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Are there use-cases for LLMs assisting in developing this software? Basically, I'm wondering if LLMs for developing a GPU-API exist and how can they can acceler

by dpflan 3y ago

Are there use-cases for LLMs assisting in developing this software? Basically, I'm wondering if LLMs for developing a GPU-API exist and how can they can accelerate development such that this "moat" becomes more of a river that other can join?

seanhunter 3y ago
I'm struggling to see how that helps given the current problem they have. What they have is several extremely half-assed implementations of somewhat different APIs that are basically the same and abysmal documentation. Pointing an LLM at it would make yet another half-assed implemetation of yet another different API, where what documentation it had would be convincingly wrong a bunch of the time. What they need is: 1) Make one API [1] that builds out of the box, works really well and gets the best out of their hardware right away. Bonus points if its not a total pig to use. 2) Take the thing that they built for 1 and make a straightforward python binding for it that works for tensorflow and pytorch.[2] 3) Have a beer on me. Seriously I would buy them one. Ideally there's an optional step 0 which is to stop making all kinds of press statements saying they are taking this seriously and paying sloppy journalists to say they are catching up in the race against nvidia if they can't actually get their act together to do steps 1 and 2. [1] In c, c++ or rust so it's easy to embed in python and other languages etc [2] By work here I mean the definition of done is a normal person can do `pip install tensorflow` and it will actually use an amd gpu with hardware accelleration right away. Not some bullshit where you have to jump through a bunch of hoops and apply a whole lot of custom patches and it kinda sorta sometimes works but actually mostly just either falls back to CPU or crashes half the time
- dpflan 3y ago
  It does seem like they need a reset, and given that need for a reset, a new-starting point: how do they move quickly? I was thinking that LLM could assist in creating a coherent approach, helping in creating code, documentation, etc (i.e. dog-food'ing their 'product') -- what I would think could make this development more rapid.

by dpflan 3y ago

seanhunter 3y ago

I'm struggling to see how that helps given the current problem they have. What they have is several extremely half-assed implementations of somewhat different APIs that are basically the same and abysmal documentation. Pointing an LLM at it would make yet another half-assed implemetation of yet another different API, where what documentation it had would be convincingly wrong a bunch of the time. What they need is: 1) Make one API [1] that builds out of the box, works really well and gets the best out of their hardware right away. Bonus points if its not a total pig to use. 2) Take the thing that they built for 1 and make a straightforward python binding for it that works for tensorflow and pytorch.[2] 3) Have a beer on me. Seriously I would buy them one. Ideally there's an optional step 0 which is to stop making all kinds of press statements saying they are taking this seriously and paying sloppy journalists to say they are catching up in the race against nvidia if they can't actually get their act together to do steps 1 and 2. [1] In c, c++ or rust so it's easy to embed in python and other languages etc [2] By work here I mean the definition of done is a normal person can do `pip install tensorflow` and it will actually use an amd gpu with hardware accelleration right away. Not some bullshit where you have to jump through a bunch of hoops and apply a whole lot of custom patches and it kinda sorta sometimes works but actually mostly just either falls back to CPU or crashes half the time

dpflan 3y ago
It does seem like they need a reset, and given that need for a reset, a new-starting point: how do they move quickly? I was thinking that LLM could assist in creating a coherent approach, helping in creating code, documentation, etc (i.e. dog-food'ing their 'product') -- what I would think could make this development more rapid.