Academia is currently 6-12mo behind the frontier of the industry due to secrecy and publication times, so any "long term" study, even for a year, would be out of date on arrival

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gipp 3 hours ago | parent | next [-]

When we're talking lab revenue, we're taking what companies are spending on AI.

The question is not whether companies are investing in AI, it's whether they're getting anything in return. Or, whether execs are just as anxious and confused about the story being sold as everyone else, taking the ludicrous amount of capital being put behind it as evidence that there's a "there" there, and hopping on the train out of pure FOMO and hedging, whether they're actually getting anything out of it at all.

	▲	vanuatu 2 hours ago \| parent [-]
		I think this is reasonable If we start to see spend go down because projects fail and companies run the ROI calculation and determine it's not worth it, then ill stand corrected and happily admit that

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tovej 3 hours ago | parent | prev [-]

Why don't you list these AI companies, then?

	▲	vanuatu 2 hours ago \| parent [-]
		can just ask chatgpt but off the top: code wrappers - cursor (special case), lovable, replit part model part applied - perplexity, 11labs, cartesia, suno applied branches of model labs - codex, claude code, deployment cos & fde teams ai roll ups - thrive, longlake, some stealth ones applied - cognition, sierra, fin, harvey, legora, glean part data part applied - scale Margins vary, but many of these companies' revenue are already a chunk higher than what was last publicly reported Wouldnt be surprising to see some of them 2-5x rev in the next few years

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jknoepfler 3 hours ago | parent | prev [-]

I'm working in a large enterprise that is leveraging AI aggressively.

Anecdotally, I'd wager that the modest/incremental but real gains from boring, daily application pale in comparison to the wasted cycles on terrible ideas, disrupted roadmaps due to poor business decision making, and the uncritical injection of insane, LLM generated bullshit into official business documents (fake KPIs for unmeasurable outcomes, references to nonsensical or non-existent process, data-driven decisions backed by hallucinated data. etc.).

I'm deeply skeptical that organizations will see real, lasting gains. I think they'll see some acceleration of copy/paste-adjacent workflows and gains in non-work like generating slide templates, but that's about the limit of it.

As prices rise to meet actual cost, I shudder to think about the idiotic, reactionary ripples it will send through corporate leadership, with everyone scrambling to evade responsibility at the same time and blaming their tech teams for failing to deliver on bullshit/impossible AI initiatives.

TL/DR yeah, I'd also like to see some real numbers.