You do realize "subsidizing" means charging less for something than it costs to provide, right? So they'll lose a dollar on every sale, but they'll make up for it in volume? E2E is usually where the profit comes from. If they're subsidizing getting regular users on board (pro/plus/max), and they're subsidizing to get businesses on board (massive deploys), where can the profit possibly come from without a pricing rug pull?
I do, my point was answering to the "if it comes so cheap that" they would stop losing money of that, they would still need to subsidize for acquisition or some big clients or for rush times. It's the all-you-can-eat-buffet strategy.
I'm not saying I see them going that way or that I would, but at least THAT would possibly work.
Thank you for the clarification. I figured I was missing something in your meaning. Although "if it comes so cheap that..." means it will probably come cheap for other providers, and the margins wouldn't be there in the end because a price increase to take advantage of those big clients / rush times might lose the clients. I think we agree that their chances of becoming profitable don't look great.
But immitating others is about the only thing genAI does. Sometimes "others" is a 'programmer', sometimes "others" is an 'artist', but regardless, it still does it poorly.
Not OP, but I'd settle for something that actually learns, instead of being a static pile of linear algebra. Pretending it learns because you change the input (context) doesn't count.
> That Ford story was really misleading. It wasn't about modern LLMs, and the way it was reported implied that Ford had fired and then hired people but if you read closer that wasn't necessarily the case at all - it sounded more like they were re-hiring people who had retired because they needed expertise that had left the company.
Oh come on, Simon. Are your glasses so rose coloured they are opaque? They fired, and then re-hired because the AI couldn't do the job. They had to re-hire the quality folks. So, no, it wasn't LLMs, it was quality control -- which is a much more well established domain for automated systems. LLMs are a complete shitshow compared to industrial process automation.
Side question -- do you worry about being so pro-LLM when the promises of LLMs are so clearly falling short?
Show me evidence that they had previously fired any of the people who were hired.
Your comment is exactly the misinterpretation I'm pushing back against here.
The time period covered by this story starts three years ago! What kind of LLMs do you think they were using back then?
> Side question -- do you worry about being so pro-LLM when the promises of LLMs are so clearly falling short
I think my record is looking pretty good here. I was early to the "LLMs are useful for writing code" thing, especially with the code interpreter pattern (both write and then execute code in a loop) which I now realize was our first hint at coding agents.
3 years ago is about when the BS "AI can do anything!" hype started. So, it is not a misinterpretation, but an accurate assessment of the hype cycle. Exactly the kind of things managers are bumbling into because "AGI any day now!" for the last 3-4 years. GPT 3.5 was released May 2022. I'm curious how many AI project in industry have crashed and burned during this hype-Summer before the Winter. Speaking of which, whatever happened to that "software dark factory" you were gushing over a while back?
When I said "misinterpretation" here I was talking about people assuming that the Ford story was a simple case of "Ford fired their employees because they thought AI could replace them, then had to hire them all back again". That's not what happened.
A TON of AI projects have crashed and burned in the past few years. This stuff is really hard to adopt at an organizational level, much more so than for individuals.
I've been pretty consistent in saying that I think the dark factory stuff is interesting more as an exploration of the edges of what this stuff can do. It's a great way to highlight the question of how we can get agents to demonstrate their work without reviewing every line of their code.
Be sure to short the shit out of that company after you leave, assuming something in your employment contract doesn't prevent it (doubtful). Especially if they are software development focused.
Well, it didn't take long for this post to be disappeared from the front page.
Edit: ahhh, I see why. In the list of ways to keep your sanity through the AI mania -- "I no longer visit Hackernews, Reddit, or really anywhere where I am going to be drip-fed nonsense."
I think just the possibility of consequences that they can give a damn about. An LLM doesn't have feelings no matter how much human-like text it can simulate. There is literally nothing going on between prompts for any given model. They are incapable of worry or any other emotion. Wipe the context clean and the LLM is completely unaware there was ever a problem.
