It’s not under a decade for ai to get to this stage but multiple decades of work, with algorithms finally able to take advantage of gpu hardware to massively excel.
There’s already feeling that growth has slowed, I’m not seeing the rise in performance at coding tasks that I saw over the past few years. I see no fundamental improvements that would suggest exponential growth or human level of performance.
All you really need is for performance to keep increasing steadily at a good rate.
If the exponential growth tops out, and AI only gains a linear two days per year of "task-completion time horizon" once it does? It'll be able to complete a small scrum sprint autonomously by year 2035. Edging more and more into the "seasoned professional developer" territory with each passing year, little by little.
ok, ok! just like you can find for much less computation power involved using a search engine, forums/websites having if not your question, something similar or a snippet [0] helping you solve your doubt... all of that free of tokens and companies profiting over what the internet have build! even FOSS generative AI can give billions USD to GPU manufacturers
[0] just a silly script that can lead a bunch of logic: https://stackoverflow.com/questions/70058132/how-do-i-make-a...
If we don't see some serious fencing, I will not be surprised by some spectacular AI-caused failures in the next 3 years that wipe out companies.
Business typically follows a risk-based approach to things, and in this case entire industries are yolo'ing.
the article's subtitle is currently false, people collaborate more with the works of others through these systems and it would be extremely difficult to incentivize any equally signifciant number of the enterprise software shops, numerics labs, etc to share code: even joint ventures like Accenture do not scrape all their own private repos and report their patterns back to Microsoft every time they re-implement the same .NET systems over and over
How about the fact that AI is only trained to complete text and literally has no "mind" within which to conceive or reason about concepts? Fundamentally, it is only trained to sound like a human.
An LLM base model isn't trained for abstract thinking, but it still ends up developing abstract thinking internally - because that's the easiest way for it to mimic the breadth and depth of the training data. All LLMs operate in abstracts, using the same manner of informal reasoning as humans do. Even the mistakes they make are amusingly humanlike.
There's no part of an LLM that's called a "mind", but it has a "forward pass", which is quite similar in function. An LLM reasons in small slices - elevating its input text to a highly abstract representation, and then reducing it back down to a token prediction logit, one token at a time.
LLM's do not act entirely like a human. If they did, we'd be celebrating AGI!
Don't expect them to show mastery of spatial reasoning or agentic behavior or physical dexterity out of the box.
They still capture enough humanlike behavior to yield the most general AI systems ever built.
This has been demonstrated so many times.
They don’t make mistakes. It doesn’t make any sense to claim they do because their goal is simply to produce a statistically likely output. Whether or not that output is correct outside of their universe is not relevant.
What you’re doing is anthropomorphizing them and then trying to explain your observations in that context. The problem is that doesn’t make any sense.
Those are real examples of the kind of thing that can be found in modern production grade AIs. Not "anthropomorphizing" means not understanding how modern AI operates at all.
You've clearly read a lot of social media content about AI, but have you ever read any philosophy?
Anything that actually works and is in any way useful is removed from philosophy and gets its own field. So philosophy is left as, largely, a collection of curios and failures.
Also, I would advise you to never discuss philosophy with an LLM. It might be a legitimate cognitohazard.
If you don't have anything measurable, you don't have anything at all. And philosophy doesn't deal in measurables.
You're not being serious.
I suspect once you have studied how we actually got to where we are today, you might see why your lack of seeing any limitations may not be the flex you think it is.
There is zero reason to think AI is some exception that will continue to exponentially improve without limit. We already seem to be at the point of diminishing returns. Sinking absurd amounts of money and resources to train models that show incremental improvements.
To get this far they have had to spend hundreds of billions and have used up the majority of the data they have access to. We are at the point of trying to train AI on generated data and hoping that it doesn’t just cause the entire thing degrade.
How can you say this when progress has so clearly stagnated already? The past year has been nothing but marginal improvements at best, culminating in GPT-5 which can barely be considered an upgrade over 4o in terms of pure intelligence despite the significant connotation attached to the number.
Even o1 was a major, groundbreaking upgrade over 4o. RLVR with CoT reasoning opened up an entire new dimension of performance scaling. And o1 is, in turn, already obsoleted - first by o3, and then by GPT-5.
haha, well said, I've got to remember that one. HN is a smelly place when it comes to AI coping.
Now, there’s a little room between the two—maybe the site is full of coders on a cope train, hoping that we’ll be empowered by nice little tools rather than totally replaced. And, ya know, multiple posters with multiple opinions, some contradictions are expected.
But I do find it pretty funny to see the multiple posters here describe the site they are using as suffering from multiple, contradictory, glaringly obvious blindspots.
It took under a decade to get AI to this stage - where it can build small scripts and tiny services entirely on its own. I see no fundamental limitations that would prevent further improvements. I see no reason why it would stop at human level of performance either.