Why are so many people so sure that the big AI providers are losing money on inference? It reminds me of the comments about how Uber can never make money. Their unit economics were fine and they were only losing money because they chose to do so on customer acquisition.
The only way to avoid extreme power concentration is to ensure we have multiple independent providers of frontier AI models, including open-source options.
However senseless it is, American rhetoric of the non-existence of Canada is concerning, because it resembles the way the Kremlin spoke about Ukraine, and rightly reminds Canada that their sovereignty is indeed the issue.
It'd be pretty annoying if they just start like spontaneously getting notifications during meetings that like, "Oh, it thought that you were thinking about an Uber, therefore it decided to summon summon two for you." And so you'll probably want these to be pretty explicit.
As mentioned before, Uber and Lyft are better regulators than the State’s paper-based taxi medallions, email is superior to the USPS, and SpaceX is out-executing NASA.
For some projects I've started to use Hetzner for vps hosting. I've found you can get more powerful servers for a cheaper cost than with providers like DigitalOcean.
none of us wanted to go through that extreme but lots of time when you are under a lot of pressure and no time to react other than just to survive that scale that keep on coming at you, you have to make uh decision that increase uh speed and velocity because speed and velocity allow us to build quick enough to survive
AB testing doesn't work very well and it doesn't work on most things. It won't work on strategy or vision or insights like nothing actually important to the success of the company. You don't AB test whether Uber is a good idea.
This book is a short but inspiring take on living life on your terms while being pragmatic about money and how to make it happen. Reminds me of a less travel-centric Vagabonding.
if you want a very good all-around model with excellent reasoning. As an open model, you can either use it hosted on the original Chinese DeepSeek site or from a number of local providers.
The book describing how and why empowered teams power the most best product companies like Tesla, Netflix, or Apple. My experience at Uber matches that of the book. My only regret is I could not read it earlier.
A lot of the things listed in the charge sheet are things that lots of websites and communications providers could be said to have done themselves, though perhaps to a different degree.
The Cruise debacle of the last few months proved (once again; remember Uber ATG?) that it only takes one company doing one ill-advised thing to hurt the entire industry.
There have been many novels written in historical modes this year, and I've hated all of them except Fellowship Point by Alice Elliott Dark precisely because that novel feels vibrant and lively and full of characters and it reminds me of early 20th century literature.
Bradley Hope and Tom Wright, Billion Dollar Whale: The Man Who Fooled Wall Street, Hollywood, and the World: Is financial fraud becoming its own sub-genre? This reporting into yet another fraud reminds me of The Spider Network or Bad Blood. What distinguishes this one is the size: it involved billions of dollars.
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