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.
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.
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.
Actually we can do classical theory of strategic interaction here. There will be a range of acceptable negotiated settlements to both parties since both parties have some estimate E of the expected balance of power resulting after a war. If A is the amount of surplus value Anthropic expects to lose in a war and H is expected amount of value humanity expects to lose in a war, the the range [max(E - H, E - A), min (E + H, E + A)] gives a whole continuum of mutually acceptable settlements.
Now there will be bargaining friction given that any power sharing agreement with Anthropic will likely increase their future capacity and thus the future expected balance of power, but maybe AI has a long enough utility horizon that we should all expect to be dead by the time it realizes the long-term expectation advantage
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