Nvidia and Salesforce double down on AI startup Cohere in $450M round
finance.yahoo.com
finance.yahoo.com
No further explanation of what Cohere might provide to it's customer of value, just the ability to generate text.
The compute is "wasted" to pick winners and secure the system, but it's not actually wasted, it can be made more efficient by actually using the compute to do something, but even if that was not the case, it pays back its value 100x.
Doesn't sound like a waste, does it?
I'd go further and argue mining Bitcoin isn't either, but I digress.
You want competition, you want vertical integration? Here it is. Compete.
there are google TPUs. Do they provide better pefrormance/dollar, or google also charges high margin, or Nvidia is doing some unique optimizations?
Is it because you don't need to buy many gpus to do your workload?
I could have written almost the same reasons for GPU workloads.
So now Nvidia is in the privileged position of having both highly-flexible GPGPU compute hardware, as well as a highly-advanced software layer to use it with. TPUs and NPUs are neat, but fundamentally they are neither of these things; they have an extremely limited processing pipeline exposed by a high-level library, and that's usually it. CUDA is comparatively flexible, to the point that it doesn't even rely on AI to sell it's product.
To me, hating on Nvidia feels like being mad that a well-bred horse with great odds beat out the jockey you were betting on. Why should we hate them, for their "monopoly" on features that Apple and Khronos gave up developing? Because they're blocking-out their competitors by... not having working MacOS drivers per Apple's request? This is the causal and obvious outcome of letting businesses commoditize specialized compute. This is what the industry wanted, and it's rich watching the customers protest like they were fooled into thinking everything was fine.
my understanding is that compilers can compile some straighforward JAX, TF, Pytorch programs to both Cuda and TPU, so they in direct competition in current hot topics (LLM, deep learning).
The math probably adds up in Google's favor with the TPUs, even if they end up being less efficient and slower per-unit than Nvidia hardware. They don't need to pay for the margins, and they can run them 24/7 for their intended purpose. The previous-generation TPUs can't be reused or resold for other purposes though, and if/when AI blows over as a trend you probably can't easily start mining crypto or doing HPC calculations like an Nvidia cluster would.
A ton of companies are dumping R&D into designing their own chips with seeming success. Nvidia will be in tough company quite soon, but for now demand greatly outstrips supply.
Pricing allows them to prioritize their customers, which seems reasonable.
Then why aren't people competing with Nvidia? Why is OpenCL on life support and unsupported on major operating systems? Why are we doing this song-and-dance routine refusing to adopt certain GPU APIs but embracing closed ones instead?
I'd like to believe that a tipping point will be reached, but if not now then when? People have talked about upending Nvidia's GPGPU compute empire for years, but besides application-specific replacements and proofs-of-concept, we don't have a real CUDA-killer. Apple does not ship one, Google does not ship one, Microsoft does not ship one and AMD doesn't either.
So... when? If we continue along the current path, I suspect Nvidia will continue to find markets where CUDA is demanded and OEMS will continue to chase them down with half-measure solutions. Unless OpenCL is revived or someone commits to a proprietary CUDA-like platform, I suspect we'll be spinning our wheels and digging ourselves deeper.
Because Nvidia invested 20 years into its API platform, and this advantage is slowly getting realized.
If the reason that OpenCL died is because Apple decided that they'd rather draw blood than work with the community, then yeah, this is a well-deserved failure on their part. Even Nvidia was willing to contribute to OpenCL; the only thing stopping us from living in a CUDA-agnostic world is the pointless and childish aggression between device manufacturers.
It feels less like we're slowly realizing things, and more like the persistent failure of Nvidia's competitors is forcing them back to the negotiations table. It's pathetic that American businesses are this willing to throw each other under the bus before they consider working together for the common good.
"the exclusive possession or control of the supply of or trade in a commodity or service."
There are other huge players: AMD and Intel.
Additionally Google and Amazon are producing their own AI hardware.
Now can you explain to me how Nvidia has a monopoly?
One of ways of wielding monopoly power is no longer being a price taker and being able to set prices at in practice to whatever you want.
Want a fence built for you? $3000 for 2 days work with 96 pieces of wood.
Want a basic android phone with 4 gb of memory, 128 gb of storage, a camera, speakers, touch screen, wifi, cell tower connection, GPS, battery, charger and cable? $60 on sale at Walmart for a Moto G Power Stylus edition. (My current phone and that's what I paid a few months ago)
It's because Microsoft/OpenAI and Meta are throwing multiple $10B's at NVIDIA. This is unsustainable and NVIDIA's stock will contract over 3-6 years unless Microsoft and Meta can translate hype into essential, profitable products which isn't a sure thing™.