Apple Will 'Watch Everything Burn' When the AI Bubble Bursts

> It very well could crash the consumer hardware market as a result

Tbh, I hope it does. Prices are outrageous, and I'm a firm believer in personal computing/having access to powerful hardware, privately and locally, is hugely important.

On a more selfish note, I miss the days of being able to build an outrageously powerful desktop for myself for relatively cheap. For now I'm still holding onto my AM4 motherboard w/ 64GB DDR4 and an aging GPU, praying my 7 y/o GPU holds up long enough for prices to drop again.

> including agriculture

in fact, agri sees its share of impact now! all of this investment has to come from somewhere, which means that money is getting sucked up into AI from the entire economy. job cuts in tech are part that, part general "de-bloating" of post-COVID tech. retail investors are a lot more likely to invest into AI than any other industry, although there are signs that big players already consider risks of overexposure to AI.

not to mention, agri saw a "bubble" of its own, surrounding Agtech, which peaked at 2021 and has been cooling ever since. scare quotes here because it was nothing like AI bubble

Yes they are. Commodities are things brought to market made with human labor. A wild tomato is not a commodity. A tomato made with human labor and subsequently brought to market is a commodity. A cell phone is a commodity for the same reasons—made with human labor, brought to market.

Yeah, as an android user myself I switch brands all the time, but the iPhone users in my life all bought iPhones 15ish years ago and have kept doing it ever since.

It would be a better way to frame it if we were strictly talking about VR. But my point was to show Apple is not some infallible genius company, they make plenty of mistakes. Why are we assuming being behind on AI is not a mistake but rather amazing foresight is the issue? We are only considering yeah the bubble bursts and apple is like oh yeah dude we told you hahahaha, but what if the bubble doesn't burst? What if there isn't a bubble and it just evolves naturally into something less exciting and fundamentally useful? Wouldn't it be fair to say Apple was wrong in that case? Why are we congragulating them for a hypothetical right and not worried about the hypothetical wrong, both of which are possibilities.

Yes Meta spent 80 billion sure, but did you know Meta never had a loss-making quarter in their entire history as a public company?

My overall point is that its not as clear cut as Apple is smart for willingly not being good at AI and they will win in the end.

Yeah, VR was very clearly useless, and yet...

Do you even know what FOMO is? The money is being spent in physical infrastructure, not the the metaverse.

Given the context of this conversation, one would naturally assume we are talking about commercial public-facing LLMs and not AI as a field.

And how much did A/UX sell? I Have an A/UX coffee mug in my kitchen. It even has a phone number on it.

Still, in the scheme of Apple stuff it was a failed experiment--even if a worthwile one.

> his main thesis that AI companies are not going about this in any sustainable way

The point isn't that his thesis is fucked, just that his analysis tends to be free with details in a way that shouldn't inspire confidence, e.g. mixing up EBIT and EBITDA.

Someone elsewhere in this thread referenced this guy [1]. His takes properly summarise the lack of care Zitron appears to display for getting detailed arguments right.

If you're deeply familiar with financial jargon, I think he's fine. But if you're not, it's easy to get whisked into woo-woo nonsense that's falsely precise due to mis-using (and in some cases, very clearly mis-understanding) core financial and economic concepts.

[1] https://bsky.app/profile/peark.es/post/3mmhtcib3622i

An example of him in July 2024: https://www.wheresyoured.at/pop-culture/

>And yes, that sound you hear is the slow deflation of the bubble I've been warning you about since March...

>How does GPT – a transformer-based model that generates answers probabilistically (as in what the next part of the generation is most likely to be the correct one) based entirely on training data – do anything more than generate paragraphs of occasionally-accurate text?

etc.

Basically the essence is he's skeptical of AI / LLMs being any good so thinks all the investment is down the drain. Meanwhile AI progresses such that Fable can probably beat most humans and IQ tests, maths and the like. And the 'bubble' didn't deflate yet.

Here's some criticism: https://bsky.app/profile/peark.es/post/3mmhtcib3622i (see the full thread)

I'm not qualified enough myself to judge Zitron's reporting, nor this criticism. But George Pearkes is a reasonably respected financial analyst.

