The force-feeding of AI features on an unwilling public

Post by meheleventyone » Sun, Jul 06, 2025, 9:09 AM UTC

squidbeak wrote: post #33

meheleventyone wrote: post #28

Earlier quoted context omitted.

Given everyone and their mother is putting AI in to their products it makes me wonder how that revenue breaks down between people incidentally paying for it versus deliberately paying for it versus being subsidized by VC. Obviously ultimately all this revenue is being collected at a massive loss but I wonder if that carries on down the value chain.

Amusing the way the argument shifts every time. This one's new though. "If it was any good, people would pay for it." "The data shows people are paying for it." "Aah but they don't know they're paying for it."

Post by amadeuspagel » Sun, Jul 06, 2025, 9:30 AM UTC

Post by jasonsb » Sun, Jul 06, 2025, 9:49 AM UTC

sasaf5 wrote: post #42

jasonsb wrote: post #32

I’ve observed the opposite—not enough people are leveraging AI, especially in government institutions. Critical time and taxpayer money are wasted on tasks that could be automated with state-of-the-art models. Instead of embracing efficiency, these organizations perpetuate inefficiency at public expense. The same issue plagues many private companies. I’ve seen employees spend days drafting documents that a free tool…

> I’ve seen employees spend days drafting documents that a free tool like Mistral could generate in seconds, leaving them 30-60 minutes to review and refine. What I have seen is employees spending days asking the model again and again to actually generate the document they need, and then submit it without reviewing it, only for a problem to explode a month later because no one noticed a glaring absurdity in the middl…

Post by tankenmate » Sun, Jul 06, 2025, 9:51 AM UTC

einrealist wrote: post #44

kgeist wrote: post #36

Earlier quoted context omitted.

We run our own LLM server at the office for a month now, as an experiment (for privacy/infosec reasons), and a single RTX 5090 is enough to serve 50 people for occasional use. We run Qwen3 32b which in some benchmarks is equivalent to GPT 4.1-mini or Gemini 2.5 Flash. The GPU allows 2 concurrent requests at the same time with 32k context each and 60 tok/s. At first I was skeptical a single GPU would be enough, but it…

If those smaller models are sufficient for your use cases, go for it. But for how much longer will companies release smaller models for free? They invested so much. They have to recoup that money. Much will depend on investor pressure and the financial environment (tax deductions etc). Open Source endeavors will have a hard time to bear the resources to train models that are competitive. Maybe we will see larger coop…

Post by watwut » Sun, Jul 06, 2025, 9:57 AM UTC

jasonsb wrote: post #32

I’ve observed the opposite—not enough people are leveraging AI, especially in government institutions. Critical time and taxpayer money are wasted on tasks that could be automated with state-of-the-art models. Instead of embracing efficiency, these organizations perpetuate inefficiency at public expense. The same issue plagues many private companies. I’ve seen employees spend days drafting documents that a free tool…