This is a huge milestone. It's also part of a much larger journey. In my work on developing Vello, an advanced 2D renderer, I have come to believe WebGPU is a game changer. We're going to have reasonably modern infrastructure that runs everywhere: web, Windows, mac, Linux, ChromeOS, iOS, and Android. You're going to see textbooks(*), tutorials, benchmark suites, tons of sample code and projects to learn from.<p>WebGPU 1.0 is a lowest common denominator product. As 'FL33TW00D points out, matrix multiplication performance is much lower than you'd hope from native. However, it is <i>possible</i> to run machine learning workloads, and getting that performance back is merely an engineering challenge. A few extensions are needed, in particular cooperative matrix multiply (also known as tensor cores, WMMA, or simd_matrix). That in turn depends on subgroups, which have some complex portability concerns[1].<p>Bindless is another thing everybody wants. The wgpu team is working on a native extension[2], which will inform web standardization as well. I am confident this will happen.<p>The future looks bright. If you are learning GPU, I now highly recommend WebGPU, as it lets you learn modern techniques (including compute), and those skills will transfer to native APIs including Vulkan, Metal, and D3D12.<p>Disclosure: I work at Google and have been involved in WebGPU development, but on a different team and as one who has been quite critical of aspects of WebGPU.<p>(*): If you're writing a serious, high quality textbook on compute with WebGPU, then I will collaborate on a chapter on prefix sums / scan.<p>[1]: <a href="https://github.com/gpuweb/gpuweb/issues/3950">https://github.com/gpuweb/gpuweb/issues/3950</a><p>[2]: <a href="https://docs.rs/wgpu/latest/wgpu/struct.Features.html#associatedconstant.TEXTURE_BINDING_ARRAY" rel="nofollow">https://docs.rs/wgpu/latest/wgpu/struct.Features.html#associ...</a>*