1. smallpond: https://github.com/deepseek-ai/smallpond
2. 3fs: https://github.com/deepseek-ai/3FS
3. deepep: https://github.com/deepseek-ai/DeepEP
not a hater, just know that theres a lot of hurdles to adoption even if something if open source - for example not being an industry standard. i dont know a ton about this space - what is the main alternative?
Not saying this is bad, but it's just interesting to see after being in the industry for 8 years.
2. The distributed technology is powerful but complex, and most user don't need most of what it offers. Let's build a simple solution.
3. GOTO 1
- Created comparable LLM performance for a fraction of the cost of OpenAI using more off-the-shelf hardware.
- Seem to be open sourcing lots of distributed stuff.
My question is, are those two things related? Did distributed computing allow the AI model somehow? If so how? Or is it not that simple?
This is true for DeepSeek as well as for others. There are a few companies giving insights or open-sourcing their approaches, such as Databricks/Mosaic and, well, DeepSeek. The latter also did some particularly clever stuff, but if you look into details so did Mosaic.
OpenAI and Anthropic likely have distributed tools of even larger sophistication. They are just not open source.
A lot of blogs praise these new systems, but don't really provide any numbers :/