> Show us on the doll where Zitron touched you

Comment read sensibly until this bit.

Ya, there are already three pure ad hominem comments here with no examples. Zitron isn't even anti-AI per se. He clearly talks out his ass at times (like AI doesn't work for developers... which he's not saying so much anymore, I don't think) but his main talking points are around numbers and profitability.

I don’t have numbers, but I would like to point out that he's missing a crucial number as well. The fact that maxing out a subscription's limit makes a user generate an amount of tokens that costs much more than the subscription itslef isn't enough to back his claim. What we need to know, is the average use of subscriptions. Think about Gyms. My gut feeling is that, if we run the numbers, we see that by maxing out a gym subscription we can get more value out of it than what we paid for. And still, gyms are profitable because the average customer is using less than what they're paying for. Now, I still think AI companies will have to rise their prices (they are already doing that), but the situation could be less dramatic than what people pointing at those figures based on subscription maxing are claiming.

You're biasing for quantity of argument vs. quality of argument. That's Zitron's MO: writing 10k word rambles that cover 20 topics, ostensibly with tons of links to sourcing, but with most of the sources not actually saying what Zitron implies they do.

Nobody has the patience to read a comprehensive point by point rebuttal to any of it, it's just too tedious.

You say "numbers don't lie". But they do, when the numbers being presented have been adversarially chosen. You just find numbers (no matter how low quality) that fit the chosen narrative, you throw out the numbers (no matter how high quality) that rebut it. If you're trying to predict the future, you can't afford that of bias. If you're an anti-AI grifter, you can't afford to not have that bias, your entire livelihood depends on only showing things that support the narrative.

"The biggest thing we’ve learned from the large language model generation is how many people are excited to replace human beings, and how many people just don’t understand labour of any kind"

Really? I think we've heard C-suite blabbermouths and borderline nontechnical tech CEOs being amplified by social media making these assertions, but boy did the weakly efficient market deliver a relatively swift correction to that mindset, no?

Q: "What would it take to change your point of view?" A: "[AI] would have to solve all hallucinations forever, which they are completely incapable [of]."

Can you produce a human that is infallible? I'll wait.

Finally: https://martinalderson.com/posts/no-it-doesnt-cost-anthropic...

My hot take is AI is increasingly less unprofitable as the cost of serving tokens drops and Nvidia's ongoing offers to guarantee profitability is a sign that it isn't stopping anytime soon.

https://newsletter.semianalysis.com/p/nvidia-gpu-debt-backst...

You either believe in the underlying science and technology or you don't. But in a world where AI is a fad like cabbage patch kids and beanie babies, what's next?

He's a college drop out with no experience in programming or technology.

He has zero numbers and is completely making stuff up to a gullible audience.

The real numbers show high demand for all these services to the point where the companies are rate limiting the services because demand is TOO high.

  “Per my own analysis, NVIDIA’s predicted $1 trillion in Blackwell and Vera Rubin GPU sales (by the end of 2027) represents around 40GW of data center capacity, which will, assuming a PUE of 1.35, result in around 30GW of usable capacity. At a cost of around $12 million a megawatt, that works out to around *$435 billion in global annual compute revenue to make these data centers necessary.*“

This but instead it's people insisting that AI will replace my job (been three months out for at least 3 years now) because they know it involves words.

To be fair he has a background in technology PR and Marketing (which he’s been very critical of) which I would count as more worthwhile when assessing the actual value of the product.

I mean you can say he’s not a “science guy” but he’s undeniably “smart”.

Talking with a friend of mine who's been in development for some time and I had been talking a little bit about the skill required to wield AI effectively and that people were expecting it to be something that required less skill than it does.

He said his version of this observation is "your agents are only as good as you are." I think he's right, and the key is to practice and build the skill.

>> LLM technology doesn't work very well for software development

This comment is so obviously false (in my experience) I'm wondering what sort of niche environment you're working in

While that's true - it does not impute Ed's position with greater accuracy or authority. I don't know if Ed is wrong, but I get this vague sense that he is being led on by his emotions.

