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OracleGPT: Thought Experiment on an AI Powered Executive

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Re: OracleGPT: Thought Experiment on an AI Powered Executive

#51

Post by stoneforger »

Guvante wrote: post #50
alexpotato wrote: post #29

You sometimes hear people say "I mean, we can't just give an AI a bunch of money/important decisions and expect it to do ok" but this is already happening and has been for years. Examples: - Algorithmic trading: I once embedded on an Options trading desk. The head of desk mentioned that he didn't really know what the PnL was during trading hours b/c the swings were so big that only the computer algos knew if the deci…

You gave examples of feedback loops. We know very well how to train computers to handle those effectively. Anything without quick feedback is much more difficult to do this way.

LLMs designing PID loops?

Re: OracleGPT: Thought Experiment on an AI Powered Executive

#52

Post by happymellon »

alexpotato wrote: post #41
pavel_lishin wrote: post #40

Earlier quoted context omitted.

But none of those things are AI in the same sense that we use the term now, to refer to LLMs.

But those things were considered on the same level of current LLMs in the sense of "well, a computer might do part of my job but not ALL of it". No, algorithmic trading didn't replace everything a trader did but it most certainly replaced large parts of the workload and made it much faster and horizontally scalable.

The problem here is that you are cherry picking examples of successful technology.

The inverse would be to list off Theranos, Google Stadia, and other failed tech and claim that people said that there was massive steps that subsequently didn't materialise. In fact a lot of times it was mostly fabricated by people with stuff to gain from ripping off VCs.

Look at how bad it is with Microsoft in Windows despite their "all in on AI".

Ultimately no one really knows how it will pan out, and if we will end up with Enron or an Apple. Or even if it's a combination of a successful tech that ultimately is mishandled by corporations and fails, or a limited tech that regardless captures the imagination through pop culture and takes over.

Re: OracleGPT: Thought Experiment on an AI Powered Executive

#53

Post by altmanaltman »

alexpotato wrote: post #29

You sometimes hear people say "I mean, we can't just give an AI a bunch of money/important decisions and expect it to do ok" but this is already happening and has been for years. Examples: - Algorithmic trading: I once embedded on an Options trading desk. The head of desk mentioned that he didn't really know what the PnL was during trading hours b/c the swings were so big that only the computer algos knew if the deci…

"Expert system" running a company is never going to happen unless shareholders are okay with no accountability from the company. You'll always need someone to blame in case things go wrong. You could have an executive using such an "expert system" for literally all their decisions, but it has to be a human being signing off on those decisions. There is no way to prosecute code and unless these expert systems can become sentinent or appear in court, best of luck trying to let it run a company in the real sense of actually making those decisions with full autonomy and responsbility.

Re: OracleGPT: Thought Experiment on an AI Powered Executive

#54

Post by pocketarc »

Terr_ wrote: post #33
zozbot234 wrote: post #23

The really nice thing about this proposal is that at least now we can all stop anthropomorphizing Larry Ellison, and give Oracle the properly robot-identifying CEO it deserves.

For those who haven't seen the reference: https://www.youtube.com/watch?v=-zRN7XLCRhc&t=38m27s

I think I've read the reference a hundred times throughout my time on HN, but had _never_ actually seen it, thank you for the link!

Re: OracleGPT: Thought Experiment on an AI Powered Executive

#55

Post by Guvante »

stoneforger wrote: post #51
Guvante wrote: post #50

Earlier quoted context omitted.

You gave examples of feedback loops. We know very well how to train computers to handle those effectively. Anything without quick feedback is much more difficult to do this way.

LLMs designing PID loops?

My point is the code for feedback loops is architecturally simple: when reading is wrong correct.

By boosting the accuracy and frequency of the reading you can get pretty good results.

But that has little to do with LLMs, or LLM generated code.

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