Your late-cycle investment theory hinges on the point that "we've entered the maturity phase of the computing and networks revolution".
The obvious counter to that point is that we are in the very early days of the artificial intelligence revolution, which many believe will make computing and networks much more dominant in society, with substantial economic and social disruption. You engage with this at point 9, arguing that "AI represents efficiency, not disruption".
My view is that you are not correct that the limited impact of AI to date means that it will not be disruptive in the medium term. Other general purpose technologies (e.g. steam power, electricity, computers) took decades to have a major economic impact.
It is a bold choice to go against the current technological consensus, but it is also a risky wager to propound a new theory that ignores this consensus. (I first encountered your work when I received a copy of your very interesting book Hedge from Azeem Azhar -- I expect that Azeem would strongly question the choice not to bet on AI as a disruptor.)
On the other hand, if you are correct, it will be a very impressive contrarian call!
The nature of AI's recent public emergence is completely opposite of the typical innovation-lead revolutions though. Instead of the upstarts disrupting bottom-up and enabling new possibilities, we are in the thick of top-down incumbents throwing their weight around to deliver what's been primarily framed as efficiency/human replacement.
That doesn't suggest new growth opportunities as much as it suggests inter-corporate battles over optimizing costs to roughly maintain the status quo.
Perhaps a wave of nascent innovation is around the corner with the infrastructures in place. But for now, this Late-Cycle lens seems like a much better fit to what we are collectively experiencing right now.
Abundant AI requires abundant energy. We can talk about ASI all we want, but the ASI scenario requires 10x the amount of energy we currently produce to be used at scale - and nuclear reactors take 15 years to build in the West.
My hunch is that the AI wave will not be as strong as we think in the West mostly because of energy constraints.
I was not talking about ASI, which is a distraction. Existing AI methods can have huge impacts over the coming years, and these will continue to improve (and become much more power-efficient).
Abundant AI requires abundant energy. We can talk about ASI all we want, but the ASI scenario requires 10x the amount of energy we currently produce to be used at scale - and nuclear reactors take 15 years to build in the West.
My hunch is that the AI wave will not be as strong as we think in the West mostly because of energy constraints.
Check usd.ai
Nicolas,
Your late-cycle investment theory hinges on the point that "we've entered the maturity phase of the computing and networks revolution".
The obvious counter to that point is that we are in the very early days of the artificial intelligence revolution, which many believe will make computing and networks much more dominant in society, with substantial economic and social disruption. You engage with this at point 9, arguing that "AI represents efficiency, not disruption".
My view is that you are not correct that the limited impact of AI to date means that it will not be disruptive in the medium term. Other general purpose technologies (e.g. steam power, electricity, computers) took decades to have a major economic impact.
It is a bold choice to go against the current technological consensus, but it is also a risky wager to propound a new theory that ignores this consensus. (I first encountered your work when I received a copy of your very interesting book Hedge from Azeem Azhar -- I expect that Azeem would strongly question the choice not to bet on AI as a disruptor.)
On the other hand, if you are correct, it will be a very impressive contrarian call!
Maury
The nature of AI's recent public emergence is completely opposite of the typical innovation-lead revolutions though. Instead of the upstarts disrupting bottom-up and enabling new possibilities, we are in the thick of top-down incumbents throwing their weight around to deliver what's been primarily framed as efficiency/human replacement.
That doesn't suggest new growth opportunities as much as it suggests inter-corporate battles over optimizing costs to roughly maintain the status quo.
Perhaps a wave of nascent innovation is around the corner with the infrastructures in place. But for now, this Late-Cycle lens seems like a much better fit to what we are collectively experiencing right now.
Abundant AI requires abundant energy. We can talk about ASI all we want, but the ASI scenario requires 10x the amount of energy we currently produce to be used at scale - and nuclear reactors take 15 years to build in the West.
My hunch is that the AI wave will not be as strong as we think in the West mostly because of energy constraints.
I was not talking about ASI, which is a distraction. Existing AI methods can have huge impacts over the coming years, and these will continue to improve (and become much more power-efficient).
Abundant AI requires abundant energy. We can talk about ASI all we want, but the ASI scenario requires 10x the amount of energy we currently produce to be used at scale - and nuclear reactors take 15 years to build in the West.
My hunch is that the AI wave will not be as strong as we think in the West mostly because of energy constraints.