jay trotta
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An interesting snippet;
“That ‘tokens got burned for millions of dollars without any real significant return on investment to show for it’ might well turn out to be the epitaph for an era,” says Professor Gary Marcus.
Admittedly, Rachel Reeves has made hiring humans much more expensive. But perhaps still not expensive enough to make a fundamentally unreliable and increasingly expensive automation tool seem attractive.
Secondly, if business isn’t seeing value, then the case for all that expensive AI infrastructure also collapses with it. Especially as those investments depreciate so rapidly.
Let’s do the math. Will Sommer, an economist forecaster, explains that when capital looks at an Amazon, a Microsoft or a Google, it sees a 25pc return on capital invested (ROIC).
Below 12pc ROIC, capital drifts off elsewhere. Below 7pc, it’s “an unmitigated disaster for all of the investors in this technology”, Sommer told The Verge.
To hit even that 7pc return, Sommer estimates that at current token costs, the big AI hyperscalers need to bank $7tn in revenue over the next three years to meet their spending commitments. And token consumption would need to increase by 50,000 to 100,000 times over what it is today.
Out-of-control employees are blowing AI budgets alarmingly fast
So out of the great cloud of AI hype, the outline of the crash can now be clearly discerned. Humans are turning out to be quite useful after all.
Stoller raises something else disquieting. It shouldn’t be a shock, he says, because much of this was quite predictable 18 months ago, when we could see what China was doing.
PS: if you haven't peeked at your States "Data Center" impact/building, take a peek and see if your OK wit that
“That ‘tokens got burned for millions of dollars without any real significant return on investment to show for it’ might well turn out to be the epitaph for an era,” says Professor Gary Marcus.
Admittedly, Rachel Reeves has made hiring humans much more expensive. But perhaps still not expensive enough to make a fundamentally unreliable and increasingly expensive automation tool seem attractive.
Secondly, if business isn’t seeing value, then the case for all that expensive AI infrastructure also collapses with it. Especially as those investments depreciate so rapidly.
Let’s do the math. Will Sommer, an economist forecaster, explains that when capital looks at an Amazon, a Microsoft or a Google, it sees a 25pc return on capital invested (ROIC).
Below 12pc ROIC, capital drifts off elsewhere. Below 7pc, it’s “an unmitigated disaster for all of the investors in this technology”, Sommer told The Verge.
To hit even that 7pc return, Sommer estimates that at current token costs, the big AI hyperscalers need to bank $7tn in revenue over the next three years to meet their spending commitments. And token consumption would need to increase by 50,000 to 100,000 times over what it is today.
Out-of-control employees are blowing AI budgets alarmingly fast
So out of the great cloud of AI hype, the outline of the crash can now be clearly discerned. Humans are turning out to be quite useful after all.
Stoller raises something else disquieting. It shouldn’t be a shock, he says, because much of this was quite predictable 18 months ago, when we could see what China was doing.
PS: if you haven't peeked at your States "Data Center" impact/building, take a peek and see if your OK wit that
