The Tesla Dojo Chip Is Impressive, but There Are Some Major Technical Issues

Waymo have all the StreetView data - practically every road in the country, complete with lidar and high-precision GPS. All labelled in detail by recaptcha 'volunteers'

And lidar wouldn't be expensive if manufactured in automotive volumes. Certainly less, per vehicle, than Musk charges people for "full self driving" at the moment.

California allows autonomous vehicles to be tested on the road, so long as every disengagement is reported (along with total miles driven etc). Waymo is testing, reporting mileage and disengagements. So are Toyota, Nvidia, Mercedes, BMW, Cruise, Lyft and Apple.

Guess who's too shy to have driven a single autonomous mile in California, where faults have to be reported? That's right, Tesla!

Tesla might be able to make vision-only driving work. But Musk has been promising deadlines then failing to achieve them for years. They've put all their chips on 'no lidar' and they've had a bunch of problems that lidar could trivially solve - such as detecting a fire truck or concrete barrier right in front of the vehicle. So it's far from obvious to me that they've got a winning approach.

But Tesla isn't a cloud-provider company, nor is it a hardware company. None of the technical specs, assembly language, API, SDKs or whatnot have been released for Dojo.

The model of "someone will find this training computer useful" is... fine. Google TPUs, NVidia DGX, Intel Xe-HPC, AMD MI100, Cerebras wafer scale AI. These are computers that nominally are aiming for the market of selling computers / APIs / SDKs that will make training easier.

Its a pretty crowded field. Someone probably has struck gold (NVidia has a lead but... its still anyone's game IMO)

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If Tesla's goal is to compete against everyone else (or make a chip that's cost-competitive with everyone else), Tesla needs more volume than (allegedly) 3000 chips (quoted from the article: I dunno where they got this figure but... there's no way in hell 3k chips is cost-effective).

That's the name of the game: volume. The reason why NVidia leads is because NVidia sells the most GPUs right now, which means their R&D costs are applied to the broadest base, which means those company's engineering costs (aka: CUDA training) is spread across the widest number of programmers, leading to a self-reinforcing cycle of better hardware, lower costs, with a larger community of programmers to learn from.

Clearly a a shot across the bow for Cerebras and another excellent target for the GraphBLAS.

Dense numeric processing for image recognition is a key foundation for what Tesla is trying to do, but that tagging of the object is just the beginning of the process, what is the object going to do? What are its trajectories, what is the degree of belief that a unleashed dog vs a stationary baby carriage is going to jump out?

We are just beginning to scratch the surface of counterfactual and other belief propagation models which are hypersparse graph problems at their core. This kind of chip, and what Cerebras are working on, are the future platforms for the possibility of true machine reasoning.

As Hamming suggested in "Art of doing science and engineering", when you want to make something autonomous, you usually have to build a completely different device that solves the same problem, rather than automating the same device.

I wonder. For all the money thrown into self-driving cars research, could we have had an autonomous rail system by now? The technology for mostly-autonomous rail is well understood. Most of the financial cost is in infrastructure to support the system. Seems to me self-driving cars try to short-circuit that infrastructure build-up. They try to "automate the device" rather than "producing an automated system that solves the problem of moving people and goods".

Specifically, I wonder if, for the cost and time spent on CPU-and-engineer-driven research and development of autonomous cars, if we could have had nationwide autonomous rail rolled out by now.

> could we have had an autonomous rail system by now?

We already have autonomous rail systems. Its called positive train control and was fully implemented like a year or two ago (mandated in 2009, but you know how government works, lol) https://en.wikipedia.org/wiki/Positive_train_control

The train conductor has become more-and-more automated to remove the chance of human error. It works with a system of very reliable sensors that indicate where every train engine is on the rails.

Given the huge amount of cargo any particular train has, I don't think there's any intent on cutting the last two humans (the conductor + engineer) out of their job. Their salary costs are miniscule compared to the safety value they deliver, even if the job of driving a train has been almost entirely automated away by now.