So there are two kind of security, one is preventing innocents who mistakenly brings things like gun or flammable liquid like gasoline. The other is preventing people who actually want to do harm like terrorism. There is no doubt TSA is effective for first group. However the evidence against second group is kind of murky as no country has ever caught anyone in the second group till now.
> It(Solar) works, but it isn't somehow magically better than installing solar panels on the ground
Umm, if this is the point, I don't know whether to take rest of author's arguments seriously. Solar only works certain time of the day and certain period of year on land.
Also there is so limited calculations for the numbers in the article, while the article throws of numbers left and right.
I literally linked the official site and it currently says Facebook. I have known FAIR for many years and I have always know it as Facebook. Can you link any official source of changing the name.
Manufacturing sector has the most job cuts over time because the prediction of China not surpassing them was wrong. Tech employment on the other hand almost never decreased.
While the surpassing is true, something I've found interesting is that across very different industries that have nothing to do with one another, and including publicly traded and private (though still huge) companies, I have heard directly from buyers that top management has given them a directive to find new suppliers in China.
From a supply chain management perspective, this does not make sense. The directive should be something like "find the best suppliers on the planet."
Claude code reached $1B in six months in early Dec and given what I am seeing on ground, I wouldn't be surprised if just in last 2 months after that their revenue grew by double.
Using TPU has the same opportunity cost as GPU. Just because they built something doesn't mean it's cheaper. If it is they can rent it cheaper to save money on paying billions of dollars to Nvidia.
A big segment of the market just uses GPU/TPU to train LLMs, so they don't exactly need flexibility if some tool is well supported.
I assume TPU TCO is significantly cheaper than GPU TCO. At the same time, I also assume that market demand for GPUs is higher than TPUs (external tooling is just more suited to GPU -- e.g. I'm not sure what the Pytorch-on-TPU story is these days, but I'd be astounded if it's on par with their GPU support). So moving all your internal teams to TPUs means that all the GPUs can be allocated to GCP.
Just doesn't make sense. If you make significantly more money renting TPU, why not rent them cheaper to shift the customers(and save billions that you are giving to Nvidia). TPU right now isn't significantly more cheaper to external customer.
Again I am talking about LLM training/inference which if I were to guess is more than half of the workload currently for which the switching cost is close to 0.
> The exception seems to be net new benchmarks/benchmark versions.
How is this an exception? If a genius and kindergarden student takes a test to add two single digit numbers how is that result any relevant? Even though adding single digit number is in the class of possible test.
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