I would think this type of behavior (ugh, or dare I say default mindset) by consumer-facing LLMs will always be desirable for ‘hard’ problems (things previously unsolved) because it’s a bit like having saftey mechanisms in place to prevent hallucinations for users incapable of verifying correctness of the output. You’ve got to do a little work to prove you understand that it’s hard but it’s still something the LLM might be able to accomplish.
I think this is also a healthy mindset for a person to have in many cases. If my boss asks me "go solve P = NP", as extreme example, I would also give some pushback.
I think his point is to do this to understand deeply what they can do, what they can’t do, and what they can almost do. And then find the highest value ‘almost’ use case and push there. Which doesn’t necessarily mean improve the llm, could be applying it in just the right way for the use case. Of course, the bitter lesson makes this hard and risky. But no more risky than investing your time in learning anything else these days.
> This isn't just a new feature — it’s a new way to build software
I imagine they smushed 2 of the most well-known AI-isms together on purpose here to troll the AI-weary. Might as well I guess, if this type of language annoys you then the whole feature probably will too.
The collective harm that this kind of language does to a human skill of writing by oneself is probably immeasurable (that is until some clever social science researcher finds a controlled way to quantifying this).
The full statement:
> This isn't just a new feature — it’s a new way to build software: open, collaborative, and powered by both human ingenuity and judgement and agent scale. Teams that build this way won't just move faster. They'll build things no one else can.
I am not sure how just drawing contrasts between two things without actually drawing any kind of causal relationship to explain _why_ something is better or _how_ it does it, came to be a good thing. It is the kind of vaccuous statement that some poor tired sod with his remaining system 1 capacity just YOLOd into the blogoshpere and, like you said, the weary who don't know any better get FOMOed by. PSA: you arent missing anything.
I was very into PC gaming during this era, and ran a decently sized gaming news website, and Carmacks use of .plan as a one-to-many microblog was really a decade or two ahead of what became mainstream twitter’s primary use case. None of the games I ‘covered’ had enough .plan activity by the developers to warrant an automated script, but I remember being really impressed by the sites that did it (usually id-centric ones like blues news or stomped I think?)
Such good memories. I think my whole career has been built around chasing the feeling I had when making that gaming site.
Effective and clear communication is really important and often really hard for engineers. It is said that one goal of stackoverflow was to help programmers learn how to write through practice, as it’s both very hard and very critical to their effectiveness:
Not a substantive comment on content but hopefully constructive feedback on presentation:
Holy moly, on mobile I was trying to read the example console screenshots/snippets and then it would just unexpectedly change. Took me a little while to figure out it’s some kind of carousel for the examples, and not more screenshots/snippets loading and pushing down content (or me going crazy). Please don’t do this on mobile sites, just let me scroll through the examples!
There’s the chance that you notice patterns emerging that become quite grating after listening to it for awhile, in the same way that LLMs tend to have subtle but eventually noticeable patterns in writing. Some people care, some don’t.
Will that be the case for the music that you are listening to that’s generated by AI, maybe? Maybe not?
By highlighting that the music predates generative AI, at least that’s something that you won’t have to think about.
At least, that’s how I read it. It’s like a ‘no artificial sweeteners’ label on a drink.
Who is going to end up capturing all this value being generated is going to be very interesting. Back in 1980, who’d have thought MS would capture the majority of the value from PCs over the next 3 decades, and not IBM?
Was ms even making that much money compared to actual hardware manufacturers? Ms is licensing the os sure but I mean most of the spend was going to the actual workstation hardware and periphery I’d expect. Including stuff not directly tech like herman miller chairs.
Yes! Microsoft made buckets and buckets of money on products with a unit cost that approaches zero. Hardware was vastly less profitable and there's a graveyard full of PC and server makers that didn't survive. Even the most profitable PC makers (Dell and Compaq during the rise of Microsoft) didn't make anything like Microsoft money.
I don't know how to apply those lessons to AI, as long as AI requires so much hardware to operate. If small models actually get capable enough, the shape of the industry changes drastically.
