LLaMA2 isn't “Open Source” – and why it doesn't matter

• ultralytics

  27 22,624 9.8 Python

  NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

  

It's not just in the LLM space; even for 'older' models, companies have aggressively embraced this approach. For example: YOLOv3 has been appropriated by a company called Ultralytics, which has subsequently released the 'YOLOv5' and 'YOLOv8' "updates": https://github.com/ultralytics/ultralytics

There is no marked increase in model effectiveness in these 'new' versions, but even if you just use the 'YOLOv8' Pytorch weights (and no part of their Python toolchain, which might have some improvements), these will somehow try to download files from Ultralytics servers. Possibly for a good reason, but most likely to, let's say, "pull an Oracle."

Serious AI researchers won't go anywhere near this stuff, but the number of students-slash-potential-interns with "but it's on GitHub!" expectations that I had to reject lately due to "nope, we're not paying these guys for their Enterprise license just to check out your project" is rather disheartening...

• llama

  184 53,053 8.1 Python

  Inference code for Llama models

  

This is fundamentally incorrect, and disheartening that it's the top comment.

You cannot use a model's output to train another model, it leads to complete gibberish (termed "model collapse").[0] And the Llama 2 license does allow users to train derivative models.[1]

[0]: https://arxiv.org/abs/2305.17493v2

[1]: https://github.com/facebookresearch/llama/blob/main/LICENSE

• InfluxDB

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  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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