I'm excited for the AI wildfire to come and engulf these AI-written thinkpieces. At this point I'd prefer a set of bullet points over having to sift through more "it's not X (emdash) it's Y" pestilence.

The metaphor sure seems plausible, but why does the whole thing read like a LinkedIn post that was fed to an LLM to farm attention? :(

With little growth and hiring happening outside of firms betting the farm on AI—and getting the funding to stay alive and play the lottery—what is a random tech employee supposed to do here?

It seems like right now the most rational move to stay in the industry is to milk the AI wave as much as possible, learn all of the tools, get a big brand name on one's resume, and then land somewhere still-alive once the AI music stops? But ultimately if nothing outside of AI is growing, it's one big game of musical chairs and even that might not save you?

> AI inference demand is directed at improving actual earnings. Companies are deploying intelligence to reduce customer acquisition costs, lower operational expenses, and increase worker productivity. The return is measurable and often immediate, not hypothetical.

Is the return measurable and immediate?

Is it really?

> training compute looks more like an operating expense with a short payback window than a durable capital asset

Today they are a durable asset functionally, longer than they are economically. So there is no reason in a market with less demand, that their economic payback windows cannot be extended further into their functional lifetimes.

There will be energy cost incentives to replace GPUs. But turnover can respond sensibly to demand as it revives, while older GPUs continue working.

Also, the data centers themselves, and especially any associated increase in power generation, will carry forward as long term functional value.

I doubt any downturn in compute demand lasts long. The underlying trend, aside from AI, was for steady increases in demand. Regardless of bad AI business models, or investment overhangs, a greater focus by more entities on AI product-market fits, along with cheaper compute, will quickly soak up cycles in new and better ways.

The wildflowers will grow fast.

I don't see how nvidia come out of this stronger

their huge customers will be able to produce ASICs hat will be faster and cheaper to operate than their GPUs

jensen has to be the luckiest man in the world, first crypto, now "AI"

The text reminded me of one of Veritasium's latest videos [1] about power law, self-organized criticality, percolation, etc... and it also has a wildfire simulation

[1] https://www.youtube.com/watch?v=HBluLfX2F_k

VC is inherently high risk capital. It's by design most companies will fail or at most break even via acquisitions/acquihires, while a small few make investors massive amounts of money.

The only real difference this time around is all of the datacenters being built. There's real hard asset costs making it much riskier and capital intensive.

In other words, which companies are default alive or dead? [0]

The companies that are sustainable with their own revenue, covering their runway or nearly there, are likely to be alive if there’s not investors to keep them alive. Those with ridiculous commitments expecting a hail mary until their business model materializes, are living on borrowed time

0. https://paulgraham.com/aord.html

> The next cycle, driven by social and mobile, burned again in 2008–2009, clearing the underbrush for Facebook, Airbnb, Uber, and the offspring of Y Combinator.

This list of companies made me wonder a bit. Technical progress has been huge, no question about that. But as for the actual quality or experience for the user/customer - I have the impression everything got worse, starting from Google from the first wave.

Framing this as something cyclic as the rest of the world is static may be a mistake if things have deep changes outside (related or not with what is being done here), or the nature of the field radically changes.

Then the cycle is broken, and there might be no survivors, or the regrowth may be so far into the future that it will make no difference for most of the survivors.

Does OpenAI and/or Anthropic survive the wildfire? Do one or both of them become the next Google? Or do they become Netscape and Google, Microsoft, et al win in the end?

AI is the only 'technology' that nobody knows what it solves. If it is a fridge, people buy it. If its a dishwasher, people buy it. The use cases of these technologies are immediately understood. AI is pushed down hard by the 'leaders', C-suite is pushing everyone to use AI at most companies. Nobody knows what its supposed to help with but a great many people claim 'success' with AI. Every full text search that was perfectly working before got converted to AI search and is instantly 100x worse. Same with lots of customer facing FAQs, customer support, etc.

Meanwhile, 67% of my time is gone fixing autocorrect on apple devices.

