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AI companies are pivoting from creating gods to building products

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Re: AI companies are pivoting from creating gods to building products

#61

Post by hx2a »

MattGaiser wrote: post #50
hx2a wrote: post #43

Earlier quoted context omitted.

And yet, generative AI also seems to be poor at randomness. When I ask Google Gemini for a list of 50 random words, it gave me a list of 18 unique words, with 16 of them repeated exactly 3 times. Abyss: 1 Ambiguous: 3 Cacophony: 3 Crescendo: 3 Ephemeral: 3 Ethereal: 3 Euphoria: 3 Labyrinth: 3 Maverick: 3 Melancholy: 3 Mellifluous: 3 Nostalgia: 3 Oblivion: 3 Paradox: 3 Quixotic: 1 Serendipity: 3 Sublime: 3 Zenith: 3

Are you using regular or pro? As pro has no issues with this task.

Regular user. For useful tasks, how much of a difference does the Pro plan make?

Re: AI companies are pivoting from creating gods to building products

#63

Post by mondrian »

BobbyJo wrote: post #31
rustypotato wrote: post #26

> But when developers put AI in consumer products, people expect it to behave like software, which means that it needs to work deterministically. If your AI travel agent books vacations to the correct destination only 90% of the time, it won’t be successful. This is the fundamental problem that prevents generative AI from becoming a "foundational building block" for most products. Even with rigorous safety measures i…

I've made this statement a bunch in other mediums: The reason AI software is always "AI software" and not just a useful product is because AI is fallible. The reason we can build such deep and complex software system is because each layer can assume the one below it will "just work". If it only worked 99% of the time, we'd all still be interfacing with assembly, because we'd have to be aware of the mistakes that were…

Recent work from Meta uses AI to automatically increase test coverage with zero human checking of AI outputs. They do this with a strong oracle for AI outputs: whether the AI-generated test compiles, runs, and hits yet-unhit lines of code in the tested codebase.

We probably need a lot more work along this dimension of finding use cases where strong automatic verification of AI outputs is possible.

Re: AI companies are pivoting from creating gods to building products

#64

Post by freejazz »

simonw wrote: post #57
hx2a wrote: post #43

Earlier quoted context omitted.

And yet, generative AI also seems to be poor at randomness. When I ask Google Gemini for a list of 50 random words, it gave me a list of 18 unique words, with 16 of them repeated exactly 3 times. Abyss: 1 Ambiguous: 3 Cacophony: 3 Crescendo: 3 Ephemeral: 3 Ethereal: 3 Euphoria: 3 Labyrinth: 3 Maverick: 3 Melancholy: 3 Mellifluous: 3 Nostalgia: 3 Oblivion: 3 Paradox: 3 Quixotic: 1 Serendipity: 3 Sublime: 3 Zenith: 3

Randomness is difficult. I wouldn't expect any LLM to be able to reliably produce random anything, except in the cases where they have access to tools (ChatGPT Code Interpreter could use Python's random.random() for example).

Okay, but repeating words?

Re: AI companies are pivoting from creating gods to building products

#65

Post by cooperx »

ryandrake wrote: post #34

Companies keep going at it the wrong way. Instead of saying "We have AI, let's find products we can make out of AI!" they should be saying, "What products do people want, let's use whatever tools we have (including maybe AI) to make them." The idea that a company is an AI company should be as ridiculous as a company being a Python company. "We are Python-first, have Python experts, and all of our products are made wi…

Its the same as all the "we are a blockchain company" startups that popped up looking for a problem to solve with their tech rather than the right way round.

However, a lot of those got a bunch of investment or made some decent money in the short term. Very few are still around. We will see the same pattern here.

Re: AI companies are pivoting from creating gods to building products

#66

Post by dragontamer »

necroforest wrote: post #49
ryandrake wrote: post #34

Companies keep going at it the wrong way. Instead of saying "We have AI, let's find products we can make out of AI!" they should be saying, "What products do people want, let's use whatever tools we have (including maybe AI) to make them." The idea that a company is an AI company should be as ridiculous as a company being a Python company. "We are Python-first, have Python experts, and all of our products are made wi…

I don't entirely disagree with you, but "what products do people want" is overly conservative. Pre-ChatGPT, very few people wanted a (more or less) general purpose chatbot.

One of my local car dealerships is using an chat system of some kind (probably an LLM?).

It's awful and a complete waste of time. I'm not sure if LLMs are getting good use yet / general chatbots are good or ready for business use.

Re: AI companies are pivoting from creating gods to building products

#67

Post by lispisok »

ryandrake wrote: post #34

Companies keep going at it the wrong way. Instead of saying "We have AI, let's find products we can make out of AI!" they should be saying, "What products do people want, let's use whatever tools we have (including maybe AI) to make them." The idea that a company is an AI company should be as ridiculous as a company being a Python company. "We are Python-first, have Python experts, and all of our products are made wi…

You're suggesting boring business way to do things. The tech ecosystem is full of startups doing that ridiculous thing you said chasing the hot new thing and raising huge amounts of money off the hype. This AI hype cycle is really bad and before that we had cryptocurrency.

Re: AI companies are pivoting from creating gods to building products

#68

Post by MattGaiser »

hx2a wrote: post #61
MattGaiser wrote: post #50

Earlier quoted context omitted.

Are you using regular or pro? As pro has no issues with this task.

Regular user. For useful tasks, how much of a difference does the Pro plan make?

Nowhere near as good as ChatGPT 4o or Claude (in not one case have I had it outperform those other two), but at least it can do math and data science correctly most of the time compared to the regular model.

I use it as a secondary when the other two are chewing on other tasks already.

I only own it as I am an outrageously heavy consumer of LLMs for all sorts of little projects at once and they all seem to pause one window if you use another.

Re: AI companies are pivoting from creating gods to building products

#69

Post by wokwokwok »

necroforest wrote: post #49
ryandrake wrote: post #34

Companies keep going at it the wrong way. Instead of saying "We have AI, let's find products we can make out of AI!" they should be saying, "What products do people want, let's use whatever tools we have (including maybe AI) to make them." The idea that a company is an AI company should be as ridiculous as a company being a Python company. "We are Python-first, have Python experts, and all of our products are made wi…

I don't entirely disagree with you, but "what products do people want" is overly conservative. Pre-ChatGPT, very few people wanted a (more or less) general purpose chatbot.

To be fair, the overwhelming feedback appears to be that people dont want a general purpose chatbot in every product and website, especially when it's labelled 'AI'.

So... certainly there's a space for new products.

...but perhaps for existing products, it's not as simple as 'slap some random AI on it and hope you ride the wave of AI'.

Re: AI companies are pivoting from creating gods to building products

#70

Post by wruza »

BobbyJo wrote: post #54
loa_in_ wrote: post #35

Earlier quoted context omitted.

But software works only 99% of the time. For some definition of work: 99% of days it's run, 99% of clicks, 99% of CPU time in given component, 99% of versions released and linked into some business' production binary, 99% of github tags, 99% of commits, 99% of software that that one guy says is battle-tested

Do you have to write your code presuming that sometimes 'a + b' will be wrong? I don't. Software pretty much always "works" when you consider the definition of work to be "does what the programmer told it too". AI? Not so much.

It’s all about limits and edge cases. a+b may “fail” at INT_MAX and at 0.1+0.2. You don’t `==` your doubles, you don’t (a+b)/2 your mid, and you don’t ask ai to just book you vacation. You ask it to “collect average sentiment from `these_5k_reviews()` ignoring apparently fake ones, which are defined as ”. You don’t care about determinism because it’s a statistical instrument.
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