Indeed. If the output produced by LLMs can be seen as extremely professional, that's because there's a whole cleaning/curating/editing chain working all the time behind the scenes. Of course that chain only works due to the intelligence, judgment, and critical thinking of human workers...

"There is a certain wildness in the tech industry these days that both mimics previous eras of large changes, like cloud computing (runaway costs in the early days), and is like nothing we’ve ever seen before (record revenues accompanied by mass layoffs).

One possible explanation: Tech executives, especially CEOs, are collectively suffering from delusions of AI grandeur. And at least one tech CEO has said as much out loud: Box founder Aaron Levie.

“CEOs are uniquely prone to AI psychosis because they’re sufficiently distant from the last mile of work that still has to happen to generate most value with AI,” Levie wrote on X.

CEOs “play with AI,” develop a prototype, or generate a contract, to use Levie’s examples, and then make the leap to believing agents can do the work.

But these top-level executives aren’t the people who have to review code, discover bugs, and identify calls to hallucinated libraries before software is deployed. They aren’t responsible for training AI models on a company’s idiosyncratic contract terms, nor do they have to spend days combing through contracts to find sneaky terms, as Levie indicates.

In other words, Levie’s theory posits, CEOs don’t really understand processes well enough to know what really can and can’t be automated. But that lack of knowledge doesn’t stop them from acting on their beliefs.

It’s important to note that Levie is not an AI hater. Quite the opposite. He mostly posts AI positivity on X to his 2.7 million followers, writing blogs titled “Headless software is the future” on how software built for AI agents is the way forward."

https://techcrunch.com/2026/05/27/tech-ceos-are-apparently-suffering-from-ai-psychosis/

#AI #AIHype #CEOs #AIPsychosis #Hallucinations #GenerativeAI #LLMs

Nice collection of charts about how AI has boosted the number of apps and websites (spoiler: it hasn't at all…)

https://mikelovesrobots.substack.com/p/wheres-the-shovelware-why-ai-coding

#AIHype #substack

His favorite part of comedy writing, he said, “is figuring out the puzzle pieces of a joke and getting the self-regard from having accomplished a difficult thing. Why would I want AI to take that away from me?”

https://www.harvardmagazine.com/commencement/class-day-ronny-chieng-harvard

#AI #AIHype #Creativity

(1/n)

"Organizations aren’t burning millions or hundreds of millions of dollars a year on AI because it’s good, they’re doing it because they are run by people who do not know what the fuck they’re doing.

Generative AI is catnip for hall monitors, snitches, toadies, and any other group that hates work and loves talking down to others. Put another way, it ingratiates losers who believe that learning to do or being good at something is a waste of time, because they deserve to just do what they want without any of that messy “effort.”

While I’m not saying every LLM user is an imbecile, they’re built to convince the mediocre and incurious that they’re remarkable, and it turns out that a great many of them run venture capital firms and Fortune 500 companies.

I also want to be clear that while there are sane and normal people who use these things, they’re mostly drowned out by a crowd of people that oscillate between bootlicking and regurgitating capitalist mythology in a way that makes it hard to trust anybody who spends significant amounts of time using an LLM.

One thing you’ll notice about the most moistened AI boosters is that they lack much degree of pride in their work. Everything they say must, at some point, compliment the mindless, unprofitable, unreliable tool underneath it — how “incredibly powerful” it is, how it’s “only getting better,” how it’s “only the beginning” of something that’s eaten over a trillion dollars and absorbed the majority of venture capital."

https://www.wheresyoured.at/the-revenge-of-the-business-idiot/

#AI #GenerativeAI #LLMs #AIBullshit #AIBubble #AIHype #Programming #SoftwareDevelopment

"Unfortunately, it’s difficult to make a crisp comparison, but the proxies that we have suggest that demand is growing much faster. For instance, both the quantity of tokens processed by Google in the last year, and by all providers according to Exponential View, have been growing by around 10×/year.

From another angle, we can look at token demand from today’s most intensive AI users: software engineers. Recent reports claim that some of Apple’s software engineers are permitted to use up to $300 in tokens per day, which works out to about 5 million output tokens per day with Claude Opus 4.7 API pricing, or 25 million output tokens per day with Kimi K2.6.16 Another point of comparison comes from Meta, whose 85,000 employees used 60 trillion tokens in one month across the organization. That figure included both input and output tokens; assuming a 25,000:1,000 input-to-output token ratio, that would be around 1 million output tokens per day and employee.

There were about 30 million software engineers worldwide as of 2025 (estimates range from 20 million to 50 million), and Stack Overflow’s 2025 survey on AI usage suggested that only around 47% of developers used AI on a daily basis, as of mid-2025. If all SWEs using AI daily were using it as intensely as Meta or Apple, they would demand somewhere between 10 and 350 trillion tokens per day in aggregate, i.e., between 200 million and 4 billion tokens per second. At the longest context sizes of 128,000:1,000, today’s Blackwell chips would struggle to serve all this potential demand for coding agents using models as large as Kimi K2.6. It also seems likely that both the number of developers using AI, and the intensity of their use will continue to grow rapidly."

https://epoch.ai/gradient-updates/is-a-compute-crunch-coming

#AI #GenerativeAI #AIBubble #Compute #AIHype #DataCenters #Inference