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An interesting opinion on hype/no hype.

"I don't think that "AI" models [a] (by which I mean: large language models) are over-hyped.

Yes, it's true that any new technology will attract the grifters. And it is definitely true that many companies like to say they're "Using AI" in the same way they previously said they were powered by "The Blockchain". (As we've seen again, and again, and again, and again.) It's also the case we may be in a bubble. The internet was a bubble that burst in 2000, but the Internet applications we now have are what was previously the stuff of literal science fiction.

But the reason I think that the recent advances we've made aren't just hype is that, over the past year, I have spent at least a few hours every week interacting with various large language models, and have been consistently impressed by their ability to solve increasingly difficult tasks I give them. And as a result of this, I would say I'm at least 50% faster at writing code for both my research projects and my side projects as a result of these models.

Most of the people online I find who talk about LLM utility are either wildly optimistic, and claim all jobs will be automated within three years, or wildly pessimistic, and say they have contributed nothing and never will.

So in this post, I just want to try and ground the conversation. I'm not going to make any arguments about what the future holds. I just want to provide a list of 50 conversations that I (a programmer and research scientist studying machine learning) have had with different large language models to meaningfully improve my ability to perform research and help me work on random coding side projects."

https://nicholas.carlini.com/writing/2024/how-i-use-ai.html

Carlini

How I Use "AI"

I don't think that AI models (by which I mean: large language models) are over-hyped. In this post I will list 50 ways I've used them.

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www.tgoop.com/gonzo_ML/2901

11.3K viewsAug 9, 2024 at 15:45

An interesting opinion on hype/no hype.

"I don't think that "AI" models [a] (by which I mean: large language models) are over-hyped.

Yes, it's true that any new technology will attract the grifters. And it is definitely true that many companies like to say they're "Using AI" in the same way they previously said they were powered by "The Blockchain". (As we've seen again, and again, and again, and again.) It's also the case we may be in a bubble. The internet was a bubble that burst in 2000, but the Internet applications we now have are what was previously the stuff of literal science fiction.

But the reason I think that the recent advances we've made aren't just hype is that, over the past year, I have spent at least a few hours every week interacting with various large language models, and have been consistently impressed by their ability to solve increasingly difficult tasks I give them. And as a result of this, I would say I'm at least 50% faster at writing code for both my research projects and my side projects as a result of these models.

Most of the people online I find who talk about LLM utility are either wildly optimistic, and claim all jobs will be automated within three years, or wildly pessimistic, and say they have contributed nothing and never will.

So in this post, I just want to try and ground the conversation. I'm not going to make any arguments about what the future holds. I just want to provide a list of 50 conversations that I (a programmer and research scientist studying machine learning) have had with different large language models to meaningfully improve my ability to perform research and help me work on random coding side projects."

https://nicholas.carlini.com/writing/2024/how-i-use-ai.html

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