Honestly, it's just shouting into an echo chamber. They call it organizational failure, but it's really just 'come on, my side.' A consultant who does that is untrustworthy. It means they have no metrics.
Same goes for their 0% claim. It's overgeneralization, isn't it?
So why did they fail, what went wrong, and how should these AI projects be analyzed—and by what metrics? They skip all that and just throw out a single KPI. What insight does that offer?
Honestly, there are a lot of people on HN who just shout that AI is useless because their own jobs are at risk. That's an undeniable fact. In my country, Korea, we say 'like a pheasant hiding its head in the ground.' It means denying reality and lacking self-awareness.
I've also seen many failed AI projects due to a lack of proper evaluation of AI capabilities. I don't want to deny that premise.
But if you're going to make that argument, you need to describe why they failed. There's none of that here, just this:
'We're going to opt out because it looks like AI projects will fail.'
They package it as being cautious, but when you peel back the wrapper, it really means:
'We can't keep up with the AI trend. And we can't tell what works and what doesn't.'
Sure, AI has a bubble. No one can deny that. But separate from that, it is useful. Do you really think millions of consumers would stick around for something useless?
Social problems are arising, and people are losing jobs because of it. Let's think the other way around. It doesn't make sense for people to lose jobs over something that's truly useless and wrong.
People are losing jobs because it's useful and valuable. So wouldn't it be more accurate to say that the problem is 'over-application' rather than the thing itself being bad? In other words, we could say that it's being valued more than it's worth. But this argument just says it's bad, period, with no nuance. I can't trust someone who talks like that.
AI writing, if you give it a red-team prompt, can at least refine the surface of counterarguments to your claim. But this—from overgeneralization to extremes—is a textbook example of bad human writing
(i'm more chatty because it's my "down-day". Hope you don't mind)
I don't think you're upset because AI is useful and valuable. Are you upset because you can't describe how the bubble will burst?
Some (more) quantitative types saying that the economics are deflationary. So NVIDIA have already won.
But there are some that claim that the bubble has nothing to do with NVIDIA's monopoly on compute (21.C steam engine/steel). That the bubble is in the OX layer. (You?). If Anthropic (or Palantir replacement) fail to do what? Then the bubble will burst.
This is the more interesting but I will have to sleep on it.
I think AI is useful and has value, but what I find problematic is the illogical behavior that people display while claiming to be engaging in thoughtful writing.
Rather than saying NVIDIA will be the ultimate winner, I think Apple could be the final winner as a hedge against semiconductor stocks, at least for now.
In that sense, I'm not sure. You can't time a bubble, so it's just a bubble.
But I do think NVIDIA will remain powerful because of its CUDA ecosystem—though the future is uncertain.
[Bro I was hoping you'd rip into your own OX idea here.. then we could have a convo here or offline.
I wouldn't say I get frustrated by illogical writing--esoecially ones that only _seem_ illogical---, but more that people like us who might know better don't point out precisely where that illogic is after thinking carefully about it.
]
It's possible to time a burst _if_ you see the pin, but anything you do _when_ you see it is technical illegal?
So your OX idea feels like just the sort of thing that could open our eyes new kinds of pins.
Further, I'm not totally closed to the idea that actively trying to pop the Anthropic bubble is moral, indie of how quixotic that sounds. Even if it might be a good case study for deinstitionalizing research math.. even if that Napoleon quote that's trending..
I would also never bet against Jensen taking some ideas from "the Apple playbook". Especially when multiple people have already pointed it out. Though this is tangential. Less tangential---
Refinement of OX framework would help us think about how NVIDIA can or cannot play the Apple game. Certainly, if given calibrated riskiness and timing, Apple would move against Anthropic. You know what I mean?
Same goes for their 0% claim. It's overgeneralization, isn't it?
So why did they fail, what went wrong, and how should these AI projects be analyzed—and by what metrics? They skip all that and just throw out a single KPI. What insight does that offer?
Honestly, there are a lot of people on HN who just shout that AI is useless because their own jobs are at risk. That's an undeniable fact. In my country, Korea, we say 'like a pheasant hiding its head in the ground.' It means denying reality and lacking self-awareness.
I've also seen many failed AI projects due to a lack of proper evaluation of AI capabilities. I don't want to deny that premise.
But if you're going to make that argument, you need to describe why they failed. There's none of that here, just this:
'We're going to opt out because it looks like AI projects will fail.'
They package it as being cautious, but when you peel back the wrapper, it really means:
'We can't keep up with the AI trend. And we can't tell what works and what doesn't.'
Sure, AI has a bubble. No one can deny that. But separate from that, it is useful. Do you really think millions of consumers would stick around for something useless?
Social problems are arising, and people are losing jobs because of it. Let's think the other way around. It doesn't make sense for people to lose jobs over something that's truly useless and wrong.
People are losing jobs because it's useful and valuable. So wouldn't it be more accurate to say that the problem is 'over-application' rather than the thing itself being bad? In other words, we could say that it's being valued more than it's worth. But this argument just says it's bad, period, with no nuance. I can't trust someone who talks like that.
AI writing, if you give it a red-team prompt, can at least refine the surface of counterarguments to your claim. But this—from overgeneralization to extremes—is a textbook example of bad human writing