alt Hacker NewsI’ll note that it’s common and dangerous, in that there’s a generation of engineers who are at risk of leading each-other astray as to the economics and therefore probability distribution of outcomes for some firms that will massively impact their careers.
I think I understand the major reasons for this meme, but I find it really worrying; there were lots of incorrect ‘it’s a bubble’ conversations here in 2012-2015, but I don’t think they had the pervasive nature and “obvious” conclusion that a whole generation of engineering talent should just, you know, leave.
Meanwhile I am hearing rational economic modeling from the companies selling inference; Jensen, (a polished promoter, I grant you) says it really well — token value is increasing radically, in that new models -> better quality, and therefore revenues and utilization are increasing, and therefore contrary to the popular financial and techbro modeling of 2023, things like A100s still cost quite a lot whether hourly or to purchase. (!) Basically the economic value is so strong that it has actually radically extended the life of hardware.
I just hate to imagine like half of the world’s (or US’s) engineering talent quitting, spending ten years afraid, or wrongly convinced of some ‘inevitable’ market outcome. Feels like it will be bad for people’s personal lives, and bad for progress simultaneously.
People shouldn't be quitting the industry, agreed. There's plenty of work to do even with AI assistance.
But how is that a counterpoint to tokens being subsidized? They obviously are subsidized, this just isn't arguable at all. The claims in the linked post make perfect sense. If they weren't subsidized the investors in AI labs would all be minting money instead of burning it.
It doesn't matter if token value is increasing. What matters is how fast it increases relative to the price increases, the repayments on the debt loads and other things we can't really know here on this forum.
Every attempt I've seen to argue this fact away is merely playing with numbers e.g. excluding every cost except inf hardware+energy, even though labs are always training and have large costs outside of compute. This might or might not be a good way to predict the future of these orgs, but it doesn't help anyone argue inference is profitable today (because inference is literally the only thing OpenAI/Anthropic sell and they lose money).
The whole computing industry is in a super weird place right now that feels temporary, like Wile E. Coyote spinning his legs suspended in mid air. Until the economics of the AI industry stop being driven by FOMO and weird, hard to interpret quasi-religious or geopolitical motivations, it's impossible to make accurate predictions about what the impact on software jobs will be. Historically a tech like this would have started at super-high prices and the token cost would have gradually fallen over a period of decades, giving people plenty of time to adapt. Look at the cost of flying, desktop computers, mobile phones, etc. AI is attempting to short circuit that normal technological path and pack decades into years by convincing capital holders that they have no choice but to "invest" because it'll be a winner-takes-all repeat of web search and social media. Yet it's not shaping up that way.