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95% of Companies See ‘Zero Return’ on $30 Billion Generative AI Spend, MIT Report Finds
(thedailyadda.com)
this post was submitted on 21 Aug 2025
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Who could have ever possibly guessed that spending billions of dollars on fancy autocorrect was a stupid fucking idea
Fancy autocorrect? Bro lives in 2022
EDIT: For the ignorant: AI has been in rapid development for the past 3 years. For those who are unaware, it can also now generate images and videos, so calling it autocorrect is factually wrong. There are still people here who base their knowledge on 2022 AIs and constantly say ignorant stuff like "they can't reason", while geniuses out there are doing stuff like this: https://xcancel.com/ErnestRyu/status/1958408925864403068
EDIT2: Seems like every AI thread gets flooded with people with showing age who keeps talking about outdated definitions, not knowing which system fits the definition of reasoning, and how that term is used in modern age.
I already linked this below, but for those who want to educate themselves on more up to date terminology and different reasoning systems used in IT and tech world, take a deeper look at this: https://en.m.wikipedia.org/wiki/Reasoning_system
I even loved how one argument went "if you change underlying names, the model will fail more often, meaning it can't reason". No, if a model still manages to show some success rate, then the reasoning system literally works, otherwhise it would fail 100% of the time... Use your heads when arguing.
As another example, but language reasoning and pattern recognition (which is also a reasoning system): https://i.imgur.com/SrLX6cW.jpeg answer; https://i.imgur.com/0sTtwzM.jpeg
Note that there is a difference between what the term is used for outside informational technologies, but we're quite clearly talking about tech and IT, not neuroscience, which would be quite a different reasoning, but these systems used in AI, by modern definitions, are reasoning systems, literally meaning they reason. Think of it like Artificial intelligence versus intelligence.
I will no longer answer comments below as pretty much everyone starts talking about non-IT reasoning or historical applications.
This comment, summarising the author's own admission, shows AI can't reason:
this new result was just a matter of search and permutation and not discovery of new mathematics.
I never said it discovered new mathematics (edit: yet), I implied it can reason. This is clear example of reasoning to solve a problem
You need to dig deeper of how that "reasoning" works, but you got misled if you think it does what you say it does.
Can you elaborate? How is this not reasoning? Define reasoning to me
While that contains the word "reasoning" that does not make it such. If this is about the new "reasoning" capabilities of the new LLMS. It was if I recall correctly, found our that it's not actually reasoning, just doing a fancy footwork appear as if it was reasoning, just like it's doing fancy dice rolling to appear to be talking like a human being.
As in, if you just change the underlying numbers and names on a test, the models will fail more often, even though the logic of the problem stays the same. This means, it's not actually "reasoning", it's just applying another pattern.
With the current technology we've gone so far into this brute forcing the appearance of intelligence that it is becoming quite the challenge in diagnosing what the model is even truly doing now. I personally doubt that the current approach, which is decades old and ultimately quite simple, is a viable way forwards. At least with our current computer technology, I suspect we'll need a breakthrough of some kind.
But besides the more powerful video cards, the basic principles of the current AI craze are the same as they were in the 70s or so when they tried the connectionist approach with hardware that could not parallel process, and had only datasets made by hand and not with stolen content. So, we're just using the same approach as we were before we tried to do "handcrafted" AI with LISP machines in the 80s. Which failed. I doubt this earlier and (very) inefficient approach can solve the problem, ultimately. If this keeps on going, we'll get pretty convincing results, but I seriously doubt we'll get proper reasoning with this current approach.
But pattern recognition is literally reasoning. Your argument sounds like "it reasons, but not as good as humans, therefore it does not reason"
I feel like you should take a look at this: https://en.m.wikipedia.org/wiki/Reasoning_system
If we're talking about Artificial INTELLIGENCE, then we should talk about "reasoning" as an ability to apply logic and not just match patterns. Because pure pattern matching is decidedly NOT reasoning, because if the pattern changes even a little (change the names and numbers, keeping the logic intact) all models start showing failures. So, yes, some people decided to reframe what "reasoning" means in this context (moving goalposts), but I'm pretty sure that 99% people who use the term when referring to AI don't mean reasoning like that. Regardless, it's not actually that of an interesting discussion, not do I actually care that much. So, sure, I'll give you that point.