I'm super enthusiastic about small models, but let's be realistic. A distillation is not the whole model (and, in fact, a lot of the small distillations on HuggingFace are worse than the base model...most of the Qwen 3.6 Opus/Fable/whatever distillations get weirder on some dimensions than Qwen 3.6 alone, as I understand it).
There are little models that are very good for their size. I say nice things about Gemma 4 damned near every day. But, I'm not writing code with it. I am using it for finding security bugs, though, as the 31b variant is outrageously good at it for its size: https://swelljoe.com/post/gemma-4-exceeds-expectations/ and I'm also using it as a base for my own training experiments, specifically the 12b which is small enough to train a LoRA for on my local hardware so I don't have to rent cloud GPUs. The 12b QAT can run on your Pixel 10 Pro today and is frightfully smart for its size, and has great vision capabilities.
But, I keep saying "for its size". You have to be realistic about what tasks these self-hosted models can do. They are getting better though. Gemma 4 31b is competitive with models 10 times its size from a year ago. That's remarkable, and indicates where things are going.
So far, it seems to be the reverse of that disruption. Hardware companies, Nvidia, Apple, AMD, Intel, ARM, memory companies, are all having record-setting quarters, and it's actual profits, not subsidized by investors and circular investments (though the hardware companies are investing in the AI companies to keep the hype train rolling).
It is honestly hard to predict. We are currently in everyone is building website/mobile app/gadget era of AI. Very few places are questioning what is worth building.
Short term, we can compare this to 2-3 recent (mini) revolutions: internet, mobile, cloud. Then the answer is somewhat predictable and (somewhat sad personally). Companies owning the main distribution of intelligence (big labs) or distribution of the app/cloud layer (Google, MSFT, AWS) will make most of the money. In fact Google looks well positioned that way with owning intelligence, cloud (and even hardware, if they can get TPUs right as commercial product).
Long term view is interesting and somewhat satisfying (again, personally). We can compare this to industrial revolution, but for intelligence instead of physical labour. I hope, to borrow from Alan Kay's words, the total value generated will be more than what few big labs can capture. Though we will also see normal market dynamics of boom and bust in play. Companies building something useful, patiently will keep winning the markets. But only to get challenged by newer modes of the technology emerging.
In this long term view, the technology per se doesn't offer monopolistic profits to big labs. I think Anthropic is well aware of this and they are trying to extract as much cash from white collar work automation as they can before things are democratised. Contrary to popular opinion, they are also trying to seek a regulatory capture here by to maintain monopolistic position in the US market by scare mongering about China and open source. Its a case study how they managed to keep the good boy image of themselves while doing this.
In the end, I hope the technology emerges as electricity or combustion engine cars. Yes early pioneers (e.g. Ford) were perhaps able to make lot of money. But eventually, the technology was too important to allow one party to have monopoly and we had an abundance market which enabled jobs and money for a lot more people.
Edit, postscript : Dario, Sam and even Jensen will end up looking like the new the John D. Rockefeller's of this era. I'm personally hoping Demis Hassabis actually solves something much more important (problems in diseases, biology etc) with AI.
> we can compare this to 2-3 recent (mini) revolutions: internet, mobile, cloud.
I would not put "cloud" at the same level as Internet and mobile. Cloud is just a layer on top of hardware that in the end makes almost no difference for Internet to exist and operates. Said differently: I doubt the world would be different nowadays without "the cloud". But it would definitely be different without Internet or mobile (smart)phones.
Linus Tech Talk (LTT) did a whole series on doing this on the pool at the channel hosts’ house. Extravagant home upgrades are a frequent topic on that YouTube channel… business expense write off yada yada. My general takeaway was, yikes, all that piping and infrastructure would be a nightmare to maintain and will likely just be closed off whenever an issue comes up (or he sells). I’m no expert, but I am a home owner, and have come to form a deep appreciation for maintaining simplicity when it comes to the operation of your house.
reply