I can't wait to see more affordable RISC-V microcontrollers on the market!<p>The Kendryte K210 looked very cool, especially with its SIMD-ish "machine learning coprocessor", but it felt like they had rushed the hardware to market without investing in scrutable documentation or software support, last time I checked.<p>The GD32V series looks fantastic, since the current crop of GD32VF103 chips appear to be API-compatible with the venerable STM32F103 workhorse. But I haven't been able to find a source of the raw chips yet, it seems like you can only get them on development boards at the moment.<p>And there are always softcores running on FPGAs, but those sort of highlight how many permutations of "RISC-V" exist. I hope that we don't end up with too many inscrutable compiler flags to juggle as more of these chips become available.
Seems like he has been changing companies quite a bit recently. Is this typical for the VP level? Does anyone know how his tenure at Google was viewed by others?
Really loved listening to his recent podcast with Lex Fridman[1].<p>[1] <a href="https://m.youtube.com/watch?v=yCd3CzGSte8" rel="nofollow">https://m.youtube.com/watch?v=yCd3CzGSte8</a>
I wonder if this will curtail the effort to implement TensorFlow in Swift, turtles all the way down?<p>That would be a shame. Python ecosystem with TensorFlow, PyTorch, mxnet, etc. has been good for rapid progress but I think we need something better to break out of just using deep learning. This needs a hackable infrastructure. I personally don't have the skill to hack the C++ TensorFlow core.<p>I think a new ecosystem based on Swift, TensorFlow, and future tools and platforms makes some good sense.<p>An alternative would be a similar hackable infrastructure based around the Julia language, which is also very good.
The corporate press release, which doesn't say much either, is <a href="https://www.businesswire.com/news/home/20200127005141/en/Google-Tesla-Engineer-Chris-Lattner-Lead-SiFive" rel="nofollow">https://www.businesswire.com/news/home/20200127005141/en/Goo...</a><p>(via <a href="https://news.ycombinator.com/item?id=22160226">https://news.ycombinator.com/item?id=22160226</a>)
I was super tempted to buy the new learning development board they just released (which is actually tough to get in the US) but I actually haven't been able to figure out the benefits of the new SiFive processors compared to other traditional arms boards like a M0. Anyone here familiar with their boards that can provide some insight?
Is there some connection to CarbonFive[0], the consultancy, or did they just.... um... completely duplicate their logo by accident or something?<p>[0]<a href="https://www.carbonfive.com/" rel="nofollow">https://www.carbonfive.com/</a>
FYI, more comments over on this post: <a href="https://news.ycombinator.com/item?id=22160226" rel="nofollow">https://news.ycombinator.com/item?id=22160226</a>
I have hard time connecting "machine learning" with what RISC-V is about.<p>Above all, the original plan for RISC-V was to make a barebone MCU ISA first, and everything else second.<p>This was largely to ARM being very militant with terms on RTL access for M* series cores for commercial use.<p>If you throw enough extension, and workarounds even on top of 8051, you should be able to make a CPU grade core with it. But you being able to do it, doesn't mean you should.
Reminds me of the Silicon Valley TV show sketch where the only goal of every single startup is "to make the world a better place".<p><a href="https://www.youtube.com/watch?v=J-GVd_HLlps" rel="nofollow">https://www.youtube.com/watch?v=J-GVd_HLlps</a>