This week, I’m really excited to welcome Tiezhen/Tom Wang from Huggingface on my show. You can find him here on X.

We talked about his background working at Google before he joined HF. Although, we did not get a chance to go really deep into running AI on robotics, but we did discuss the constraints facing AI on edge devices. Basically, 7B parameter model is close to the largest models we can reasonable run on a phone and small board type of device due to memory constraint. Although, Tom has been raving about OpenGLM’s open sourced 9B parameter AI agent that can reach your phone GUI and handle tasks.

We then talked about what you can do to fine tune models. For those out there that are interested, I would definitely recommend trying it with one of the 3B to 8B parameter Qwen models and use your own data. You can also try quantizing it (which may require data set depending on which NPU you are running off).

Open sourcing is very exciting and collaborative for many AI researchers. That’s why they are working so hard on it. I get that. And you can see with the number of projects and check ins on AI projects, many of them are just done by Chinese researchers. Chinese devs are not only rolling out open source models, but also involved in help building all the tools used in AI work.

Toward the end, we spoke more about the economics involved in AI right now. Why certain AI labs are racing to IPO.

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