Ya that was my first thought too. Since they're targeting AI, they'll probably start with the streaming multiprocessors (SMs) and tensor processing units (TPUs)

Ya that was my first thought too. Since they're targeting AI, they'll probably start with the streaming multiprocessors (SMs) and tensor processing units (TPUs): https://stackoverflow.com/questions/32226993/understanding-streaming-multiprocessors-sm-and-streaming-processors-sp https://stackoverflow.com/questions/32226993/understanding-s... https://primo.ai/index.php?title=Processing_Units_-_CPU,_GPU,_APU,_TPU,_VPU,_FPGA,_QPU https://primo.ai/index.php?title=Processing_Units_-_CPU,_GPU... I take issue with this though because the DSP/SIMD approach that GPUs and TPUs take is a subset of SMP/MIMD (symmetric multiprocessing and multiple instruction multiple data). Where this matters is that today's neural networks are built on matrix operations, which is a narrow niche within computer science. A more general approach which would allow for faster evolution of the 20 or so other algorithms in AI would be to use compute clusters to explore genetic algorithms, simulated annealing and all the rest in playgrounds limited only by the developer's imagination. Loosely that would look like a desktop computer with perhaps 1000 or more cores appearing as a single CPU, that could be programmed in a language of choice like Erlang, Go, Julia, MATLAB, C/C++, etc (optionally using containerization tools like Docker). Or like having something akin to AWS EC2 locally. I believe that this divergence in computing approaches is why Moore's Law ended around 2007 with emphasis switching to low cost and low power mobile and embedded systems. It's also why my heart fell out of programming and I stopped pursuing endlessly more photorealistic game engines that result in everyone making the same game over and over again. If someone out there won the internet lottery and wants to invest in something truly disruptive, some low hanging fruit might be a highly scaled multicore RISC-V processor (as you mentioned) with 100-1000 cores running over 1 GHz using under 100 watts for under $1000. Targeting 10,000 to 100,000 cores by 2030 and 1 million cores shortly thereafter. That's the level of performance we should be expecting from companies like Intel, had Moore's Law continued. And it shows just how far expectations have fallen, with today's personal computers running little faster than those of 2010 for typical (non-GPU) workflows, tragically at the same price of $1000-3000. I also wish that Imec would start with a consumer-level superconducting processor for under $1000, but unfortunately today's socioeconomic reality of widening wealth inequality doesn't support that. But it's easy enough to make liquid nitrogen from the air with a liquid nitrogen generator (looks like they start around $4000, that could/should be disrupted to $400 or less). Unfortunately their Josephson junctions still need liquid helium at 4k it looks like. Probably some company overseas will figure out a 77k liquid nitrogen version and bypass IP law, as these things tend to go lately.