The other problem is that unless we hit AGI real fast the quality can go nowhere but down, there will be less and less non polluted data to train from, the code bases will become more and more bloated because let's be real LLMs don't produce very good code, &c.

In the meantime we're left with AI generated scams, AI generated cooking recipes which don't work, AI generated art that look like ass, AI bots flooding social media, &c.

The internet, email, Gmail, smartphones were some kind of revolution because it would help me. AI is only here to prevents me from thinking instead of improving my life one way or another.

All is see is preventing me from doing what I do, potential hallucinations that can harm work and relationships, and decreasing the quality of that work (especially SWE which is lowering every decade). That’s a bad kind of revolution.

Lol get a grip. Jeff Dean just said 25% of the code being checked into Google's internal codebase is now AI generated. If you think it's just kids using it for homework and engineers saving a few minutes here and there you're kidding yourself.

https://www.dwarkeshpatel.com/p/jeff-dean-and-noam-shazeer

>I am hopeful for some of the more advanced applications, e.g. proof assistance in math,

"I expect, say, 2026-level AI, when used properly, will be a trustworthy co-author in mathematical research, and in many other fields as well." You just aren't in the same universe as what the top experts are saying about this tech.

https://unlocked.microsoft.com/ai-anthology/terence-tao/

You seem like one of those people that used GPT3.5 once and hasn't updated at all since then. You're criticizing the wright flyer and we're already at turboprops.

This assertion feels misleading. When I worked at a FAANG, 10% of our codebase was generated Protobuf. Obviously, this was highly repetitive boilerplate that was equivalent to maybe a few thousand actual lines of code. What does the 25% of LLM-generated code actually look like? I'm guessing it's doing nothing particularly novel or interesting. (Also, I have to wonder if a large chunk of that 25% could be encapsulated as a more reliable and deterministic abstraction.)

All advancements in "AI" in the last year or so were in smaller models becoming more powerful, more companies reaching openai levels and a bit more accuracy. I think this is the plateau for the current theoretical tech.

+: one case I bumped into today: socks5 with the latest hyper version to proxy https requests. All models were completely off-track. None was able to make any functioning implementation. This is just a few lines of code.

LLMs as we have them now are the application which makes a computer be able to understand a non-programmer and to communicate to a non-programmer, it is the new eyes, ears and mouth of computers.

This works so well, that it can already pretend to be a human. This is like realizing: Yes, in fact, this mouse allows me to move a cursor in the computer with which I can click on an application, as if it were my finger in the computer.

But I guess it will ultimately be agents what will show the true power of this new interface. Agents which assist you with your memory by properly reminding you of things, by allowing you to ask it things while you are leaving the house and so on, it even contacting other agents or even persons in order to answer your questions or execute what you asked it to.

How can this not be world-changing?

Perhaps more people should heed the 'AI' skeptics. Just because we can do something doesn't mean we should.

For one, the principal-agent problem. Who's building, running, and maintaining these agents? I doubt that these are running locally and tweaked by the user themselves. The business model is to sell these things as a service running in the cloud. That means the operator has final say on how these systems are implemented. Sure, your helpful AI agent today may remind you to pick up some soda at the store. But if the last decade+ of "enshittification" has shown, it's only a matter of time before your helpful AI agent will remind you to pick up some delicious Mountain Dew (TM) at the Piggly Wiggly (TM) and use your American Express (TM) card to earn Roblox (TM) points.

And even if we assume these agents don't eventually come to serve masters other than the end-user, the internet is already a user-hostile place. It's entirely reasonable to believe it'll be agent-hostile too, where APIs and UI designs adapt to trick AI agents with "dark patterns" to do things that aren't necessarily in their users' best interests.

Techno-utopianism might feel good, but economics and money-making will drive how these things actually play out.

Like phones can be, but give that to an unsupervised 10 years old and it's not a given that the outcome will be a net positive

Keep in mind also that it's in vogue to talk about AI bad, and taboo to talk about how much you use it in your job or life.

"Our app leverages AI to make you better!"

versus

"Our app written by AI makes you better!"

The first one catches eyes, the second one is just a turn off.

If you're writing software and not using LLMs, you're working at a fraction of the pace of those that do. While it's not going to create some world-changing algo today, it completely eliminates most of the boiler plate you need to type out, makes implementing tests much, much faster. At least that has been my experience in Golang at work.

Maybe so for you, but you might want to think about why your work involved so much boilerplate and routine content in the first place. If so much of it is easily completed by an LLM already, was your employer really paying you some large share of your 5-6 digits of compensation for every year? Do you think most of your value to the company has just been in typing boilerplate and mindlessly generating tests until now?

Personally, I'd feel pretty insecure in my career and underdeveloped in my trade if I could answer yes to that.

If it does apply to you (or others reading this), hopefully you can exploit this brief window of gained personal productivity to develop more valuable skills and get your tasked to more valuable roles asap. Software engineering as a profession isn't going anywhere, but the people most helped by today's fairly primitive LLM coding assistants are the ones that are actually vulnerable to be squeezed out of the trade because it means they're the not actually contributing very much specific expertise.

The productivity change you've experienced should be taken as a bright red warning flag that you've unwittingly settled into a role as an technician getting paid highly because of ephemeral demand bubble rather than the valuable engineer you might imagine yourself to be.

Many of those tasks can be completed via normal copy and paste. It's much faster to have the LLM do it. When you're initializing a client for a database in go, you can refer to the library on how to do it, or you can just let the LLM do it.

Maybe you have a photographic memory and you don't need to reference docs for other people's libraries, I don't have that ability. But the LLMs do, so I use them.

So the mere existence of “worthless” churn in your job isn’t evidence that you aren’t solving business problems that are worthy of pay.

To put it another way. Most jobs exist to make a problem go away for an executive.

I understand you are also getting at the ethos of good engineering and encouraging this person to take pride in their work.

> you've unwittingly settled into a role as an technician getting paid highly because of ephemeral demand bubble rather than the valuable engineer you might imagine yourself to be.

I have not seen this put so succinctly and this cannot be repeated enough.

Why not talk about the other side of the coin - things that have been predicted to be amazing and fell flat, like Pets.com and Alexa?

LLMs goes from coding by myself to shutting down my brain and generating bad code. I don’t see how you can compare both.

The enshittification of search and Quora means that outside of Wikipedia and sometimes Reddit, the Internet's offer of "access to all of the world's information" is mostly dead.

With social media becoming a hellscape, people have mostly retreated to semi-private Discord servers; which severely damages the Internet's offer of "participate in a global commons".

There are a few bright spots like easy video sharing. However, I'm not sure I trust them not to get enshittified next.

I want to be clear, from an academic perspective these things are fascinating and very very cool! You can teach a computer to talk like a person might simply by having it read all the books! But there is not a business reason to have this. Not at the current costs. Maybe LLMs are a step we need to get actually useful AI tools, but as currently constituted its just not there.

The killer app of LLMs is how its gonna kill the industry when the investments fail to make the expected return. A lot of people are gonna lose their jobs when managers try to replace them with AI, and even more are gonna lose their jobs when that doesn't work and all those companies go under, and there's another tech bubble burst

I mean lets just say your premise is right, how much time is spent worldwide writing emails that could be automated? Just on a pure man hour basis it's surely worth billions if it did nothing else.

>But there is not a business reason to have this. Not at the current costs.

ChatGPT Pro tier is $200/mo, if you can't find ways to get that value I'm sorry but it's a skill issue and you're ngmi. The API tier is like $/million tokens. It's a joke to complain about the cost at this point...