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How the AI Bubble Bursts

martinvol.pe

501–510 of 557 posts

Re: How the AI Bubble Bursts

#501
post #207

> Taking this into account, Google is extremely well positioned to weather the storm. When they announce capex expenditure, they don’t spend it overnight. They can simply deploy month by month until their competitors struggle to raise and get forced to capitulate. At that point they can just ramp down the spending and declare victory in a cornered market. They don’t need capex, they just need to make it very clear fo…

What recursive self-improvement?

[dead]

Re: How the AI Bubble Bursts

#502

Earlier quoted context omitted.

There's nothing to "ponder" as you so patronizingly put it, and your stats on gaming are self-evident. Op never said they're selling games. They said they're making their own games and websites for a fraction of the cost (even $0). That's amazing value. And it's just getting better.

that $0 is meant to go on the side of the value add that justifies the sort of funding we are seeing? I didn't mean to patronize, sometimes self evidence isn't trivial to notice.

The funding is in anticipation of AI becoming so good that mistakes are only seen in the most complex output. In consumer applications, it's hard not to see that happening, given the exponential improvements of the past year. Whoever gets there first can capture the market.

Re: How the AI Bubble Bursts

#503
post #464

Earlier quoted context omitted.

your comment sums up the conflict. I dont know if you noticed, but there was a shifting of the goal post from "sub-par" to something wrong/sub-optimal. The best helicopter you can buy may in fact crash into trees sometimes.

Microsoft's products do not occasionally fail, they're constantly going out of their way to block users from doing basic tasks through ads and dark patterns. It makes some KPI go up so some asshat product manager can get a promotion, and they never lose users because 99% of their users are hostages.

I'm not saying they are great. I am pointing out the difference between absolute and relative performance.

You can have a shitty product as long as you are better than the next guy.

My fortune 50 company is migrating to microsoft because they dont like their current tools

Re: How the AI Bubble Bursts

#504

Earlier quoted context omitted.

Demand of tokens is absolutely skyrocketing. And unlike the traditional "this will replace humans right away", I think what this introduce is a lot of incentive to spread those token in places where there was never any incentive to hire a software engineer for previously. In turn, that will drive a lot of business activity in those area that will potentially fail given the current quality of the output. This feels li…

Tulips sales also skyrocketed. Seriously, what value are tokens providing other than justifying layoffs. Concretely. Today. Not in the speculating scenario that cardiologist could be replaced with models. We see this new trend of agentic coding, again a promise software will be written that way going forward, despite the number of fiasco already experienced when trusting a model turned bad. The use case may provide v…

In the last eight months, my solo SaaS has gone from $0 to $325k ARR, and growth is accelerating. I run tens of billions of tokens per month through automated pipelines for the product itself (which replaces an ultra niche human-driven process in a very non-technical industry), plus probably low billions more per month for coding, systems operation and management, data analysis, etc. And I feel like I'm just barely scratching the surface of what today's models are capable of.

Re: How the AI Bubble Bursts

#505

Earlier quoted context omitted.

They are. They're making as many fabs as they can as fast as they can. The bottleneck is ASML, who can only make so many EUV machines. No one else can make EUV machines. Scaling chip fabs and chip equipment is much harder. And you have to understand that chip fabs go bankrupt if demand suddenly drops so they have to be more cautious by default.

If you're really compute constrained do you really need EUV machines? You can make do with DUV fabrication nodes, albeit at somewhat higher cost. The trailing edge is where a lot of the mass impactful innovation is, e.g. trying to replicate more advanced EUV nodes with DUV multiple patterning.

There was a good episode on Dwarkesh's podcast about this in the last few weeks, just a deep dive into the semiconductor industry and what the bottlenecks are.

Re: How the AI Bubble Bursts

#506

> If investor money dries up, they will be forced to cut their losses and pass the true costs to their users. I do not see this talked about often enough whilst everyone is in the process of introducing hard dependencies on these services into their workflows.

Really? Virtually every AI thread on HN has multiple people promising doom and gloom once the labs start passing the "true costs" onto the users. This very post has multiple deep comment chains arguing about this!

Re: How the AI Bubble Bursts

#507
post #341

Earlier quoted context omitted.

Do you feel good about YouTube spending money on hosting and video producers spending time/money on content that you're paying nothing for? How is that sustainable?

The categorical imperative has been put on life support since 2016 at the latest. Everything is smash and dash now. And nobody with the means to change it cares about externalities anymore.

I don't understand any of those sentences. How do they apply to YouTube?

Re: How the AI Bubble Bursts

#509
post #26

Earlier quoted context omitted.

Is that right? I think that you can serve tokens without training the next models. It would be bad strategy, but it would work. So it's an important question, are they covering their operating expenditure? If they are the business has legs (and it will be worth spending a lot to train the next models). If not, maybe not.

If a major model provider were to just halt progress on developing new and improved models, the open weight alternatives would catch up in a couple years. They would have a period of great margin, followed by possibly zero margin as enterprises move to free options. They would have to come up with a lot of great products around the inferior models to justify charging at that point.

> If a major model provider were to just halt progress on developing new and improved models, the open weight alternatives would catch up in a couple years.

That's why it would be bad strategy.

Re: How the AI Bubble Bursts

#510

Earlier quoted context omitted.

They are. They're making as many fabs as they can as fast as they can. The bottleneck is ASML, who can only make so many EUV machines. No one else can make EUV machines. Scaling chip fabs and chip equipment is much harder. And you have to understand that chip fabs go bankrupt if demand suddenly drops so they have to be more cautious by default.

If you're really compute constrained do you really need EUV machines? You can make do with DUV fabrication nodes, albeit at somewhat higher cost. The trailing edge is where a lot of the mass impactful innovation is, e.g. trying to replicate more advanced EUV nodes with DUV multiple patterning.

That’s what’s happening. Companies who were planning a move to advanced nodes for non AI chips are delaying it. All the advanced nodes are going to AI or smartphone chips only.
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