> You have to evaluate every situation you want to use this in, one at a time, against an answer key you trust, and decide what a wrong call costs you there.
Lmao, imagine a time when all of the talking heads are yapping about AGI and you come up with crap that goes the opposite direction and you call it progress... bold.
Lol no one cares. Most of that is smoke and mirrors anyways. Stokes was plagiarized. Most of these "breakthrough" solutions are actually present in the training data and in the prompts researchers and mathematicians input into ChatGPT themselves, prompts OpenAI then steals even when you don't agree to improve the model.
PS: I use LLMs every day, basically let Codex write most of my code (after 15+ years of professional programming), these are amazing tools, smart in some ways, but completely demented in others. People just need to fucking stop being AI doomers and AI coomers. Is this technology great? Yes. Is it worth 10 trillion? Hell fucking no. If we get to a point where RSI is a thing, then maybe. So far it's not a thing and its not even close.
Ed Zitron is the most objectively and confidently wrong human re: anything going on in AI, competing only with the likes of Gary Marcus and, on his bad days, Yann LeCun.
Feb 2024: "I believe we're reaching the upper limits about what generative AI can do and how accurate its outputs can be."
July 2024: "Generative AI, as I said back in March, is peaking, if it hasn't already peaked. It cannot do much more than it is currently doing, other than doing more of it faster with some new inputs"
July 2024: "Generative AI models aren’t getting more energy-efficient, nor are they getting more “powerful”
August 2024: "generative AI is a dead-end technology that has peaked”
Dec 2024: "I also warned you in March that generative AI had already peaked.”
Jan 2025: "I believe we’re at peak AI"
February 2025: "Sam Altman deputizing Orion from GPT-5 to GPT-4.5 suggests that OpenAI has hit a wall with making its next model, requiring him to lower expectations"
April 2025: "It also, at this point, is pretty obvious that generative AI isn't going to do much more than it does today."
August 2025: "These models have clearly hit a wall where training is hitting diminishing returns"
Nov 2025: "the fact we're running out of high quality training data and we're hitting the walls of scaling laws, in the training paradigm, these models aren't getting better. What we're seeing today is pretty much what they're always gonna be like"
"Based on estimates of their burn rate and historic analyses, I hypothesize that OpenAI will collapse in the next 12-24 months unless it raises more funding than in the history of the valley and creates an entirely new form of AI." - Ed Zitron (Jul 29, 2024)
Yes, but clearly that's not what Zitron was implying. The rest of his thread's commentary makes that clearer. He's saying:
OpenAI is going to implode soon. They would have to raise an unfathomable amount of money, it's literally never been done and is so much it won't happen. That's why they're going to collapse.
He could have predicted that OpenAI would raise an unprecedented amount of money and are not going to collapse. He clearly believed differently.
Honestly he's a bit over the top, but the thing he gets right is that he's constantly hammering on the insane financial incentives that everyone in the AI industry has to keep the music going.
Despite the ridiculous amount of capital being spent, the AI industry is still essentially in its startup phase, incubated in the fake-it-till-you-make-it Silicon Valley startup culture. The entire economy has been taken along for the ride. Failure is not an option.
So when the big AI players make extraordinary claims with limited evidence, or when things don't quite add up (like the HuggingFace incident), yet everything somehow seems to lead to "AI is even more powerful than we thought!", I think it's sensible to be skeptical until proven otherwise.
Zitron consistently presents the skeptic case, and many cases the hypotheses he's putting out there seem more plausible than the "official" AI narrative. Simple as that.
Astra, on average, despite its GPT 6 version bump, is not any better at coding than Sol. Some even argue its worse in practice due to the varying quality of its output.
(^ this "swearing at a model" thing has happened to me multiple times on Astra already)
If you have to "debate" the quality of a new Big Number model (and double and triple check your eyes and model setting switches when it pukes up complete garbage), that is NOT a good sign.
There is a theory that they are training them on those benchmark tests. No way to know if that's true, but there is also no reason to trust these companies to not do something like that. They lie a lot.
The "how much time does it save a dev" tests seem a stronger way to measure success, but not seen one of those run for a while.
Not bothered with Astra myself, but the demos I've seen people build don't seem any more impressive on the important stuff. Defaulting to three.js for games just feels smoke-and-mirrors to make them look better, as those games are still as unplayable for the same reasons they were in 2D.
"They get paid anyway" yeah not really. Businesses have margins and marketing budgets. There's only so much you can spend on ads and if those ads don't convert, you go elsewhere, you literally have to. You spends less on Google ads and more or Meta or other channels (influencers, marketplaces, etc. etc.)
Google has to be careful, ads that convert less are less valuable (duh) and what happens is not "well the business will just buy more ads", but "well the business has a 35% gross margin and marketing expenses already account for 20% of gross profit, they can't just buy more ads"
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