"Applied to 36 and been rejected by 24" as in interviewed with 24 (which would be incredibly good) or been passed on by 24 which is frankly totally normal?
Yes because now it opens the door for future algorithms to chip away at that exponent where as in the past it may have seemed that an exponent of 2 was the floor.
1. you can have luna clean up after itself and improve code 2. you might be doing something like video-editing, cad modeling, artistic direction, pcb routing, etc. that need to run a long time to "converge"
It wasn't really used enough and it sat in an awkward middle space between luna and sol where either luna high/xhigh or sol med were better cost/perf wise
One anecdote for a datapoint: Not sure if it's better now but I've lost a phone in an InDrive and I've lost an expensive bag in an Uber and it was significantly easier and less sketchy to get the bag back. I'm not a price sensitive rider so the insurance of a reputable 'comfort' tier Uber driver paid off. The InDrive driver made me get another ride to him then demanded $1000mxn (~$55usd) to return my phone. The Uber app had me pay ~$250mxn if I remember correctly and the driver promptly returned the bag.
The laws should produce friction but the right friction in the right places. There are too many arbitrary and difficult processes in the US immigration system that keep great people out of the US.
TPUs and ASICs run in data centers too. Your argument only holds true if there's some satisfied limit to demand for inference. If not, data centers will continue to spring up to host more and more agents. Even if agents were running on hardware and software as efficient as the human brain, its conceivable we want trillions of them running at any given time which would require data center scale.
they didn't plateau, the hardware was effectively saturated and it wasn't until later in 2026 that newer hardware came online to provide enough capacity to keep scaling up the models efficiently
As a company... but that includes things like research costs, model training etc. to determine if they're selling electricity at a loss you should look at inference costs bc that's the "thing" they're selling
The underlying idea is that AI capabilities will become so advanced that only AI will enable us to monitor/correct/understand behavior. Obviously this is not without issue and I don't want to try to defend their position right now. But that's what they mean
You can drop react into an html page with a script tag. You don't need a build step. The build step is only requisite if you'd like the full benefits of react, which personally I find worth it. Cached builds are quite fast. All build steps/compilers/etc. exist to add some devex upgrade on top of some lighter-weight thing that many devs find useful.
and if you follow Mexican politics, her politics are almost entirely a continuation of the last president who was her political mentor so it's reasonably well understood what trajectory her term is on
Absolutely true although at some point it's not just raw numbers but also the kernels that run matmuls and there seems (from outsider perspective) to have been more optimization in the cuda kernels
Thank you. Not to go against site rules and veer into meta-discussion on other posters but it strikes me as very odd that a foreigner is just repeating govt propaganda to people who live here.