I am sympathetic to some of his criticisms that the enthusiasm and financial commitment has run far ahead what can be delivered. But I don't quite share his intensity over the doom and gloom. There probably will be a correction. It will probably sting. But I don't expect it to be the near wipe-out that Ed's passionate voice seems to steer towards.

Not sure about that. As I replied elsewhere, it's a forcing function:

> People misunderstand the point of the tokenmaxxing time period, it was to force people to use AI so as to not have them stuck in their way, as some people are, and then to evaluate how it can help the company.

https://news.ycombinator.com/item?id=49047448#49047826

I think you're absolutely right. Apple couldn't be seen as ignoring the gamer geek space as it wasn't very interesting to them at their scale and that automagical AR was a decade or more away.

Think Apple fell for the trap of assuming they would eventually solve the glasses form factor and then fell for the second trap of convincing themselves that passthrough VR was the same as their real XR vision.

The commodity is not in the LLM but the tokens.

Anthropic's offerings are vertically differentiated. However from an economical stand point, it also be true that they are not the preferred option for many.

They won't. They'll just pay more for the LLM.

I use LLMs all the time, but I'm also a highly capable and experienced engineer that can definitely work without. I have just found that the LLM is a force multiplier, like I haven't had before.

With respect, the way you talk about corrections makes me suspect you weren't working in tech in the US at the turn of the century.

A "correction" in this model isn't a reasoned and gradual re-evaluation of the market cap of every company. It's a broad pullback where people panic and no one wants to be left holding the bag. Money shifts into other assets for years and tech employment, incomes, and the availability of funding takes a big hit.

As to your comment about profitability... every unprofitable company is on a path to be profitable. Some even get there.

Plus, look at it this way: Kellogg's is a profitable company and a part of almost every person's life. Does this make them worth trillions of dollars? No, they just provide boring, commodity products, their valuation is basically a low multiple of the assets they hold and the revenues they bring. There's a future where OpenAI or Anthropic are more powerful than all the world's governments combined, but also a future where they're Kellog's.

That's exactly what a crash is, there's not much difference. For example that's exactly what happened in the dot com era.

You could say this for any new technology though, it's a vacuous statement. No one needs a car, they can ride a horse. But step changes in technology do occur and raise the standard for everyone in a society, hence why we don't see horses for transportation anymore.

You don’t need it, but using it would make you more productive. As an example, I have worked in a code base which is pretty much opinionated. I have many Claude skills to build the boiler plate starting code and tests for the feature I have to build following the existing conventions and patterns in the code base and that saves a lot of manual coding time for me.

This is a very personalised use case, but I think everyone can find these kind of use cases that saves a lot of time for you.

I have been programming for 35 years and a professional programmer for 25 years. Of course I don't NEED AI to program, because I did it before.

This is completely unrelated to the how useful AI is for programming or how much more efficient you can be with it.

I never said you would need AI to do things you can do today. When I said it will not be 'all you ever need', my point is that NEW uses will come that will need more powerful AI. By definition, you can't NEED a new technology to do something that is already being done, because the fact that it is being done already proves you can do it without the new tech. However, that doesn't mean the tech can't do something new that does need the tech.

For example, no one needed an airplane before they were invented. However, you do need an airplane if you want to get somewhere 6000 miles away in less than a day.

There hasn't been a single bit of technology that is 'needed' if you use your strict definition of the word, because obviously humans existed and survived before the technology existed. Being absolutely necessary is not what makes a technology persist or spread, that is an artificial bar to reach.

Some people have such a natural aversion to LLMs that they will make incoherent arguments as to why they should go away. There are plenty of legitimate concerns and critiques of LLMs, you don't need to articulate arguments that you would never make about any other piece of technology to argue against their usage.

Thank you for your comment.

The narrative that LLMs are essential to the future of the trade often feels like an assault on my professional expertise.

Whatever your experience is, mine is that LLMs don't work well for software development. I wish people who use AI would be more willing take that perspective seriously.

Not quite. You could buy a long-dated put if implied vol and current rates are amenable. This protects you against the underlying going up significantly. You might also predict that it won’t go up too much, and just short the underlying with a stop loss.

> you have to predict exactly when the bubble is going to pop

Not true.