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TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

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Re: TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

#121

Post by PaulHoule »

aniviacat wrote: post #77
binocarlos wrote: post #30

Earlier quoted context omitted.

I would pay hundreds of dollars per month for the combination of cursor and claude - I could not get my head around it when my beginner lever colleague said "I just coded this whole thing using cursor". It was an entire web app, with search filters, tree based drag and drop GUIs, the backend api server, database migrations, auth and everything else. Not once did he need to ask me a question. When I asked him "how lon…

Current LLMs fail if what you're coding is not the most common of tasks. And a simple web app is about as basic as it gets. I've tried using LLMs for some libraries I'm working on, and they failed miserably. Trying to make an LLM implement a trait with a generic type in Rust is a game of luck with very poor chances. I'm sure LLMs can massively speed up tasks like front-end JavaScript development, simple Python script…

Roughly LLMs are great at things that involve a series of (near) 1-1 correspondences like “translate 同时采访了一些参与其中的活跃用户 to English” or “How do I move something up 5px in CSS without changing the rest of the layout?” but if the relationship of several parts is complex (those Rust traits or anything involving a fight with the borrow checker) or things have to go in some particular order it hasn’t seen (say US states in order of percent water area) they struggle.

SQL is a good target language because the translation from ideas (or written description) is more or less linear, the SQL engine uses entirely different techniques to turn that query into a set of relational operators which can be rewritten for efficiency and compiled or interpreted. The LLM and the SQL engine make a good team.

Re: TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

#122

Post by renegade-otter »

ema wrote: post #32
jsheard wrote: post #20

Earlier quoted context omitted.

There's no accounting for taste, but keep in mind that all of these services are currently losing money, so how much would you actually be willing to pay for the service you're currently getting in order to let it break even? There was a report that Microsoft is losing $20 for every $10 spent on Copilot subscriptions, with heavy users costing them as much as $80 per month. Assuming you're one of those heavy users, wo…

If it makes software developers 10% more productive there sure would be many companies who'd pay $80 a month per seat.

It's like saying "AI is going to replace book writers because they are so much more productive now". All you will get is more mediocre content that someone will have to fix later - the same with code.

10% more productive. What does that mean? If you mean lines of code, then it's an incredibly poor metric. They write more code, faster. Then what? What are the long-term consequences? Is it ultimately a wash, or even a detriment?

https://stackoverflow.blog/2024/03/22/is-ai-making-your-code...

Re: TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

#123

Post by stackghost »

slibhb wrote: post #108
bdndndndbve wrote: post #10

The current AI hype wave has really hit a nerd soft spot - that we're steps away from AGI. Surely if a computer can make plausible-looking but incorrect sentences we're days away from those sentences being factually accurate! The winter after this is gonna be harsh.

"Plausible-looking but incorrect sentences" is cheap, reflexive cynicism. LLMs are an incredible breakthrough by any reasonable standard. The reason to be optimistic about further progress is that we've seen a massive improvement in capabilities over the past few years and that seems highly likely to continue for the next few (at least). It's not going to scale forever, but it seems pretty clear that when the dust se…

>when the dust settles we'll have LLMs significantly more powerful than the current cutting edge -- which is already useful.

LLMs, irrespective of how powerful, are all subject to the fundamental limitation that they don't know anything. The stochastic parrot analogy remains applicable and will never be solved because of the underlying principles inherent to LLMs.

LLMs are not the pathway to AGI.

Re: TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

#125

Post by __alexs »

JanSt wrote: post #16
bdndndndbve wrote: post #10

The current AI hype wave has really hit a nerd soft spot - that we're steps away from AGI. Surely if a computer can make plausible-looking but incorrect sentences we're days away from those sentences being factually accurate! The winter after this is gonna be harsh.

Using Claude 3.5 Sonnet in Cursor Composer already shows huge benefits for coding. I'm more productive than ever before. The models are still getting better and better. I'm not saying AGI is right around the corner or that we will reach it, but the benefits are undeniable. o1 added test-time compute. No need to be snarky.

It's not snark, it's calling out a fundamental error of extrapolating a short term change in progress to infinity.

It's like looking at the first version of an IDE that got intellisense/autocomplete and deciding that we'll be able to write entire programs by just pressing tab and enter 10,000 times.

Re: TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

#126

Post by __alexs »

slibhb wrote: post #108
bdndndndbve wrote: post #10

The current AI hype wave has really hit a nerd soft spot - that we're steps away from AGI. Surely if a computer can make plausible-looking but incorrect sentences we're days away from those sentences being factually accurate! The winter after this is gonna be harsh.

