openpilot VS tinygrad

Yes, but he spent several years in self-driving cars (https://comma.ai), which while interesting is also a space that a lot of players are in, so it's not the same as seeing him back to doing stuff that's a little more out there, especially as pertains to IP.

We have a product for sale: https://comma.ai

We raised $18.1M and have made $28M in lifetime revenue to date.

Where are you getting your narrative?

What about comma? https://comma.ai/ Seems like our old friend geohot built exactly what you want.

Positive HN discussion: https://news.ycombinator.com/item?id=36927971

The issue was that the front camera on the windshield couldn’t see under the hood. You misunderstand how easy it is to solve for depth and distance with AI without requiring stereo cameras. Read https://github.com/commaai/openpilot

Nice to have: I want to get a self-driving add-on that supports some cars better than others. Not a must but high up on my nice-to-have list.

EDIT: I probably should have added that I currently have the base model of the Kona the lowest model available, and I am looking for a similar thing in the ioniq 6, because my understanding is that it's fully compatible with the comma.ai device and therefore I am not planning on getting the better on board driving system, the Kona that I got unfortunately was not compatible with that device.

I wonder how bad this is compared to the competition. https://comma.ai allows you to add self-driving features to a large number of non-Tesla cars so, if we’re including physical firmware hacks as a threat vector, I’d bet tons of alternative cars (new enough Honda Odysseys, Toyota Siennas, etc: probably anything with adaptive cruise control and lane following) have the same sort of potential vulnerability.

Not sure, but from the first article from 4 years ago:

>Last month, we had 1,209 cars drive a little over 1,000,000 miles

Let's say they've had zero growth since then, so 48,000,000 conservatively?

Actually, from their website [1]:

>100+ million miles driven and 10k users.

[1]: https://comma.ai

Not sure if I completely understand what "Ryzen AI" does, but Tinygrad for example has some limited support for RDNA3[0]. It isn't quite there yet in matters of performance though, as you can read in the comments of that file.

There's also a small tutorial by AMD on how to use the WMMA intrinsic[1] using AMD's hipcc[2] compiler. Documentation is sparse kinda sparse, but the instruction set is not huge. The RDNA3 ISA guide[3] might also be helpful (and only a fraction of the pages are relevant.)

0. https://github.com/tinygrad/tinygrad/blob/master/extra/gemm/...

1. https://gpuopen.com/learn/wmma_on_rdna3/

2. https://github.com/ROCm/HIPCC

3. https://www.amd.com/content/dam/amd/en/documents/radeon-tech...

This post describes how I added automatic differentiation to Tensorken. Tensorken is my attempt to build a fully featured yet easy-to-understand and hackable implementation of a deep learning library in Rust. It takes inspiration from the likes of PyTorch, Tinygrad, and JAX.

what do you think about tinygrad? I think its a good example of growing and well written, (partially) well documented library with many close to reference implementations

The idea of model architecture making fast hardware design easier is what makes https://github.com/tinygrad/tinygrad so interesting.

🌟 Support on GitHub Website: https://tinygrad.org/

Before we begin, make sure you have TinyGrad and the required dependencies installed. You can find the installation instructions here.

Try to get something like tinygrad[1] running locally, that way you can tweak things a bit run it again and see how it performs. While doing this you'll pick up most of the concepts and get a feeling of how things work. Also, take a look at projects like llama.cpp[2], you don't have to fully understand what's going on here, tho.

You may need some intermediate knowledge of linear algebra and this thing called "data science" nowadays, which is pretty much knowing how to mangle data and visualize it.

Try creating a small model on your own, it doesn't have to be super fancy just make sure it does something you want it to do. And then ... you'll probably could go on your own then.

1: https://github.com/tinygrad/tinygrad

2: https://github.com/ggerganov/llama.cpp