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0 pointsdragontamer4y ago0 comments

There are plenty of other, innovative companies specializing on FP16 matrix multiplication systolic arrays.

For one, Google TPU. Another: Cerebras wafer scale AI. AMD MI100. Etc etc.

Even if they screwed the pooch with Nvidia, there are plenty of competitors in this space.

Now Tesla has to build its own software stack for large scale distributed learning, which might be harder than the chip design.

Is Tesla really the kind of company that wants to carry the expensive loadstone of training and inference software + hardware?

It's not like PyTorch is gonna run on this thing unless they create a fork. And a huge advantage of things like NVidia are NVlink / NVswitch. Both hardware, and software, that efficiently distributes data at 600GBps across your GPU clusters.

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5 comments · 2 top-level

panick214y ago· 2 in thread

> Is Tesla really the kind of company that wants to carry the expensive loadstone of training and inference software + hardware?

Yes. They are very much that kind of company. Tesla has been pushing vertical integration and that is very much Elon Musk whole approach for most of his companies.

Doing your own battery manufacturing and even supply chain is considerably more expensive and complex compared to making a chip and getting some software developers.

dragontamerOP4y ago

Battery manufacturing isn't vertically integrated at all. They use Panasonic cells and are dependent on Panasonic's half of the gigafactory.

panick214y ago

Yes, so far they are doing that. In fact they use a mix of Panasonic, CATL and LG.

However they are working on having their own battery and battery factory design. They are even working on their own cathode manufacturing plants.

They have a very large 'pilot' plant in California to test a completely redesigned battery manufacturing system. They are actively building additionally battery factories in Austin and Berlin and have a equipment on order for these factories. For the Battery factory in Berlin they have received funding from the European Commission for this.

Tesla will not be fully vertically integrated but they will provide a large parts of their own cells and likely a increasing share over the coming years.

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londons_explore4y ago· 1 in thread

I see only two reasons to do it yourself with multiple very capable third parties out there which pretty much exactly match the requirements:

1) You hope to make it available to external customers and turn it into a scale business. Your internal use is just the first customer. You need your own hardware so you can keep costs down at large scales.

2). Someone's pet project was to design their own ML ASIC and they thought it would look very good on their CV, and the CEO took the bait.

Hopefully it's the first case!

mschuster914y ago

There's a third and fourth reason: the need to keep the secret sauce secret and keep others from replicating it, and that existing vendors aren't flexible enough to offer what they want.

For all that Elon Musk values openness in some areas (e.g. putting Hyperloop into public domain), he prefers keeping stuff as vertically integrated as possible for everything he deems to be essential to the business, for maximum control.

Tesla has stakes in lithium mining operations, SpaceX has their own metallurgy team and IIRC also a foundry, and while they are using a Liebherr crane at the moment they are thinking about building their own. And for that, it makes sense - SpaceX is only one of Liebherr's customers while SpaceX depends on a crane that fits their needs - so either they get Liebherr to customize their crane or they build their own.

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