wrong about…

> people aren't aware of how wrong they can be, and the errors take effort and knowledge to notice. I have friends who are highly educated professionals (PhDs, MDs) who just assume that AI\LLMs make no mistakes. They were shocked that it's possible for hallucinations to occur. I wonder if there's a halo effect where the perfect grammar, structure, and confidence of LLM output causes some users to assume expertise?

It is only in the last century or so, that statistical methods were invented and applied. It is possible for many people to be very competent at what they are doing and at the same time be totally ignorant of statistics.

There are lies, statistics and goddamn hallucinations.

Re: AI is a floor raiser, not a ceiling raiser

#128

Post by skmurphy »

bayindirh wrote: post #47
falcor84 wrote: post #36

Earlier quoted context omitted.

Great point, but just mentioning (nitpicking?) that I never heard about machines/containers referred to as "livestock", but rather in my milieu it's always "pets" vs "cattle". I now wonder if it's a geographical thing.

Yeah, the CERN talk* [0] coined the term Pets vs. Cattle analogy, and it was way before VMs were cheap on bare metal. I think the word just evolved as the idea got rooted in the community. We use the same analogy for the last 20 years or so. Provisioning 150 cattle servers take 15 minutes or so, and we can provision a pet in a couple of hours, at most. [0]: https://www.engineyard.com/blog/pets-vs-cattle/ *: Engine Ya…

Randy Bias also claims authorship https://cloudscaling.com/blog/cloud-computing/the-history-of...

this tweet by Tim Bell seems to indicate shared credit with Bill Baker and Randy Bias

https://x.com/noggin143/status/354666097691205633

@randybias @dberkholz CERN's presentation of pets and cattle was derived from Randy's (and Bill Baker's previously).

Re: AI is a floor raiser, not a ceiling raiser

#129

Post by skmurphy »

stillpointlab wrote: post #29

This mirrors insights from Andrew Ng's recent AI startup talk [1]. I recall he mentions in this video that the new advice they are giving to founders is to throw away prototypes when they pivot instead of building onto a core foundation. This is because of the effects described in the article. He also gives some provisional numbers (see the section "Rapid Prototyping and Engineering" and slides ~10:30) where he sugge…

Thanks for pointing this out. I think this is an insightful analogy. We will likely manage generated code in the same way we manage large cloud computing complexes.

This probably does not apply to legacy code that has been in use for several years where the production deployment gives you a higher level of confidence (and a higher risk of regression errors with changes).

Have you blogged about your insights, the https://stillpointlab.com site is very sparse as is @stillpointlab

Re: AI is a floor raiser, not a ceiling raiser

#130

Post by Lerc »

gruez wrote: post #50

The blog post has a bunch of charts, which gives it a veneer of objectivity and rigor, but in reality it's just all vibes and conjecture. Meanwhile recent empirical studies actually point in the opposite direction, showing that AI use increases inequality, not decrease it. https://www.economist.com/content-assets/images/20250215_FNC... https://www.economist.com/finance-and-economics/2025/02/13/h...

In a sense I agree. I don't necessarily think that it has to be the case, but I got that same feeling of that it was wearing a white lab coat to be a scientist. I think their honest attempt was to express the relationship of how they perceive things.

I think this could still be used as a valuable form of communication if you can clearly express the idea that this is representing a hypothesis rather than a measurement. The simplest would be to label the graphs as "hypothesis". but a subtle but easily identifiable visual change might be better.

Wavy lines for the axis spring to mind as an idea to express that. I would worry about the ability to express hypotheses about definitive events that happen when a value crosses an axis though, You'd probably want a straight line for that. Perhaps it would be sufficient to just have wavy lines at the ends of the axes beyond the point at which the plot appears.

Beyond that. I think the article presumes the flattening of the curve as mastery is achieved. I'm not sure that's a given, perhaps it seems that way because we evaluate proportional improvement, implicitly placing skill on a logarithmic scale.

I'd still consider the post from the author as being done in better faith than the economist links.

Id like to know what people think, and for them to say that honestly. If they have hard data, they show it and how it confirms their hypothesis. At the other end of the scale is gathering data and only exposing the measurements that imply a hypothesis that you are not brave enough to state explicitly.

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