Over the past few weeks, several US banks have pulled off from lending to Oracle for expanding its AI data centres, as per a report.
Over the past few weeks, several US banks have pulled off from lending to Oracle for expanding its AI data centres, as per a report.
A lot of fields don’t require doctorate levels of expertise to render effective business services. I’ve seen first hand companies replace thousands of employees and shutter divisions because their AI counterpart has been doing the job quantitatively equally, and faster. Perfect is the enemy of good enough, in most cases, as they say.
Lemmy is filled to the brim with llm haters but you’re not only a minority, you’re probably also closing doors on the future trajectory of tech in business.
perhaps but one example, Commonwealth Bank (largest Australian Bank and in the top 10 worldwide AFAIK) in Australia said they were dismissing 1000’s of staff because of AI, turned out they were just offshoring. The latter is seen positively apparently, the former not so much.
“Think of the shareholder value of firing all these people!”
Also, I call bullshit. I’ve seen many cases of companies replacing their staff with AI, then a month later desperately trying to hire staff again because the AI is good at "looking like* it can do the job but once in use turns out it’s complete shit.
This is of course problematic, but not directly the fault of the technology itself. The entire system is problematic, but that’s a digression from the effectiveness of the tech doing the job.
And the instances I’m talking about were running the ai stack and employee teams in parallel for nearly a year. The replacement wasn’t a “yeah let’s try this… whoops that didn’t work”. It was a tried and tested approach, and the employees made redundant (in the capability sense, not the firing sense, which followed afterwards).
And I give it less then a year before the “oh shit, we really should have human’s overseeing this” hits