[jbreckmckye]

I don't think so.

His argument is not "this tech doesn't work", but rather "these businesses aren't economically viable"

And that the smoke and mirrors accounting and perpetual thirst for more billions indicates just how unviable it is

Whilst he does dunk on LLM capabilities, the framing is the business angle - can Anysphere etc. actually form a moat and make a profit?

[simianwords]

>His argument has never been "this tech doesn't work", but rather "these businesses aren't economically viable"

Why? because of cost?

[jbreckmckye]

Cost, debt, difficulty forming a moat, gap between what the product promises and what it can do, and the difficulty actually raising capital required.

His style is acerbic and (imo) excessive sometimes. But he's also one of a minority of journos actually looking at the numbers and adding them up. Which seems to be a rarity

[JanneVee]

Well from my point of view. When they talk about gigawatt datacenters, then yes it is economically nonviable. You just need to know the scale of a gigawatt to realize that we need to start building power plants and fortifying the power grid to ship a gigawatt of power to a single location. Until the build out which takes years mind you, it is competing with other consumers of power. Lets take another huge consumer of power like a large steel mills use 100 megawatt. So if that power becomes more expensive because of datacenters, then the price of steel will go up. And if the price of steel goes up it affects a lot of things in the economy.

We are facing a situation that the short term effects are on memory and storage prices going up and lack of jet engines. Long term we wont be able to build actual buildings and ships without financing it with even more debt than today and everyone in the economy is going to service that debt through the price.

[simianwords]

I don't think Ed doesn't comment about the actual tech. Here are some things he has said before and please tell me if these still hold in the spirit?

> You cannot "fix" hallucinations (the times when a model authoritatively tells you something that isn't true, or creates a picture of something that isn't right), because these models are predicting things based off of tags in a dataset, which it might be able to do well but can never do so flawlessly or reliably.

ChatGPT is fairly reliable.

>Deep Research has the same problem as every other generative AI product. These models don't know anything, and thus everything they do — even "reading" and "browsing" the web — is limited by their training data and probabilistic models that can say "this is an article about a subject" and posit their relevance, but not truly understand their contents. Deep Research repeatedly citing SEO-bait as a primary source proves that these models, even when grinding their gears as hard as humanely possible, are exceedingly mediocre, deeply untrustworthy, and ultimately useless.

This is untrue in spirit.

> You can fight with me on semantics, on claiming valuations are high and how many users ChatGPT has, but look at the products and tell me any of this is really the future.

Imagine if they’d done something else.

Imagine if they’d done anything else.

Imagine if they’d have decided to unite around something other than the idea that they needed to continue growing.

Imagine, because right now that’s the closest you’re going to fucking get.

This is what he said in 2024. He really thought ChatGPT is not in the future.

There are so many examples and its clear that he's not good faith and has consistently gotten the spirit wrong.

[energy123]

This guy sounds like an uninformed jackass.

Look at Gemini 3.1 Pro on the AA-Omniscience Index, which measures hallucinations. It's 30, previous best was 11.

https://artificialanalysis.ai/evaluations/omniscience

With the amount of talent working on this problem, you would be unwise to bet against it being solved, for any reasonable definition of solved.