That’s why I don’t get the AI marketing angle here at all. Any somewhat knowledgeable user will not use it for AI, and people with no clue who might fall for that kind of marketing usually don’t host their own local models.
And still AI marketing for underpowered devices is everywhere. Even the ESP32-S3 is marketed with AI features. You know, the microcontroller that tops out at 16MB RAM.
A lot of the AI marketing you see for various devices might be meant to appease and interest investors rather than potential users. Or the result of some marketing person or executive being convinced that absolutely every product needs to have an AI angle.
Even so, not every “AI” workload needs to be running the biggest local LLMs you can at the highest speeds possible.
Robotics often need low-power chips that can handle computer vision, for example, and that’s a use-case that Nvidia Jetson seems to focus on, to great success, with only 8-16GB RAM. SpacemiT’s engineers seem to be aiming at that market considering they put K3 on modules that are pin-compatible with Jetson NX carrier boards, and gave it dedicated cores for matrix and vector processing.
Regardless whether they manage to succeed at all for AI uses, K3 is designed for that. Maybe it makes more sense for that domestically in China, where they would want drop-in substitutes for less reliance on Nvidia imports.
For anyone else, it’s a RISC-V devboard that manages to be faster than any others despite the low power budget and having so much of the silicon wasted on AI stuff instead of more general-purpose cores. It’s not really designed for general dev use but the alternatives just happen to be so much worse for now.
That’s why I don’t get the AI marketing angle here at all. Any somewhat knowledgeable user will not use it for AI, and people with no clue who might fall for that kind of marketing usually don’t host their own local models.
And still AI marketing for underpowered devices is everywhere. Even the ESP32-S3 is marketed with AI features. You know, the microcontroller that tops out at 16MB RAM.
A lot of the AI marketing you see for various devices might be meant to appease and interest investors rather than potential users. Or the result of some marketing person or executive being convinced that absolutely every product needs to have an AI angle.
Even so, not every “AI” workload needs to be running the biggest local LLMs you can at the highest speeds possible.
Robotics often need low-power chips that can handle computer vision, for example, and that’s a use-case that Nvidia Jetson seems to focus on, to great success, with only 8-16GB RAM. SpacemiT’s engineers seem to be aiming at that market considering they put K3 on modules that are pin-compatible with Jetson NX carrier boards, and gave it dedicated cores for matrix and vector processing.
Regardless whether they manage to succeed at all for AI uses, K3 is designed for that. Maybe it makes more sense for that domestically in China, where they would want drop-in substitutes for less reliance on Nvidia imports.
For anyone else, it’s a RISC-V devboard that manages to be faster than any others despite the low power budget and having so much of the silicon wasted on AI stuff instead of more general-purpose cores. It’s not really designed for general dev use but the alternatives just happen to be so much worse for now.