Economics of AI: Competitive Lab Strategies, Market Forces, Effect on Jobs (Part 2 of 2)
Every week, the headlines can’t make up their mind: AI is either the biggest opportunity of our lifetime or the biggest bubble since 2000. Sometimes both, in the same newspaper.
The numbers don’t help either. A company valued at $1.5 trillion is preparing to go public, yet only about $90 billion will actually change hands. The same company lost $104 billion on paper in nine months, while making $6.6 billion in cash. The world’s most valuable chipmaker is standing behind its own customers’ debts. And somewhere in that chain, quite possibly, sits your pension fund.
If that sounds confusing, it’s because it is (and not because you’re missing something).
I was very curious about these numbers & how these things may or may not hold up. On Wednesday, I’ll untangle it in plain language, no finance degree required. We’ll follow the money step by step:
why Big Tech now spends almost everything it earns on chips & data centres
how the AI labs make (and spend) their money
who is lending them all this cash
what has to be true for the whole thing to hold up
We’ll check it against history (yes, the dot-com bubble), look at a live bond market together & discuss on where this might be heading.
And because most of us aren’t running a trillion-dollar company (yet! ;-)), we’ll finish with the question that matters for the rest of us: when almost anything digital can be copied, what keeps you competitive?
Hosted by & in the location of Ship26 - the co-building space in zurich for Founders and Independents.
More info about Ship26: https://www.ship26.com/?utm_source=luma