AJRF
Since the start of the year the market has shifted from 50/50 split (closed v open weights) to 30/70 (70% of usage they see through their platform - is now open weight)
DeepSeek V4.1 Flash 1017 sees 5x the weekly token usage through OpenRouter than the closest closed weight model (GPT-6 Luna)
Even though OpenRouter is only one limited view of the market - those trends should be worrying to potential investors.
Even if the tech + business fundamentals don't match reality, there's just so momentum in favor of a "win" here.
What we have today is interesting tech, with many, many applications - but the path to the kinds of things mentioned in this prospectus have no clear path, it seems like scaling laws are plateauing, but those invested speak as if it's a foregone conclusion we get AI we see in science fiction movies.
There is a good documentary called "All Watched Over by Machines of Loving Grace" which documents how computing started, the touted benefits (it would fix society, all illnesses, liberate humanity from work) - and the slow decline in optimism towards what we have today. I feel like AI will play out the same way.
If you continue down this path, your golden goose is COOKED
RubyGems should sue the everliving daylights out of OpenAI for this.
React Native gives you (with asterisks) - one "source" for things to go wrong (as it sits on top of the native implementations of the UI + Native APIs). You are writing at that source level, and that filters down to the native builds. I am WELL aware to do certain things on each platform you need to get your hands dirty, but most apps are just serialising JSON from a database and displaying it.
AI writes very buggy, sloppy code.
They've decided - instead of containing that code to 1 surface, they would now have 2 surfaces they throw slop on top of.
I look forward to the 2027 version of this where they've gone back
Why leave that aside? That is _the_ story.
If a Chinese research lab did this we'd call it espionage.
Yeah so unverified PR's is super annoying, but people using LLMs to answer things incorrectly they could look at themselves is a big issue too.
I often hear this get dismissed along the lines of "oh you didn't context engineer hard enough" - but the default state of the model is to very confidently state a thing to be true when it hasn't searched correctly.
That is a trait of a very junior engineer - one who, if they never learned to fix this behaviour would be fired.
It seems objectively _worse_ than what we had before - trained engineers who gained wisdom over a long time horizon and had a reputation they'd lose if they kept incorrectly stating things.
I'm just building some data points.
If you discard coding purity questions like style, architecture, cleanliness - the stuff they come out with is buggy & error prone.
The problems seems architectural - in that context windows are limited and you need more compute to increase them, married with the fact the models are really over confident. But if you do increase them it causes mode collapse. Yann LeCun has a really good graphic in his slides of a circle (all possible answers) and a red line coming from the centre depicting the one correct path. How do you actually stop the model going into the subsequence of wrong paths? I don't think it's possible.
I've had so many times in my day job someone has told me (Claude told them) there is a bug in my code, I look at it and nope - it just didn't look up the right file. Then you push back on it and it completely crumbles and says sorry.
I wouldn't keep an employee hired who did that over and over again and never learned
and a arch linux reskin with a tiling window manager + his companies apps pre-installed is the way to do that?
I've never seen such a lively crowd for a talk in all my years, Cliff was absolutely electric.
DefCon 34 – Stalking the Wily Hacker: 40 years later [video]
Are we wink winking that it's a lot of fixes?
I've worked in tech 12+ years and I _hate_ when a Passkey prompt comes up, its only ever slowed me down.
But the devs who work on them are quite rabid, and keep dismissing real criticism of their implementation.