"Plausible-looking but incorrect sentences" is cheap, reflexive cynicism. LLMs are an incredible breakthrough by any reasonable standard. The reason to be optimistic about further progress is that we've seen a massive improvement in capabilities over the past few years and that seems highly likely to continue for the next few (at least). It's not going to scale forever, but it seems pretty clear that when the dust se…

> "Plausible-looking but incorrect sentences" is cheap, reflexive cynicism. LLMs are an incredible breakthrough by any reasonable standard

No it isn't. The previous state of the art was markov chain level random gibberish generation. What OP described is an enormous step up from that.

Re: TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

#127

Post by znpy »

aniviacat wrote: post #77
binocarlos wrote: post #30

Earlier quoted context omitted.

I would pay hundreds of dollars per month for the combination of cursor and claude - I could not get my head around it when my beginner lever colleague said "I just coded this whole thing using cursor". It was an entire web app, with search filters, tree based drag and drop GUIs, the backend api server, database migrations, auth and everything else. Not once did he need to ask me a question. When I asked him "how lon…

Current LLMs fail if what you're coding is not the most common of tasks. And a simple web app is about as basic as it gets. I've tried using LLMs for some libraries I'm working on, and they failed miserably. Trying to make an LLM implement a trait with a generic type in Rust is a game of luck with very poor chances. I'm sure LLMs can massively speed up tasks like front-end JavaScript development, simple Python script…

I had similar experiences:

1. Aasked ChatGPT to write a simple echo server in C but with this twist: use io_uring rather than the classic sendmsg/recvmsg. The code it spat out wouldn't compile, let alone work. It was wrong on many points. It was clearly pieces of who-knows-what cut and pasted together. However after having banged my head on the docs for a while I could clearly determine from which sources the code io_uring code segments were coming. The code barely made any sense and it was completely incorrect both syntactically and semantically.

2. Asked another LLM to write an AWS IAM policy according to some specifications. It hallucinated and used predicates that do not exist at all. I mean, I could have done it myself if I just could have made predicates up.

> But for anything even mildly complex, LLMs are still not suited.

Agreed, and I'm not sure we are any close to them being.

Re: TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

#128

Post by abm53 »

ben_w wrote: post #82
aniviacat wrote: post #77

Earlier quoted context omitted.

Current LLMs fail if what you're coding is not the most common of tasks. And a simple web app is about as basic as it gets. I've tried using LLMs for some libraries I'm working on, and they failed miserably. Trying to make an LLM implement a trait with a generic type in Rust is a game of luck with very poor chances. I'm sure LLMs can massively speed up tasks like front-end JavaScript development, simple Python script…

> Current LLMs fail if what you're coding is not the most common of tasks Succeeding on the most common tasks (which isn't exactly what you said) is identical to "they're useful".

And I would go further… these “common tasks” cover 80% of the work in even the most demanding engineering or research positions.

Re: TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

#129

Post by stackghost »

AlexandrB wrote: post #23

It's ironic that Sam Altman's background is in YC, because this is the opposite of startup thinking. Instead of scrappy disruption he seems to want massive investment upfront with only vague ideas of what the technology could be used for.

>he seems to want massive investment upfront with only vague ideas of what the technology could be used for

That sounds exactly like venture-funded startup thinking to me.

Re: TSMC execs allegedly dismissed OpenAI CEO Sam Altman as 'podcasting bro'

#130

Post by ramraj07 »

stackghost wrote: post #123
slibhb wrote: post #108

Earlier quoted context omitted.

"Plausible-looking but incorrect sentences" is cheap, reflexive cynicism. LLMs are an incredible breakthrough by any reasonable standard. The reason to be optimistic about further progress is that we've seen a massive improvement in capabilities over the past few years and that seems highly likely to continue for the next few (at least). It's not going to scale forever, but it seems pretty clear that when the dust se…

>when the dust settles we'll have LLMs significantly more powerful than the current cutting edge -- which is already useful. LLMs, irrespective of how powerful, are all subject to the fundamental limitation that they don't know anything. The stochastic parrot analogy remains applicable and will never be solved because of the underlying principles inherent to LLMs. LLMs are not the pathway to AGI.

Noam Chomsky and Doug Hofstader had the same opinion. Last I checked Doug has recanted his skepticism and is seriously afraid for the future of humanity. I’ll listen to him and my own gut than some random internet people still insisting this is all a nothing burger.
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