They’re different, and I think this one has the capability of being more devastating.
The dot-com bubble was really broad. Hundreds or thousands of companies, all without vowels in their names trying to break new ground. A wild west style gold rush. When it popped a lot of small companies went bankrupt.
This is a handful of companies with billions of capital buying GPUs from NVidia to be make the largest hungriest machine they can. All in the pursuit of being first to create “AGI”. If one of them succeeds, the others are toast and multiple 500+B dollar companies will collapse in on themselves. If none of it works, the same thing happens and it takes a large chunk out of $4T Nvidia too.
I’m sure that silicon valley executives visualise a future where they own the machines that produce all intellectual property and do most jobs. They see a return to feudalism where they are the lords.
I think this greater vision is about as likely to be realised as it is that Elon Musk will invent full self driving, or robots that aren’t obviously remotely operated, or a tesla roadster, or a battery powered articulated lorry with thermo nuclear explosion proof glass, or building a rocket to get the US back to the moon before the Chinese in what is clearly a new space race/pissing match. Or a hyperloop, or ever getting anywhere near to building a colony on Mars, or, or, or.
But I don’t think it is just a case of AGI or bust. LLM’s augmented with ai agents have a very real potential to replace a capitalism-destabilising percentage of white collar jobs without AGI.
Just like the dot com bubble popping didn’t kill the web, I do think it is unlikely that any possible current AI bubble popping will kill capital’s push to automate jobs away.
(And as far as I can see the AI bubble is the result of massive capital expenditure rather than rampant speculation, so because I am pretty confident in the ‘value’ to capital of LLM’s + AI Agent’s, I don’t really see it as the same kind of a bubble as the dotcom bubble.)
I’m honestly hoping for a repeat. Hopefully Microsoft goes down this time too, since they’re heavily into AI. Twitter, Meta, Google and Amazon too. It’s really just the worst of the worst.
They remember it too. It’s why they try to keep the bubble going by jumping to the next shiny investor lure. Just a few years it was all deep learning, blockchain and NFT. One guess is that they’ll go for humanoid robots next.
This is no revelation. THEY KNOW. The play is obvious.
Not one these investors wants to risk missing out on being the next Google or FaceBook or Twitter or Amazon. They know damned well the vast majority will fail. They’re gambling on not being the one left holding the bag.
AI is here to stay, will continue to improve, and there will be a killer app, probably a dozen. My money is on life sciences, particularly medicine.
At least they‘ve wasted their money for research of what doesn‘t work instead of just building silly products as for the .com bubble.
Humanity will gain insights to the kind of AI approaches that won‘t work much faster than without all the money. It‘s just an allocation of human efforts
Not really. None of what has been going on with transformer models has been anything but hyper scaling. It’s not really making fundamental advances in technology it’s that they decided what they had at the scale they had makes convincing enough demos that the scam could start.
It has been more than just hyperscaling. First of all, the invention of transformers would likely be significantly delayed without the hype around CNNs in the first AI wave in 2014. OpenAI wouldn‘t have been founded and their early contributions (like Soft Actor-Critic RL) could have taken longer to be explored.
While I agree that the transformer architecture itself hasn‘t advanced far since 2018 apart from scaling, its success has significantly contributed to self-learning policies.
RLHF, Direct Policy Optimization, and in particular DeepSeek‘s GRPO are huge milestones for Reinforcement Learning which arguably is the most promising trajectory for actual intelligence. Those are a direct consequence of the money pumped into AI and the appeal it has to many smart and talented people around the world
Anyone remember the dot-com bubble?
They’re different, and I think this one has the capability of being more devastating.
The dot-com bubble was really broad. Hundreds or thousands of companies, all without vowels in their names trying to break new ground. A wild west style gold rush. When it popped a lot of small companies went bankrupt.
This is a handful of companies with billions of capital buying GPUs from NVidia to be make the largest hungriest machine they can. All in the pursuit of being first to create “AGI”. If one of them succeeds, the others are toast and multiple 500+B dollar companies will collapse in on themselves. If none of it works, the same thing happens and it takes a large chunk out of $4T Nvidia too.
I’m sure that silicon valley executives visualise a future where they own the machines that produce all intellectual property and do most jobs. They see a return to feudalism where they are the lords.
I think this greater vision is about as likely to be realised as it is that Elon Musk will invent full self driving, or robots that aren’t obviously remotely operated, or a tesla roadster, or a battery powered articulated lorry with thermo nuclear explosion proof glass, or building a rocket to get the US back to the moon before the Chinese in what is clearly a new space race/pissing match. Or a hyperloop, or ever getting anywhere near to building a colony on Mars, or, or, or.
But I don’t think it is just a case of AGI or bust. LLM’s augmented with ai agents have a very real potential to replace a capitalism-destabilising percentage of white collar jobs without AGI.
Just like the dot com bubble popping didn’t kill the web, I do think it is unlikely that any possible current AI bubble popping will kill capital’s push to automate jobs away.
(And as far as I can see the AI bubble is the result of massive capital expenditure rather than rampant speculation, so because I am pretty confident in the ‘value’ to capital of LLM’s + AI Agent’s, I don’t really see it as the same kind of a bubble as the dotcom bubble.)
I’m honestly hoping for a repeat. Hopefully Microsoft goes down this time too, since they’re heavily into AI. Twitter, Meta, Google and Amazon too. It’s really just the worst of the worst.
They remember it too. It’s why they try to keep the bubble going by jumping to the next shiny investor lure. Just a few years it was all deep learning, blockchain and NFT. One guess is that they’ll go for humanoid robots next.
This is no revelation. THEY KNOW. The play is obvious.
Not one these investors wants to risk missing out on being the next Google or FaceBook or Twitter or Amazon. They know damned well the vast majority will fail. They’re gambling on not being the one left holding the bag.
AI is here to stay, will continue to improve, and there will be a killer app, probably a dozen. My money is on life sciences, particularly medicine.
At least they‘ve wasted their money for research of what doesn‘t work instead of just building silly products as for the .com bubble.
Humanity will gain insights to the kind of AI approaches that won‘t work much faster than without all the money. It‘s just an allocation of human efforts
Not really. None of what has been going on with transformer models has been anything but hyper scaling. It’s not really making fundamental advances in technology it’s that they decided what they had at the scale they had makes convincing enough demos that the scam could start.
It has been more than just hyperscaling. First of all, the invention of transformers would likely be significantly delayed without the hype around CNNs in the first AI wave in 2014. OpenAI wouldn‘t have been founded and their early contributions (like Soft Actor-Critic RL) could have taken longer to be explored.
While I agree that the transformer architecture itself hasn‘t advanced far since 2018 apart from scaling, its success has significantly contributed to self-learning policies.
RLHF, Direct Policy Optimization, and in particular DeepSeek‘s GRPO are huge milestones for Reinforcement Learning which arguably is the most promising trajectory for actual intelligence. Those are a direct consequence of the money pumped into AI and the appeal it has to many smart and talented people around the world