But it isn’t joining the workforce. Your perspective is that it could, but the point that it hasn’t is the one that’s salient. Codex might be able to do a substantial portion of what a freelancer can do, but even you fell short of saying it can replace the freelancer. As long as every ai agent needs its hand held the effect on the labor force is an increase in costs and an increase in outputs where quality doesn’t matter. It’s not a reduction of labor forces
OK, let me fall less short. It has replaced the freelancer for me. I communicate product requirements. It builds the product immediately at trivial cost. It’s better than a human. There are jobs I would have considered hiring out that I don’t because the machine is better. Nothing you said about labor effects in the large even logically follow. Have you even used one of these systems?
I find that when decisions are very minor, people love to have tons of options to select from. When decisions are much more impactful and high stakes, people seem to love finding ways to convince themselves there are no options and that they must proceed down a single path out of necessity for how the world is.
There’s rarely (maybe never) an objective and comprehensive measure of quality. Your concept of what merits matter is someone else’s advertising. No one is operating non-meritocratically, they just value different qualities from you.
I think your definition of popular is holding you back. If popular just means other people like you, you’re obviously wrong- plenty of people are very successful even though they are disliked. Often this will happen multiple times on a single team at a company.
If popular means you’re perceived as valuable, you’re obviously right. All institutions are social institutions and operate on social understandings of value. So to be successful you have to be perceived as valuable by these social structures.
I think calling this a scam misunderstands the non-quantitative metrics of worth. There isn’t actually a Best Academic, a Best Engineer, or a Best Coworker in some measurable objective sense. Those are all social evaluations and they’re valuable because of that, not despite it
What investors were intentionally deceived and what were the lies specifically? I saw something about a Kickstarter, but it's trickier as there is no promise of delivered products, it ends up being an donation basically, although Kickstarter try to make that intentionally vague.
There absolutely is a promise. Even if you manage to legally find a way to not get sued, taking advantage of the fact that everyone who gave you money believed it was a promise is still scamming them.
Isn't the whole thing (or two) with Kickstarter is that if it's not funded, everyone gets their money back and if it's funded, the creator tries to deliver the goals according to the timeline but if they don't, they're not held liable for that? So if for some reason the creator run out of money before they could send actual products, you as a donator don't have the right to get your money back? Maybe I misunderstood the whole concept of Kickstarter.
It's what takes time though. When you need to make a wrapper for some API for example LLMs are incredible. You give it a template, the payload format and the possible methods and it just spits out a 500-1000 line class in 15 seconds. Do it for 20 classes, that's work for a week 'done' in 30 mins. Realistically 2 days since you still have to fix and test a lot but still..
If you can get the specific documentation for it. Sadly many companies don't want you using the API so they just give you a generic payload and the methods and leave you to it. LLMs are good in the sense that they can tell what type StartDate, EndDate is (str MSDate), maybe it also somehow catches on that ActualDuration is an int.. It also manages to guess correctly a lot of the fields in that payload that are not necessary for the particular call/get overridden anyway.
The cloud being moving away from the "you must work to eat" economy and into the "you can work if you want nice stuff" economy. Getting there won't be fun but a lot of us would like that for our grandchildren.
That's because it's software / an application. I don't blame my editor for broken code either. You can't put blame on software itself, it just does what it's programmed to do.
But also, blameless culture is IMO important in software development. If a bug ends up in production, whose fault is it? The developer that wrote the code? The LLM that generated it? The reviewer that approved it? The product owner that decided a feature should be built? The tester that missed the bug? The engineering organization that has a gap in their CI?
Blameless culture is important for a lot of reasons, but many of them are human. LLMs are just tools. If one of the issues identified in a post-mortem is "using this particular tool is causing us problems", there's not a blameless culture out there that would say "We can't blame the tool..."; the action item is "Figure out how to improve/replace/remove the tool so it no longer contributes to problems."
> You can't put blame on software itself, it just does what it's programmed to do.
This isn't what AI enthusiasts say about AI though, they only bring that up when they get defensive but then go around and say it will totally replace software engineers and is not just a tool.
Blame is purely social and purely human. “Blaming” a tool or process and root causing are functionally identical. Misattributing an outage to a single failure is certainly one way to fail to fix a process. Failing to identify faulty tools/ faulty applications is another way.
I was being flippant to say it’s never AI’s fault, but due to board/C-Suite pressure it’s harder than ever to point out the ways that AI makes processes more complex, harder to reason about, stochastic, and expensive. So we end up with problems that have to be attributed to something not AI.
"I got rid of that machine saw. Every so often it made a cut that was slightly off line but it was hard to see. I might not find out until much later and then have to redo everything."
Designers, engineers, and/or pilots aren't tools, so that's a strange rhetorical question.
At any rate, it depends on the crash. The NTSB will investigate and release findings that very well may assign fault to the design of the plane and/or pilot or even tools the pilot was using, and will make recommendations about how to avoid a similar crash in the future, which could include discontinuing the use of certain tools.
If I bought an AI powered toaster that allows me to select a desired shade of toast, I select light golden brown, and it burns my toast, I certainly do blame “it”.
I wouldn’t throw it against a wall because I’m not a psychopath, but I would demand my money back.
I presume your definition of use case is something that doesn't include what people normally use it for. And I presume me using it for coding every day is disqualified as well.
I didn't mean to suggest it has no utility at all. That's obviously wrong (same for crypto). I meant a use case in line with the projections the companies have claimed (multiple trillions). Help with basic coding (of which efficiency gains are still speculative) is not a multi-trillion dollar business.
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