cmiles8

All indications are there will be a lot of repossessed GPUs appearing on the market before too long. Likely to be messy for a while but will open up a lot of possibilities when it’s easy to get your hands on some secondhand GPUs.

But wasn’t fable distilled from knowledge taken from others? I get why Anthropic is angry here, but it would appear they’re not really in a position to complain about this.

Some CEOs are genuinely good, but the buzzword-spouting MBA types? Fire away.

Frankly, when people worry about “AI eating jobs,” it’s these MBA-manager types who are probably most ripe for role elimination.

AI helps doers do more, but it also means we need vastly fewer people whose job is just to coordinate, summarize, manage, and relay information but fundamentally aren’t the ones innovating, building, or doing.

Oracle is increasingly looking like the Lehman Brothers of the AI boom. One day it will all go pop and the cards will start crumbling elsewhere in the industry.

Being first rarely matters in tech. Fast follow that’s “good enough” and cheaper eats “first” for lunch all day long, and that’s the pattern starting to play out.

What evidence says otherwise? OpenAI is projected to have massive losses for years to come and all indications are that’s driven by the cost of compute being far higher than the revenue generated by said compute.

Four things are currently correct:

1. There is a huge demand for compute, specifically GPU compute

2. Infrastructure providers are building like crazy, including taking on massive debt to fund this because their own cash flow can’t cover the bills

3. The demand for that compute is broadly being paid for with investor dollars pumping up the valuation of AI companies, not cash flow from said companies. If those subsidies go away these companies can’t pay for the compute they’re buying.

4. Those that own a lot of compute are starting to offload it, looking for interested buyers (e.g., Meta looking to build a cloud biz or SpaceX selling its excess compute to others).

All while advances in open weight models are making it appear that the major labs truly have no model moat.

Put together those 4 things paint a very ugly business and financial picture that seems unlikely to just correct itself naturally. History tells us, very clearly, that “the way out” of such a scenario is a series of events that is likely to leave some of the current players severely damaged if not simply out of business.

What’s the over under for this being another AI-fueled engineering screw up for AWS?

There’s still really nothing keeping it at even these lower levels except pure hype. By the fundamentals typically applied to aggressive growth companies a “sane” price is closer to $40-60 and even that would be very aggressive considering the company’s financials.

If the company doesn’t quickly show a financial picture that matches the sky high pro formas then even anything close to those levels will become extremely hard to justify.

The bond markets have already turned very negative on SpaceX with extreme red flags developing there.

Tl;dr is:

A temporary overvaluation can build enough real capital that the economy lands in a permanently higher-capital equilibrium, even after the inflated valuations correct. The future for AI companies may look rather iffy, but the whole economy may not be as screwed as some fear.

“Marketing” typically includes all the people in solutions architecture, developer advocacy, compute credits, and many other things. It’s a ton more than just advertising spend, which is often a minority of what appears on that line item. Given that it’s very plausible those sort of sums are realistic.

Bingo

Stay well diversified, keep investing each month, and take a nap.

There are almost surely severe bumps ahead for the AI space and that will likely spill over into the broader market. But unless you’re retiring in the next few years don’t worry about it. You can’t time the ups and downs and the only proven strategy is to just keep investing in a broad indexed portfolio and just ride out. You’ll take a short term hit but also end up buying on the dip because you don’t stop investing.

A bunch of press on this today you can look up. Demand on the offering was much lower than expected and what materialized in prior rounds. Amazon had to sweeten the deal to get the money loaned.

Well there is clearly also a lot of non-GAAP style “trust us bro” things going on too which generally boil down to “if you ignore all the reasons why we’re not profitable then we’re profitable.” It’s WeWork’s “community adjusted EBITDA” messaging repackaged.

The bond market is measuring the risk of repayment though not the success ROI of the dollars invested by the company (that impacts the stock price but not so much the bond price). The bond markets are hiccuping on AI because there’s growing concern that these loans simply won’t get repaid.

The general fallacy of the “but inference is profitable” argument is that it tends to ignore all the costs of building and training the model. Given the fact that 1) that’s not trivial, and 2) the arms race underway means one can’t stop training, then it ruins the financial picture.

It’s like saying a new apartment building is “profitable” because the monthly income covers the monthly running costs, but ignoring the giant mortgage that covers the cost of building the building. That thinking is a good way to go bankrupt in real estate and a good way to go bankrupt in AI.

Market signals on an impending AI bust are broader than just Oracle’s woes.

For example, Amazon just had a challenging bond offering where the market is clearly starting to seriously question the ROI on all this money being pumped into AI buildout. That does not bode well at all for AI-only companies without broader cash flow from other businesses. And when the cash dries up this whole thing comes crashing down like a house of cards.

Yeah no. Almost everything people are pushing back against is branded as AI data center expansion. Moving to the cloud doesn’t need net new data centers being build… that’s just workloads moving from one data center to another.

In US politics at least that’s plenty to shut things down, which is exactly what’s happening.

Exactly. Towns are also increasingly nervous that when the bottom drops out of the AI bubble they’ll be left with abandoned half-built data centers blighting their communities.

It’s a serious concern that looks increasingly plausible. The bond market for financing buildouts is looking shaky and even Amazon struggled there in its last go at loaning money to fuel the buildout. That doesn’t bode well for others.

Small town politics generally fly below the radar but this is a real hot button issue in a growing number of communities. Town meetings are dominated by residents lacking the room for otherwise sleeping zoning hearings that nobody attends. Folks don’t want data centers in their town and they’re increasingly successful in chasing developers out.

Outside the bubble of tech the attitude towards AI and everything associated with it has turned quite negative. It’s hard to see that sitting in silicon valley but venturing out into “the real world” it’s hard to ignore.

All that AI capital investment is flowing down into construction, utilities, raw materials and many other industries that on the surface appear unrelated to AI.

That’s currently all being kept alive by artificial cash flow broadly funded with loans and VC investment. When that hiccups the blast radius is much much bigger than a few AI companies just folding.

Good advice. Ironically most long term folks that just buy low cost index funds and take a nap outperform most of the market stressing out daily on their next move. That’s the cruel reality of investing.

When you factor in the opportunity cost of all that stress and managing an active portfolio the percentage of successful active portfolio managers likely falls down to single digits.

Invest early, invest consistently and often in up or down markets, and the math says you will do very well.

There’s always money to be made in a bubble implosion. The challenge is there’s a very thin line between major bank and losing your shirt. Because of that most long terms smart investors just sit it out which is likely why you see Berkshire sitting on treasury bills.

There’s really not much question we are in a giant bubble that’s broadly been fueled by AI hype. The only serious question is how do we get out of it.

In a controlled scenario the AI sector gets a severe correction with many AI-focused companies wiped out but broader damage more limited. In an uncontrolled scenario the AI bubble bursts and takes the whole economy with it.

The likelihood of a scenario where suddenly the economics of AI suddenly start to make sense and enough $ flows in to make the present valuations defensible seems around 5% now and rapidly falling towards zero.

It’s all fine till it’s not. Then it’s a gigantic financial house of cards that comes crashing down.

OpenAI are really starting to look and smell like “the bad guys” in the industry.

When the AI bubble cools these roles will be eliminated faster than you can blink. Mark my words.

There’s a difference between proprietary software thats highly profitable maintaining a stronghold over “cheaper” options and a massively overvalued and artificially inflated ecosystem having to confront economic realities.

We are seeing the later start to unravel.