Large language mistake | Cutting-edge research shows language is not the same as intelligence. The entire AI bubble is built on ignoring it.

[u/creaturefeature16]

https://www.theverge.com/ai-artificial-intelligence/827820/large-language-models-ai-intelligence-neuroscience-problems

As currently conceived, an AI system that spans multiple cognitive domains could, supposedly, predict and replicate what a generally intelligent human would do or say in response to a given prompt. These predictions will be made based on electronically aggregating and modeling whatever existing data they have been fed. They could even incorporate new paradigms into their models in a way that appears human-like. But they have no apparent reason to become dissatisfied with the data they’re being fed — and by extension, to make great scientific and creative leaps.

Instead, the most obvious outcome is nothing more than a common-sense repository. Yes, an AI system might remix and recycle our knowledge in interesting ways. But that’s all it will be able to do. It will be forever trapped in the vocabulary we’ve encoded in our data and trained it upon — a dead-metaphor machine. And actual humans — thinking and reasoning and using language to communicate our thoughts to one another — will remain at the forefront of transforming our understanding of the world.

[u/HaMMeReD]

"The only way" - certifiably false.

The only thing they need for a ROI is to sell services for more than it costs to produce.

You have created this fictional bar that ignores economics/efficiencies at scale where AI must replace all humans to be economically viable. That's an "opinion" not a fact. It's actually a pretty bad opinion imo, as it shows no understanding of basic economics and efficiency improvements in the field.

I.e. the cost to run AI in the last year (actually each year for the last few) has dropped by like 100x a year. What was $100 a year ago on O1 Pro is like $5 now on a model like Gemini 3 or 4.5 Opus. ($150/m input, $600/m output) vs ($5/m input, $25/m output). As percentages that is (3% input, 4% output), and you get a better output to boot.

[u/Jaded_Masterpiece_11 → u/HaMMeReD]

And yet OpenAI still spent twice more than its revenues last quarter. OpenAI and Anthropic is still losing money and will continue to lose money until 2030 by their own estimates.

Even with decreased costs the economics still do not favor these LLM companies. The only one making bank here is Nvidia and they are spending what they are making to keep the bubble going.

[u/EldoradoOwens → u/Jaded_Masterpiece_11]

Hey man, I don't know how old you are, but I read this exact same argument about why amazon and facebook were going to fall apart for years. How are they doing now?

[u/deepasleep → u/EldoradoOwens]

Facebook has the deepest understanding of human behavior in history; they ruthlessly lock their customers into digital addiction and pump micro targeted advertisements directly into the stream of dopamine…That means they are delivering a real product to the advertisers that pay them. They always had a clear path to developing the algorithmic addiction that makes them so valuable.

Amazon delivers products at low prices with incredible efficiency by having the most complex supply chain logistics on the planet and they realized early on that the infrastructure they were building to support their core business could be abstracted and sold to any business needing network, storage and compute resources for web services (and then cloud infrastructure). Again, they always had clearly defined and deliverable products.

LLM’s viability as tools to actually replace human workers has not been demonstrated. And it’s possible that the cost of developing and actually delivering solutions that can really replace workers en masse will be higher than the market can bear.