Everyone should read his argument carefully. Ponder them in silence and accept or reject them in based on the strength of the arguments.

Sorry that happened to you, I have been there too,

When a company is hiring and laying off like that it’s a serious red flag, the one that did that to me is dead now

Is his math wrong?

IBM CEO has sour grapes.

IBM's HPC products were enterprise oriented slop products banked on their reputation, and the ROI torched their credibility when compute costs started getting taken seriously. Watson and other products got smeared into kafkaesque arbitrary branding for other product suites, and they were nearly all painful garbage - mobile device management standing out as a particularly grotesque system to use. Now, IBM lacks any legitimate competitive edge in any of the bajillion markets they tried to target, no credibility in any of their former flagship domains, and nearly every one of their products is hot garbage that costs too much, often by orders of magnitude, compared to similar functionality you can get from things like open source or even free software offered and serviced by other companies. They blew a ton of money on HPC before there was any legitimate reason to do so. Watson on Jeopardy was probably the last legitimately impressive thing they did, and all of their tech and expertise has been outclassed since.

First, I think it's $80b per 100 GW datacenter. The way you figure that out is a GPU costs $x and consumes y power. The $x is pretty well known, for example an H100 costs $25-30k and uses 350-700 watts (that's from Gemini and I didn't check my work). You add an infrastructure (i) cost to the GPU cost, but that should be pretty small, like 10% or less.

So a 1 gigawatt data center uses n chips, where yn = 1 GW. It costs = xi*n.

I am not an expert so correct me please!

> those gpu's will be obsolete in 5 years, but will the newer be enough better as to be worth replacing them is an open question

Doesn't one follow from the other? If newer GPUs aren't worth an upgrade, then surely the old ones aren't obsolete by definition.

> those gpu's will be obsolete in 5 years, but will the newer be enough better as to be worth replacing them

Then they won't be obsolete.

I recently compared performance per dollar for CPUs and GPUs on benchmarks for GPUs today vs 10 years ago, and suprisingly, CPUs had much bigger gains. Until I saw that for myself, I thought exactly the same thing as you.

It seems shocking given that all the hype is around GPUs.

This probably wouldn't be true for AI specific workloads because one of the other things that happened there in the last 10 years was optimising specifically for math with lower size floats.

I think real issue is current costs / demand = Nvidia gouging GPU price that costs for hardware:power consumption is 70:20 instead of 50:40 (10 for rest of datacenter). Reality is gpus are serendipidous path dependent locked from gaming -> mining. TPUs are more power efficient, if bubble pops and demand for compute goes down, Nvidia + TMSC will still be around, but nexgen AI first bespoke hardware premium will revert towards mean and we're looking at 50% less expensive hardware (no AI race scarcity tax, i.e. 75% Nvidia margins) that use 20% less power / opex. All of a sudden existing data centers becomes not profitable stranded assets even if they can be stretched past 5 years.

But if your competitor is running newer chips that consume less power per operation, aren't you forced to upgrade as well and dispose of the old hardware?

It's just the same dynamic as old servers. They still work fine but power costs make them uneconomical compared to latest tech.

5 years is maybe referring to the accounting schedule for depreciation on computer hardware, not the actual useful lifetime of the hardware.

It's a little weird to phrase it like that though because you're right it doesn't mean you have to throw it out. Idk if this is some reflection of how IBM handles finance stuff or what. Certainly not all companies throw out hardware the minute they can't claim depreciation on it. But I don't know the numbers.

Anyways, 5 years is an infection point on numbers. Before 5 years you get depreciation to offset some cost of running. After 5 years, you do not, so the math does change.

It’s not about assumptions on the hardware. It’s about the current demands for computation and expected growth of business needs. Since we have a couple years to measure against it should be extremely straightforward to predict. As such I have no reason to doubt the stated projections.

AGI has value in automation and optimisation which increase profit margins.When AGI is everywhere, then the game is who has the smartest agi, who can offer it cheapest, who can specialise it for my niche etc. Also in this context agi need to run somewhere and IBM stands to benefit from running other peoples models.

agree the capital could be put to better use, however I believe the alternative is this capital wouldn't have otherwise been put to work in ways that allow it to leak to the populace at large. for some of the big investors in AI infrastructure, this is cash that was previously and likely would have otherwise been put toward stock buybacks. for many of the big investors pumping cash in, these are funds deploying the wealth of the mega rich, that again, otherwise would have been deployed in other ways that wouldn't leach down to the many that are yielding it via this AI infrastructure boom (datacenter materials, land acquisition, energy infrastructure, building trades, etc, etc)

I'm a younger millennial. I'm always seeing homeless people in my city and it's an issue that I think about on a daily basis. Couldn't we have spent the money on homeless shelters and food and other things? So many people are in poverty, they can't afford basic necessities. The world is shitty.

Yes, I know it's all capital from VC firms and investment firms and other private sources, but it's still capital. It should be spent on meeting people's basic human needs, not GPU power.

Yeah, the world is shitty, and resources aren't allocated ideally. Must it be so?

> ~10^14 tokens on the internet

Does that include image tokens? My bet is with image tokens you are off by at least 5 orders of magnitude for both.

I must be dense, why does this imply AI can't be profitable?