3 ms·

Here's hoping someone with access puts it on bittorrent.

1letterunixname 4y ago
DLP, overall architecture, and many more aspects put the kibosh on that. The career risk isn't worth it especially when tech is deployed client- and network-side to detect just such exfil attempts. The average of network, security, and client management staff tend to be PEs (SREs) who can code, some have PhDs, and are the cream of what was previously organized as "corporate IT" world. So I fail to see any incentive to throw away their career and reputation by giving away IP for $0. There's a metric s*ton of optimized hardware to generate models. And I have my doubts if Sama at OpenAI, even with 10 gigabucks from Microsoft, can sustain growth, organizational culture, and long-term investment at the scale others are bringing online with less trouble and more experience. The future interaction will AI models will most likely be through an API because the models themselves are becoming too large to fit even on the most extreme DIY NAS solutions. TL;DR: it's not happening.
- generalizations 4y ago
  > The future interaction will AI models will most likely be through an API because the models themselves are becoming too large to fit even on the most extreme DIY NAS solutions. And yet I spent last night running GPT-J-6B on my desktop CPU at 2 tokens / sec. People are finally starting to optimize these models, and there's a ton of optimization to go. We'll definitely be running these locally in the next few years. This model especially looks like an ideal candidate for CPU optimization, given the pairity with GPT3, and that it's within spitting distance of the size of models like GPT-J-6B.
- Hyption 4y ago
  There are plenty low paid students or working students or admins in-between.
- imranq 4y ago
  You can make small LLMs more performant than large ones like GPT-3 by fine-tuning on specific tasks or providing them tools to offload precise calculations: e.g. Toolformer: https://arxiv.org/abs/2302.04761 https://arxiv.org/abs/2302.04761 which uses APIs and functions to improve GPT-J beyond GPT-3 for various tasks
  - 1letterunixname 4y ago
    How dare you bring knowledge in here! Some people at work would be offended if they couldn't buy their A100 or DGX toys, or had to scale back their custom ASIC and systems R&D.
cma 4y ago
Once it is out there it can be rehosted on the clear net since model weights can't be copyrighted (unless they intentionally over train on some copyrighted snippets they own maybe).
lsb 4y ago
BitTorrent links: https://github.com/facebookresearch/llama/pull/73/files https://github.com/facebookresearch/llama/pull/73/files

DLP, overall architecture, and many more aspects put the kibosh on that. The career risk isn't worth it especially when tech is deployed client- and network-side to detect just such exfil attempts. The average of network, security, and client management staff tend to be PEs (SREs) who can code, some have PhDs, and are the cream of what was previously organized as "corporate IT" world. So I fail to see any incentive to throw away their career and reputation by giving away IP for $0. There's a metric s*ton of optimized hardware to generate models. And I have my doubts if Sama at OpenAI, even with 10 gigabucks from Microsoft, can sustain growth, organizational culture, and long-term investment at the scale others are bringing online with less trouble and more experience. The future interaction will AI models will most likely be through an API because the models themselves are becoming too large to fit even on the most extreme DIY NAS solutions. TL;DR: it's not happening.

generalizations 4y ago
> The future interaction will AI models will most likely be through an API because the models themselves are becoming too large to fit even on the most extreme DIY NAS solutions. And yet I spent last night running GPT-J-6B on my desktop CPU at 2 tokens / sec. People are finally starting to optimize these models, and there's a ton of optimization to go. We'll definitely be running these locally in the next few years. This model especially looks like an ideal candidate for CPU optimization, given the pairity with GPT3, and that it's within spitting distance of the size of models like GPT-J-6B.
Hyption 4y ago
There are plenty low paid students or working students or admins in-between.
imranq 4y ago
You can make small LLMs more performant than large ones like GPT-3 by fine-tuning on specific tasks or providing them tools to offload precise calculations: e.g. Toolformer: https://arxiv.org/abs/2302.04761 https://arxiv.org/abs/2302.04761 which uses APIs and functions to improve GPT-J beyond GPT-3 for various tasks
- 1letterunixname 4y ago
  How dare you bring knowledge in here! Some people at work would be offended if they couldn't buy their A100 or DGX toys, or had to scale back their custom ASIC and systems R&D.

cma 4y ago

Once it is out there it can be rehosted on the clear net since model weights can't be copyrighted (unless they intentionally over train on some copyrighted snippets they own maybe).

lsb 4y ago

BitTorrent links: https://github.com/facebookresearch/llama/pull/73/files https://github.com/facebookresearch/llama/pull/73/files