> Every promising engineer, designer, or operator is being courted by three, five, ten different AI startups, often chasing the same vertical, whether it’s coding copilots, novel datasets, customer service, legal tech, or marketing automation.

This is flat out wrong.

> The next cycle, driven by social and mobile, burned again in 2008–2009, clearing the underbrush for Facebook, Airbnb, Uber, and the offspring of Y Combinator. Both fires followed the same pattern: excessive growth, sudden correction, then renaissance.

The GFC doesn't have anything in common with the .com bubble, maybe we'd have see another tech bubble in the first 2010s if there were not a GFC, but it's fundamentally wrong to place those 2 things nearby.

These analogies are like fitting a curve to align with the data. Let the new data come in next year, the curve changes to fit that data as well. Any data can be curve-fitted and be seen as following some pattern.

It is not that simple. You need to consider factors outside of the silicon valley, outside of USA, outside of technology business. There is lot of world out there. These analogies and predictions don't come out into the global scene to have a look at the what's going on across the globe.

The bubbles which happened earlier are not insulated phenomena that happened in silicon valley labs. It is a complex interaction between various forces.

For example, social and political norms may turn against all that is AI. Any AI-enabled service or product might be seen as serving plastic food.

Ummm... Google, Amazon, eBay, and PayPal... Facebook, Airbnb, Uber, and the offspring of Y Combinator... doesn't look like a particularly virtuous trajectory to me.

I think.. after reading this article twice that, if it is indeed presented accurately and if the table participants are not just trying to drive a specific agenda, is it applying the wrong metaphor.

It is not a bubble. It is not a fire ( cleansing or otherwise ). It is, however, a piece of technology that is, misguidedly, plopped hard into everything without regard for what it is actually good at. This is why I despair when I see AI in notepad or "ai protects okta'.

I am concerned, because I do see a big change on the horizon coming, but it is not the change that is being presented. It may not be the feared ai/agi/asi ( depending on one's particular bent ),but rather deep re-entrenchment of existing ecosystems in ways that will make things a lot more difficult overall.

Here is what I mean by this:

- the internet as we once knew it, is effectively dead - the ones who can ( money-wise and knowledge-wise ) and see the need to, move behind local networks - those that can't ( money-wise, knowledge-wise, or circle-wise ), are forced into locked systems that effectively become AML for... anything ( and if you did not experience it yet, I am assuming you did yet try to buy anything that has -- lets call it -- dual use )

It is bifurcation ( or what some media call k-shaped these days ), but it is not a fire at all. If anything, these are very, very aggressive vines.

I think this article is nearing the truth in the future of AI. I think the avoidance of claiming it is a bubble is a good sign, but saying it's an AI wildfire is still hyperbole. The idea that inference will drive compute demand is not what I experience because inference is a much easier problem than training. The training of an AI (LLM) is especially demanding and if and when we complete that, inference will be a piece of cake.

I think the best metaphor will be the California gold rush. There is definitely gold there but most of it has already been mined. The people who are entering at this point are woefully unprepared, assuming that they can vibe their way into a fortune, when the rest of the gold requires hard earned labor.

It is worse than in 2000 now. Amazon, Microsoft all had good products back then. Amazon was in fact better than it is now.

"AI" hardly has any working products. Vibe coding is foisted upon companies by CEOs who want to promote their friends' products or who want to use it as an excuse for firing people or who have circular revenue agreements with other companies.

This is like the housing bubble of 2008 which was based on hot air and incorrect algorithms.

> Businesses aren’t asking “do we want AI capabilities?” They’re asking “how much can we get, and how soon?”

This is only because businesses are full of folks with short-sighted FOMO desperately trying to cram AI features into any product they can. AI is the new digital clock.

    the number of expenses required to minimally live
       (ex:utilities, transpo, insurance, comms) and
    the ever escalating costs of those added requirements

"The Bubble is Good Actually" cope cope cope.

If energy is indeed the limiting factor here, then maybe the companies building space-based compute (in which energy scales linearly) will remain after the wildfire.

The key is for them to build before the money runs out--I'm not sure they will have enough time.