This really ought to mention https://github.com/oobabooga/text-generation-webui, which was the first popular UI for LLaMA, and remains one for anyone who runs it on GPU. It is also where GPTQ 4-bit quantization was first enabled in a LLaMA-based chatbot; llama.cpp picked it up later.
The post mentions that they consider "Responsible Release" to be an unsolved hard problem internally. It's possible that they are culturally blind to agents.
They're basically saying that Pandora's Box, assuming it exists, has already been open. Even if OpenAI, Facebook AI Research and Google DeepMind all shut down tomorrow, research capable of producing agents will continue worldwide.
Feb 24, 2023: Meta launches LLaMA, a relatively small, open-source AI model.
March 3, 2023: LLaMA is leaked to the public, spurring rapid innovation.
March 12, 2023: Artem Andreenko runs LLaMA on a Raspberry Pi, inspiring minification efforts.
March 13, 2023: Stanford's Alpaca adds instruction tuning to LLaMA, enabling low-budget fine-tuning.
March 18, 2023: Georgi Gerganov's 4-bit quantization enables LLaMA to run on a MacBook CPU.
March 19, 2023: Vicuna, a 13B model, achieves "parity" with Bard at a $300 training cost.
March 25, 2023: Nomic introduces GPT4All, an ecosystem gathering models like Vicuna at a $100 training cost.
March 28, 2023: Cerebras trains an open-source GPT-3 architecture, making the community independent of LLaMA.
March 28, 2023: LLaMA-Adapter achieves SOTA multimodal ScienceQA with 1.2M learnable parameters.
April 3, 2023: Berkeley's Koala dialogue model rivals ChatGPT in user preference at a $100 training cost.
April 15, 2023: Open Assistant releases an open-source RLHF model and dataset, making alignment more accessible.