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Nvidia has a moat. Hardware is hard. No one really competes with them for general compute
by anon291 3mo ago
Nvidia has a moat. Hardware is hard. No one really competes with them for general compute
- therobots927 3mo agoOh great, good to know the shovel seller has the market cornered. Now back to the conversation, do any of the gold miners have a moat? Or is this a race to the bottom?
- FuriouslyAdrift 3mo agoAMD Instinct is their direct competitor for compute and they are better per dollar, better per watt, and out competing on raw performance. Only thing holding them back is fab capacity which nVidia keeps buying in bulk to keep them small.
- anon291 3mo agoHave you ever actually had anyone work with these chips? Developer ux on amd is terrible.
- lelanthran 3mo ago> Have you ever actually had anyone work with these chips? Developer ux on amd is terrible. Just how much of dev ux do you need? A foundational library, of course, but as the AI companies keep saying, their models can vibe-code what's needed for those chips anyway.
- FuriouslyAdrift 3mo agoYes. We have a quad MI300A server and run several inference models on it. For $107k it has saved us so much money on tokens already and it's a heck of a lot faster than cloud services.
- anon291 3mo agoDo you do research? Because if you don't, then you're not the target market for general purpose AI compute chips.
- FuriouslyAdrift 3mo agoWe use it for business analysis in a manufacturing environment (inputs from sensors, databases, external signals, etc.) We also use it as a programming tool to design software, ingest logs and do analysis, find patterns in data, etc. We bought it because we were burning through too much cash with Claude and Gemini.
- HDThoreaun 3mo agoAMD is held back by their interconnect and firmware disadvantage compared to nvidia. They’ve been trying really hard to create their own cuda, but rocM and HIP still aren’t very popular especially for research.
- pocksuppet 3mo agoAnd their repeated refusal to either implement CUDA or reimplement everyone's CUDA libraries on their own platform. They say that AMD never misses a chance to miss a chance.
- nradov 3mo agoI thought that Nvidia's moat was more in CUDA? Hardware is hard but we've already seen other companies like Google design neural processors with compute efficiency close to Nvidia.
- dsl 3mo agoGeneral compute is also the worst solution to the problem. Nvidia's entire business is dependent on Google not being able to make TPUs fast enough.
- foobiekr 3mo agoGoogle would have to start selling them (the real ones, complete with interconnect) to third parties. If google does that, though, Nvidia is done. Unlike AMD, Google can actually ship software. AMD has never shipped good software other than drivers (maybe) in the entire history of the company, including both ATi's history and true AMD. They have always relied on Intel to provide the software.
- foobiekr 3mo agoNvidia's moat is the IBM, Microsoft moat: I am about to spend $20M, if I buy anything other than Nvidia, and things go wrong, I am going to get blamed, and if things go right I will get no credit. This is why AMD is making no progress outside of very narrow cases and supercomputing.