I've sort of lost some respect for ed that I had early on in the hype cycle - he's still right about some things, but I can see him slowly and subtly retreating from his strong position, held even a few months ago, that these things will never ever be useful for anything and it's all a scam because they don't actually do anything at all except burn money. He would say it like 8 times a monologue. I remember one podcast maybe ~6 months ago he brought a developer skeptic on, and was trying to get him to say it wasn't actually useful for coding, and the dev was like "maybe not as advertised, but I definitely use it and it is useful to me" and he pivoted off the topic very quickly.

It seems he realizes he was wrong about that and has pivoted slowly to, "well, maybe they work sometimes, but the cost isn't justified." Which is a reasonable question! I just find his style of never admitting when he is wrong off putting and the way he presents things as absolute fact, when he's guessing like the rest of us. He was right about a lot, wrong about a lot, it's okay to admit that, I don't think his fan base would care.

That's essentially how you become an online pundit. The internet rewards provocative takes. If you have a tendency to doubt yourself and revise your views, then (a) your views become less provocative and thus less likely to translate into click-worthy headlines; (b) you end up biting your tongue or saying "I don't know" often enough that is becomes impossible to keep up with the requisite weekly publication schedule.

Which is to say, it's easy to scapegoat this guy, but I think his approach is not any different from other "opinion piece" bloggers that we all tend to reshare.

This is exactly how I feel about him too. I also find his "number big" approach to writing ("check out my 18,000 word blog about something I'm learning about in real time") off-putting, so I've completely stopped engaging with it.

We need better critics of the industry.

I’m remember when CrowdStrike caused that huge outage, he basically blamed Windows / Microsoft for it. I kind of stopped taking him seriously after that. I more-or-less agree with his point of view, but he seems more interested in selling outrage rather than journalism.

I've only read a few of his pieces here and there and had just assumed he was an AI skeptic, so I never thought his position was LLMs would never be good for anything at any price. That's a pretty extreme thing for any serious person to have ever claimed. Frankly, it seems more like a straw man exaggeration of AI skepticism. I consider myself to generally be an AI skeptic, but to me that means skepticism about:

1) Nearer-term investment returns on AI businesses and data center build-outs.

2) Claims that LLMs are now (or soon will) rapidly displace most/all senior positions in certain high-skill professions (eg software engineering, music/film making, etc), leading to less overall jobs for those kinds of workers and mass unemployment.

3) The "Foom" overnight takeoff hypothesis that AI will soon be able to iteratively sustain substantial self-improvement directly yielding profound new fundamental capabilities across infinite generations with no human involvement.

I've never thought that AI isn't already quite useful for some things today, or that no investors will ever make money on AI, or that AI won't displace some workers in some types of jobs, or that using AI isn't already helping accelerate the development of AI. Just that there's been a lot of hype, exaggeration and over-estimation about how much impact, how soon and how broad. There will be a few instances of rapid, large impacts but the majority of it will be slower, more gradual and less disruptive than extreme predictions - and many of the most over-the-top predictions may not ever happen. Not because they can't happen but probably for more mundane economic, logistic and human-factors reasons along the lines of why we're no closer today to the 1950s visions of a flying car in every driveway.

The economics is spending a few hundred bucks on software for an IC you're already paying over ten grand a month in order to make them more productive. How are supposedly smart industry experts not seeing this obvious fact? Are these guys actually experts?

His reasoning about costs are also completely flawed. API fees aren't the providers' costs. It's a largely arbitrary number that they think they can get away with based on what everyone else seems to be doing that they also expect to cover on-demand usage as well as their research, marketing, and stock buybacks. They likely have a 60-90% gross margin.

Ed's writing style is often off-putting, repetitive and sometimes gives almost "desperate" vibes. But he does raises questions no one in the industry is seriously entertaining and exploring. What if those monsters are indeed unprofitable, now what? So while I stopped reading him regularly, I visit once a quarter just to read something not about our inevitable benevolent apocalyptic LLM gods and their Prophet St. Sam, prophesying a complete job loss and despair.

This reminds me of a Bitfinexed blog situation. That guy researched and proved Tether token scam for years and he was right. But he didn't account for a tiny nuance - Tethers are useful for financial crime and are propped by that public regardless of the financial viability or rejection by every decent financial institution. Turns out you can have a hundred billion of unbacked tokens, if they are "alternatively backed" instead. I suspect LLM monsters may turn out the same way (or not).

Serious question - are there any LLM bubble critics with more sane and to the point style of writing and not just posting unsubstantiated hype for views like most on YT?

Weird, especially since a lot of us have similar opinions. Was he saying that from the start and since shifted focus to it or is it completely new? The conversation about cost isn't exactly a new one.

I am sympathetic to his view because I also considered the whole AI hype train a complete scam until pretty recently. When I saw enough people validating that coding agents were actually legitimately ok and sometimes good at things, I decided to spend $50 on one to test it out.

I have been pleasantly surprised at its utility knocking out grunt work. It's not super smart, but it's great at things like writing a python script to edit characteristics of a jsonl file or sorting structured data. I didn't ever expect it to be useful beyond extremely limited output and it's actually kinda good when you know how to narrowly target the tasks. The constraints of code make it a more suitable category than all the other stuff.

It's still a bs hype machine with Elon saying it might save all of humanity in court today. That's pretty unlikely.