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AI adoption and Solow's productivity paradox

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Re: AI adoption and Solow's productivity paradox

#301

My experience has been * If I don't know how to do something, llms can get me started really fast. Basically it distills the time taken to research something to a small amount. * if I know something well, I find myself trying to guide the llm to make the best decisions. I haven't reached the state of completely letting go and trusting the llm yet, because the llm doesn't make good long term decisions * when working a…

The future of work is fewer human team members and way more AI assistants. I think companies will need fewer engineers but there will be more companies. Now: 100 companies who employ 1,000 engineers each What we are transitioning to: 1000 companies who employ 10 engineers each What will happen in the future: 10,000 companies who employ 1 engineer each Same number of engineers. We are about to enter an era of explosiv…

This seems like a bot comment.

Re: AI adoption and Solow's productivity paradox

#302

Earlier quoted context omitted.

Does it matter if they can't ever stop training though? Like, this argument usually seems to imply that training is a one-off, not an ongoing process. I could save a lot of money if I stopped eating, but it'd be a short lived experiment. I'll be convinced they're actually making money when they stop asking for $30 billion funding rounds. None of that money is free! Whoever is giving them that money wants a return on…

There's an argument to be made that a "return on investment by way of eliminating all workers" is a reasonable result for the capitalists.

At least until they are running out of customers. And/or societies with mass-unemployment destabilize to a degree that is not conducive for capitalists' operations.

Re: AI adoption and Solow's productivity paradox

#303
post #9

My compsci brain suggests large orgs are a distributed system running on faulty hardware (humans) with high network latency (communication). The individual people (CPUs) are plenty fast, we just waste time in meetings, or waiting for approval, or a lot of tasks can't be parallelized, etc. Before upgrading, you need to know if you're I/O Bound vs CPU Bound.

None of this fits

Re: AI adoption and Solow's productivity paradox

#304
post #296

My experience has been that AI is much more useful on my own systems than on company systems. For AI to (currently) be useful, I need to choose my own tooling and LLM models to support AI centered workflow. At work, I have to use whatever (usually Microsoft) tools my company has chosen to purchase and approve for my corporate computer, and usually nothing works as well as on my own machine where I get to set it up as…

What you are describing is a failure to integrate AI into said company systems. I have seen quite a few companies now that buy MS AI products with great hopes only to be severely disappointed, because they may as well have just used vanilla ChatGPT (in fact then they would at least get newer models faster). But there are counter examples too. If you can pull all your company documentation into a vector db and build a RAG based assistant, you can potentially save countless hours across your workforce and possibly customers too. But this is not easy and also requires some level of UI interactivity that noone really offers right now. In fact they can't offer it, because you usually need to integrate ancient, arcane sources into your system. So you do have to write a lot of integration code yourself at every step. Not many companies are willing to spend that kind of money and effort, because managers just want to buy a MS product and be done with improving efficiency by next quarter.

Re: AI adoption and Solow's productivity paradox

#305
post #64

Earlier quoted context omitted.

What if LLMs are optimizing the average office worker's productivity but the work itself simply has no discernable economic value? This is argued at length in Grebber's Bullshit Jobs essay and book.

I find that highly unlikely, coding is the AIs best value use case by far. Right now office workers see marginal benefits but it's not like it's an order of magnitude difference. AI drafts an email, you have to check and edit it, then send it. In many cases it's a toss up if that actually saved time, and then if it did, it's not like the pace of work is break neck anyway, so the benefit is some office workers have a…

Code is much much harder to check for errors than an email.

Consider, for example, the following python code:

    x = (5)
vs

    x = (5,)
One is a literal 5, and the other is a single element tuple containing the number 5. But more importantly, both are valid code.

Now imagine trying to spot that one missing comma among the 20kloc of code one so proudly claims AI helped them "write", especially if it's in a cold path. You won't see it.

Re: AI adoption and Solow's productivity paradox

#306

Large firms are extremely bureaucratic organizations largely isolated from the market by their monopolistic positions. Internal pressures rule over external ones, and thus, inefficiency abounds. AI undeniably is a productive tool, but large companies aren't really primarily concerned with productivity.

Indeed. Most large companies don't need AI to increase productivity - they just need to stop wasting time on stupid bullshit. However, figuring out what is stupid bullshit and what is not seems to be an impossible task, and I don't think AI is going to help here at all.

Re: AI adoption and Solow's productivity paradox

#307
post #261
post #64

Earlier quoted context omitted.

What if LLMs are optimizing the average office worker's productivity but the work itself simply has no discernable economic value? This is argued at length in Grebber's Bullshit Jobs essay and book.

We made an under-the-radar optimization in a data flow in my company. A given task is now much more freshData-assisted that it used to. Was a LLM used during that optimization? Yes. Who will correlate the sudden productivity improvement with our optimization of the data flow with the availability of a LLM to do such optimizations fast enough that no project+consultants+management is needed ? No one. Just like no one…

Is there a productivity improvement resulting tangible economic results coming from that optimization?

It’s easy to convince yourself that it is, and anyone can massage some internal metric enough to prove their desired outcome.

Re: AI adoption and Solow's productivity paradox

#308

Earlier quoted context omitted.

Eh, try using Microsoft Copilot in Word or PowerPoint. It is worthless. If your experience with AI was a Microsoft product, you would think it was a scam too.

It’s comical that Microsoft inserted Copilot buttons throughout all of their productivity suite, and none of them are able to do the bare minimum that you would hope for. “Oh cool, copilot is in excel! I’m going to ask it a question about the data in the spreadsheet that it’s literally appearing beside natively in-app, or for help with a formula!” “Wait what, it’s saying it can’t see anything or read from the current…

Meta's AI can't search posts on Meta's properties (or at least couldn't a few months ago). I'm not really sure what it's point is unless it's meant as a kind of help desk for the site (which they already also have).

Re: AI adoption and Solow's productivity paradox

#309

Earlier quoted context omitted.

> I asked if anyone heard of twitter vaporware and only 3 people heard of it from influencers, none used it. Shocking results, I say!

No, these people ("managers, engineers" etc.) do just not work in tech & IT but in other fields and they do not read tech news in your country etc. Most people are just "not that deep in there" as most people on HN.

> “Tech news”

A guy attached Claude to his socials, groundbreaking tech.

Re: AI adoption and Solow's productivity paradox

#310
post #40
post #26

Earlier quoted context omitted.

Then where are all the amazing open source programs written by individuals by themselves? Where are all the small businesses supposedly assisted by AI?

Seemingly every day on Show HN? Also small businesses aren't going to publish blog posts saying "we saved $500 on graphic design this week!"

But they could have saved that $500 by paying... a human
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