171–180 of 186 posts
This is why Nvidia needs competition. I love the performance of their hardware and the quality of their drivers, but I don't love being their customer. They have a long, long history of price discrimination using techniques like this. Back in the day it was "workstation" graphics for CAD programs that they would nerf for consumer cards by downgrading various features of OpenGL. Different markets, same techniques. It'…
Earlier quoted context omitted.
> You used to be able to (and still can, in some cases) take a low-end device and, if you'd won the chip lottery, "undo" the binning and have a perfectly functional high-end version. For the purposes you tested it, sure. Maybe some esoteric feature you don't use is broken. NVIDIA still can't sell it as the higher end SKU. The tests a chip maker runs to bin their chips are not the same tests you might run. I'm sure ch…
Disabling cores that have 100% passed QA is quite commonplace, especially for chips that have been on the market for over a year and thus are being built with yields as mature as they're going to get. Artificially restricting supply of high-end chips and increasing supply of mid-range chips by disabling fully functional cores is how chip makers preserve their pricing structure. Without doing this, market pressures wo…
Earlier quoted context omitted.
I am indeed well aware of how firmware validation works. Finding a vulnerability in firmware validation is however much more likely than reversing OTP for almost all varieties of OTP, even NVidia’s firmware validation which is generally regarded as pretty strong.
This reminds me of when Motorola introduced the first carrier-enforced, signature lock on Android with no "OEM Unlock" option and a bunch of ... questionably informed... people insisted it was by passable. (To my knowledge, it has not been bypassed, and jesus that was 15 years ago probably) Granted, it's Nvidia, and they've been featured in devices that were notoriously hackable, but also, it's not 2018 anymore. Need…
I think there might have been one or two OMX devices in this era with locked bootloaders that weren't bypassed due to a lack of research, but I actually find this example a bit amusing: early Qualcomm Motorola Android phones were touted as "unhackable" due to their use of fuses (Qualcomm even went on a marketing pitch calling them "Q-Fuses"), but were extremely quickly unlocked using trivial TrustZone supervisor vulnerabilities (iirc, there was an SMC that literally had a write-what-where primitive in it).
Earlier quoted context omitted.
> NVidia has software moat for specialized applications but not for AI, which is responsible for most of their sales now. Almost everyone in AI uses pytorch/jax/triton/flash attention and not CUDA directly And what does pytorch et al. use under the hood? cuBLAS and cuDNN, proprietary libraries written by NVidia. That is where most of the heavy lifting is done. If you think that replicating the functionality and perfo…
Did you read the last part? Pytorch uses drivers, and drivers exists for Google's TPU and Apple's M1 GPU as well and both works pretty well. I have tested both and it reaches similar MFU as Nvidia.
Earlier quoted context omitted.
Intel is by far the best out of the box experience under linux. I have 3 cards. I will get one of the new battlmage cards for my gaming pc. Edit: the only downside is that the hw h265 encoder is pretty bad. Av1 is fine though
What does a "pretty bad" h265 implementation look like? Buggy? Inefficient or what?
https://xcancel.com/realGeorgeHotz/status/1868356459542770087Imagine running this card at full speed, with fully unlocked potential. What would happen to new tiny power connectors? I am betting insta-fire.
It would just throttle like it already does.
Earlier quoted context omitted.
Nvidia wouldn't leave money on the table dropping the price of the 4090. There would just be more supply of 4090s at the same price. A card manufacturer selling them below MSRP would get immediately sanctioned by Nvidia.
Even a monopolist is constrained by supply and demand. If they could sell everything they make as a 4090 without trashing their margins, they would. The fact that 4080, 4070, 4060 lines exist means they can't.
They're cutting down 4090s into 4080s to fulfill a demand for a cheaper chip, while still supplying their premium option. Your fanciful world concept of things being sold for no/minimum margins is just that: fanciful.
Earlier quoted context omitted.
Did you read the last part? Pytorch uses drivers, and drivers exists for Google's TPU and Apple's M1 GPU as well and both works pretty well. I have tested both and it reaches similar MFU as Nvidia.
Maybe on a particular model/dataset but extremely unlikely in general. Again, like another commenter pointed out: if you truly believe it isn't that hard we would love to hire you at Meta ;)
I never claimed it was easy. I meant in my opinion it is in the order of 10s of millions dollars of investment, not a trillion dollar CUDA moat that people comment here.
Earlier quoted context omitted.
I consider those two very different problems. One is a supply problem, the other is a competition problem. Also, housing is a basic human right, whereas fast GPUs probably are not.
Different markets, similar semantics. Both are artificially supply restricted. Infact you can argue that something is really wrong in our governance if housing is human right and yet there are people profiteering from how unaffordable it has become. I am more appalled at how long it has taken for the big tech other than Google to standardized ML workload and not be bound by CUDA.
There is, however, a political barrier to increasing the housing supply.