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What if A.I. doesn't get better than this?

newyorker.com

11–20 of 119 posts

Re: What if A.I. doesn't get better than this?

#11

The title is irritating, conflating AI with LLMs. LLMs are a subset of AI. I expect future systems will be mobs of expert AI agents rather than relying on LLMs to do everything. An LLM will likely be in the mix for at least the natural language processing but I wouldn't bet the farm on them alone.

That battle was long-ago lost when the leading LLM companies and organizations insisted on referring to their products and models solely as "AI", not the more-specific "LLMs". Implementers of that technology followed suit, and that's just what it means now.

You can't blame the New Yorker for using the term in its modern, common parlance.

Re: What if A.I. doesn't get better than this?

#12
post #5

> You didn’t need a bar chart to recognize that GPT-4 had leaped ahead of anything that had come before. You did though. I remember when GPT-4 was announced, OpenAI downplayed it and Altman said the difference was subtle and wouldn't be immediately apparent. For a lot of the stuff ChatGPT was being used for the gap between 3 and 4 wasn't going to really leap out at you. https://fortune.com/2023/03/14/openai-releases-…

> Back then people were happy if they got models to write a small simple function and it worked. Now they expect models to manipulate large production codebases and get it right first time. This push is mostly coming from the C-level and the hustler types, both of which need this to work out in order for their employeeless corporation fantasy to work out.

I'm not going to say that nobody is expecting it to do these things, but I don't think they should. It's still unable to write a simple function.

What we've seen isn't a reasonable increase in expectations based upon validation of previous experiments. Instead it's racking up of expectations by all the signals of success. When they time and time again take in more VC cash at ever greater valuations, we are forced to assume they want to do something more, and since they get the cash we have to assume somebody believes them.

Its a pyramid scheme, but instead of paying out earlier investors with the later investors cash its a confidence pyramid scheme. They obsolete the previous investors valuations by making bigger claims with larger expectations. Then they use those larger expectations as proof they already fulfilled the previous expectations.

Re: What if A.I. doesn't get better than this?

#13
OpenAi has 700+ million users. Sam recently said only 7% of Plus users were using thinking (o3)!!! That means 93% of their users were using nothing but 4o!

Clearly the OpenAi leadership saw these stats and understood the main initial goal of GPT5 is to introduce this auto-router, and not go all in on intelligence for the 3-7% who care to use it.

This is a genius move IMO, and will get tons of users to flood to ChatGPT over competitors. Grok, Gemini, etc are now fighting over scraps of the top 1% while OpenAi is going after the blue ocean of users.

Re: What if A.I. doesn't get better than this?

#14
post #7

>What If A.I. Doesn't Get Better Than This? What if it does? There's a certain type of fear . . . "It's the fear . . . they're gonna take my job away . . . " It's the fear . . . I'll be working here the rest of my days . . . " -- David Fahl Same fear, different day.

Because every s-curve looks like an exponent for those in the start. I mean look at the first plane, then first air-jets: it’s understandable to assume we would travel the galaxy in something like 2050. Meanwhile planes are basically the same last 60 years. LLMs are great but I firmly believe that in 2100 all is basically the same as in 2020: no free energy (fusion), no AGI.

[dead]

Re: What if A.I. doesn't get better than this?

#15
What happens is they go out of business: "these firms spent five hundred and sixty billion dollars on A.I.-related capital expenditures in the past eighteen months, while their A.I. revenues were only about thirty-five billion."

DeepSeek (and the like) will prevent the kind of price increases necessary for them to pay back hundreds of billions of dollars already spent, much less pay for more. If they don't find a way to make LLMs do significantly more than they do thus far, and a market willing to pay hundreds of billions of dollars for them to do it, and some kind of "moat" to prevent DeepSeek and the like from undercutting them, they will collapse under the weight of their own expenses.

Re: What if A.I. doesn't get better than this?

#16

The title is irritating, conflating AI with LLMs. LLMs are a subset of AI. I expect future systems will be mobs of expert AI agents rather than relying on LLMs to do everything. An LLM will likely be in the mix for at least the natural language processing but I wouldn't bet the farm on them alone.

A* search, literally textbook AI, is still doing great work.

Re: What if A.I. doesn't get better than this?

#17

>What If A.I. Doesn't Get Better Than This? What if it does? There's a certain type of fear . . . "It's the fear . . . they're gonna take my job away . . . " It's the fear . . . I'll be working here the rest of my days . . . " -- David Fahl Same fear, different day.

Nah, I'm not afraid of working here the rest of my days. Consistent paycheck, benefits, challenging-but-rewarding work.

If you provide people with that they typically shut up and stay out of the way. Everyone should be more afraid of the former than the latter.

Re: What if A.I. doesn't get better than this?

#18

OpenAi has 700+ million users. Sam recently said only 7% of Plus users were using thinking (o3)!!! That means 93% of their users were using nothing but 4o! Clearly the OpenAi leadership saw these stats and understood the main initial goal of GPT5 is to introduce this auto-router, and not go all in on intelligence for the 3-7% who care to use it. This is a genius move IMO, and will get tons of users to flood to ChatGP…

If they're not paying users then they're just a liability.

Re: What if A.I. doesn't get better than this?

#20
My current intuition on this topic is that they are right about scaling but they are training on the wrong data.

LLMs were not intended to be the core foundation of artificial intelligence but an experiment around deep learning and language. Its success was an almost accidental byproduct of the availability of large amount of structured data to train from and the natural human bias to be tricked by language (Eliza effect).

But human language itself is quite weak from a cognitive perspective and we end up with an extremely broad but shallow and brittle model. The recent and extremely costly attempts to build reasoning around don't seem much more promising than using a lot of hardcoded heuristics, basically ignoring the bitter lesson.

I've seen many argue that a real human level AI should be trained from real-world experience, I am not sure this is true, but training should likely start from lower-level data than language, still using tokens and huge scale, and probably deeper networks.

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