Conjecture supported by allegories that break down quickly. Arguments conflating the dot-com boom with the current AI boom even though the economics are wildly different. Dismissive arguments conflating anti-AI constituents with people who were against cars, etc...
AI is highly divisive. It's dramatically reduced the value of code, which has derailed a lot of careers who have built their entire adult life around the idea that code would remain valuable, while simultaneously driving others into a psychosis who believe that AI can do anything.
Excellently put. IMO the worst/scariest thing about AI is what it has done to the methods and work habits of some of the people who I've always looked up to as good software engineers. They now earnestly say things like "We don't have to look at code, understand it, or review it anymore. AI does all that." and "We don't have to test our software because if a bug is found in prod, you just tell the AI to fix it and deploy it instantly." Decades of software best practices thrown out the window in a year because of this psychosis!
> It's dramatically reduced the value of code, which has derailed a lot of careers who have built their entire adult life around the idea that code would remain valuable
I just don't relate to this sentiment. I wasn’t the fastest typer or the quickest at designing a solution pre-AI, but I was able to learn, build, and maintain systems. My value wasn’t in how fast or how much code I could write, it was in my ability to understand what the hell is going on and do something with that knowledge.
That’s still the case now, even though Kent from Accounting could theoretically one shot some of the software I build. He wouldn’t know what to do with the software, and he wouldn’t want it because now it’s his problem.
The tech industry oversees invisible Rube Goldberg’s machines of flowing electrons. Most people don’t want to learn or deal with its issues. And since AI is yet another complication piled on top of the machine, I feel confident that my career will still have value.
They’re something like 5% domestically, a little less if you include all budget devices, a little more if you only look at “premium” phones in its price category.
It’s likely made no impact on iphone sales, but I don’t think it’s a reasonable goal. Android and iPhone users don’t meaningfully switch, the goal would be to gain Android customers, and it seems, drive market direction. 5% of all US phones, which is 10% of android phones, doesn’t seem terrible considering they’re certainly spending a lot less than Samsung et al in R&D
Virtually nothing. Their processor is at least seven years behind the times. It’s not profitable. It’s just a Me-too loss leader to service the ad machine. 3D models and data-centers are built on top of that.
All Google loss leaders to service the ad company, Microsoft is also running into the same problem. Xbox, Blizzard games and Copilot are not profitable and to top it off. Between the two of them, they have spent upwards of $330 billion dollars in 2026 on AI models and AI CapEx. Microsoft laying off 60,000-70,000 people didn’t come out of thin air.
Wow! This is very cool. I had an idea for something very similar to this when I found out the US federal government offered API keys, maybe three or four years ago. I found that while Congress did list bill revisions as they were made the format and retrieval of these was not an easy task. The idea was that I wanted to look at any line of any bill and see who proposed it that particular line’s inclusion.
For the record, and feel free to steal it if you like it, I called it “G(overnm)it-blame”
Linear programming admits a worst-case polynomial time algorithm.
It is notable that simplex, especially dual simplex is often better in practice, especially for integer linear programming with branch and bound because you only have to slightly modify the parent optimal basis in simplex vs entirely restarting or refactorizing for interior point methods.
It's NP-complete problems if "subexponential" means O(2^{n^{\epsilon}}) for every \epsilon>0.
If subexponential just means 2^{o(n)}, (as it is here, O(2^{n/\sqrt{\log n}})), then no. E.g. if the cost of the reduction took you from n to \sqrt{\log n}n, then you'd be back to exponential time. The Subexponential Reduction Family is the class of problems that preserve subexponential time in the second sense.
I said the same thing in another thread and someone compared it to no one forcing you to own a smart phone. I will preempt that argument by saying the community is motivated to verify these results because they are important to the field.
reply