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by lm28469 1248 days ago
Look back at crypto and apply the same logic. It "changed everything" if you are part of the money makers, for the average joe nothing changed
2 comments

I don't understand these comparisons between crypto and generative AI models.

The AI models just seem so clearly and instantly more useful to me.

> useful to me.

To you yes. Now go out in the real world in which most people don't work in an office and mostly use internet for entertainment

Crypto seemed very useful to many people, and they still do, you'll find thousand upon thousands of comments and this very website preaching cryptos as the next game changer

Crypto looked useful as long as the price kept going up. Everyone likes free money.
That was the crass money-making part of it, but a lot of nerds earnestly believe(d) that cryptocurrencies would have massive world-changing consequences. I think it's increasingly obvious that there's little rational or empirical basis for such belief.

With AI, the biggest claims I see are overwhelmingly from people who are not doing cutting-edge work in the field, who have no real foundation for a belief that these AIs will continue to improve at a dramatic rate. Because to really change the world, they do need to get a lot better.

My personal excitement about language models is based on what they can do today.

I'm a big believer in the "capability overhang" idea, which is that the existing language models still have a huge array of capabilities that we haven't discovered yet.

That theory seems to be proved correct on a constant basis. Even the classic "let's think about this step by step" paper came out less than a year ago: https://arxiv.org/abs/2205.11916 - May 2022.

Couldn't agree more.

This paper (https://arxiv.org/abs/2206.07682) also touches on a pretty fascinating phenomenon - that when scaling up large language models they seem to "naturally" obtain new emergent abilities that do not exist on smaller models.

> Now go out in the real world in which most people don't work in an office and mostly use internet for entertainment

I wanted to refute your point by giving some YouTube videos about practical uses and their views. Then I checked YouTube's trending videos and compared the view counter to that of a PewDiePie video of 2 days ago and now I agree. You are right.

Eh, crypto is mostly useless I agree.

But honestly you sound just like someone in 1996 going "Oh the internet isn't going to change anything and is just a fad", and here we are decades later and the internet has changed almost everything in our lives. Every person you know uses the internet every day on their cellphones in one way or another.

Except good luck explaining bitcoin to someone non technical, but sit that same person down in front of Midjourney and have them prompt up some images and they'll have a great time.
I use chatgpt to write code. If it gets a bit better and can connected to an editor to create files, update existing files developer productivity will go through the roof
And we use hammers to hit on nails, you still need a knowledgeable/skilled person to build a proper house though
I have a website in development aidev.codes that automatically saves the output from OpenAI queries to files you specify (hosts them in a web page if it's that type of file). GitHub integration is one of many things I have planned. Today fixing some bugs with the knowledgebase stuff I just added yesterday and also putting in a template system. It has an !!edit command.

Also if you use vim you can try my npm package `askleo` `npm i -g askleo` (not tied to the website but requires your own OpenAI API key) with `:r ! askleo Go function to reverse a list of numbers` or whatever .

I already fear my productivity drop when OpenAI finally takes ChatGPT offline.
What sorts of things are you using it (successfully) for? I've gotten it to write a script or two for me, but it feels like usually I have to type out so much context (or domain/business knowledge) that it doesn't end up saving much effort.
I use it as an instant StackOverflow for the most part to get around new libraries or libraries/languages I don't use that often. Also generating custom bash one liners or small scripts. It is priceless for this use case. Yeah, sometimes it is wrong, but in my exp. less than 5%. Also we are lucky that for our purposes we can almost always validate the answer almost instantly and without incurring any cost.
Because you are a developer. Replace yourself with a product manager, and maybe you will start seeing things differently. I think in the long run LLMs will enable the real-deal NoCode solutions. You would probably need to write an essay to get it right, but you will just need to know a human language understood by the LLM and the business domain.
Thanks! That really had nothing to do with what I asked tho... This bit of thread is literally about using it to write code, so saying "pretend you're a PM" is not really relevant at all
What I meant is that your (our) job as a developer (in a mid-term future, I would say 10-12 years) will be made largely irrelevant, because a PM will be able to program by explaining what they wants to a LLM. That's why you are not seeing any real benefit from it now.
Is it better than Copilot?
I use it to generate whole test suites from function definitions. Not one test, but dozens, covering various inputs and edge cases. TDD purists will balk at that, but it saves serious amounts of typing out boilerplate. You have to recheck its suggestions, of course.

I couldn't get Copilot to spew anything like that (a single simple test at best, and it fails at that more frequently than it produces something useful).

It's also quite good at converting relatively simple programs or configs between languages. For example, I used it to convert PostgreSQL DDL queries into Hibernate models (and also in reverse), JS snippets into OCaml, XML into YAML, maven pom.xml into gradle build scripts, and a few more.

Different use case I think. With chatGPT you write something like:

write a function using the python requests library which makes a get request to the URL example.com, parses the JSON response and returns the value of the "foo" field. Throw an exception if the get request fails, the response is not JSON or is invalid JSON, or if the foo field is not present in the response.

I just tried this and got a correct (and reasonable) function on the first try.

This kind of high level description to low-level implementation is a huge timesaver but it saves time in a different way than copilot.