Push everybody to buy hardware they don’t need to constantly run agents for pretty basic tasks, such as processing your daily emails and sending you little summaries notifications. So, the most inefficient software tools ever produced, but that keeps the whole industry alive. That’s pretty much the vision Jensen Huang is selling to ensure NVIDIA continues to grow

Ditch the servers.

Do and sync over client to client.

Keep data local again.

Only use cloud for backups of local client encrypted blobs of vectors:data

If you get rid of a lot of the suspect semantics hallucinated up over decades of software development it's not hard to see the geometry of an electronic snowflake. All the language just obfuscates the elegance. Crude meat suit grunts and clicks.

Streamline it all to management of geometric states and access control and put the semantics on the presentation layer. What if we don't need python and go and ruby anymore? Made sense in a pre-gpu everywhere reality. Could just be high school stats classes to generate sets of values. Let go of the obscure linguistic chants.

The data centers are just to serve surveillance purposes. Obfuscated behind politically correct memes of creating jobs.

Chip away at the monolith and atomize the topology

TIL too, but probably what GPUs are good at: optimizing for throughput while hiding latency. Probably better suited for OLAP than OLTP.

[dead]

Microsoft and others report their stake in Open AI as net income. Open AI and others revenue comes in large part from large customers like Microsoft. Nvidia makes large investments into Open AI, SpaceX, and core weave and in return they buy Nvidia hardware. It is all very circular. And at the same time it appears these companies have near zero moat. I think it is foolish to not question how big this business really is. Seemingly no one knows.

Surely AI is a thing that is here to stay, but I am not at all convinced that the big frontier models are going to be able to return their investment and if it becomes apparent they cannot, then you are almost certainly going to see a massive correction.

Core of my comment is 1/ being wrong on timing is being wrong 2/ There is no clear definition of bubble burst. Public markets were down 10% in July and many stocks like SNDK fell 50% -- is this a bubble burst?

> to satisfy demand from a small number of customers who may not be able to pay them

Because a lot of isn't real demand, e.g. given away for free or very very cheap.

there isn't enough demand to raise prices. OpenAI announced price CUTS recently and they are hilariously unprofitable already. Why would they be cutting prices if they have the ability to raise them? outside of this website and the ownership class everyone hates AI

They are pressured by open models to reduce prices, not increase

There is some gold, but it’s a fairly small amount compared to the ATM discussed by AI companies (basically software generation, software security, audio transcripts, translation, image processing, image generation, search, etc). So it’s not like there won’t be an AI industry in the future but it won’t be absolutely everywhere the way the AI boosters are projecting. Inference will be a low margin industry, training will be capex constrained and likely low margin too. And some services on top will have decent margins. But nothing like the datacenters full of PHDs Amodei and Altman are dreaming about.

Just like any other technology

Most tech revolutions end up making a fair bit of money for successful businesses.

There's a lot of money changing hands, at least that's a spoil isn't it? And if the music stops, someone is going to end up holding it.

AI isn't Web3.

Sure. Here's an example:

https://www.wheresyoured.at/exclusive-openai-financials/

Zitron wrote:

> Additional factors – including interest income and interest expense – left it with a net loss of $8.84 billion. It then marked $3.74 billion of losses as “net loss attributable to noncontrolling members capital,” leaving the net loss attributable to the company as $5.09 billion.

> It’s unclear what this means, nor how OpenAI reconciled the removal of $3.74 billion in costs. I will not speculate further.

It is very clear what this means, and no speculation is required if you understand basic consolidation accounting, which you would expect someone in his position to understand.

It's not rocket science: when you have a parent company with entities it doesn't wholly own, the slice of losses belonging to the other equity holders is split out as "noncontrolling interests." Nothing is removed or hidden; the total loss is unchanged, it's just allocated to reflect that the parent company doesn't own the whole. Framing it as OpenAI removing costs implied something sketchy and requiring speculation where there's only routine GAAP accounting.

But it's even worse than this. So many of Ed's claims conflate the foundational R&D and capital expenditures these companies are incurring with the unit economics of their businesses. He seems woefully unable to understand that you could sped gobs of money on the former and still have positive gross margins that scale over time with the latter.

One example - he often compares current revenues to capex being spent on future capacity to claim that AI companies aren't profitable. (See this post for example: https://www.wheresyoured.at/am-i-meant-to-be-impressed/ .)

But this ignores that the capex spent to build more capacity is expected to generate additional future revenue. You don't need to recoup your capex immediately. A better approach would be to amortize the capex and compare revenues to that.

Clearly he assumes revenue won't increase enough to recoup this level of capex (and it's very possible it won't) but IMO it's either a miscalculation of how the financing works or a deliberately misleading framing to compare current small revenues to a big scary capex number.

I'm sure the above is simplified by the way, but I am confident that people who work at Goldman understand the relevant details extremely well.