Generative AI and Long-Term Memory for LLMs (OpenAI, Cohere, OS, Pinecone)
Автор: James Briggs
Загружено: 2023-01-19
Просмотров: 17456
Generative AI is what many expect to be the next big technology boom, and being what it is — AI — could have far-reaching implications far beyond what we'd expect.
One of the most thought-provoking use cases of generative AI belongs to Generative Question-Answering (GQA).
Now, the most straightforward GQA system requires nothing more than a user text query and a large language model (LLM).
We can test this out with OpenAI's GPT-3, Cohere, or open-source Hugging Face models.
However, sometimes LLMs need help. For this, we can use retrieval augmentation. When applied to LLMs can be thought of as a form of "long-term memory" for LLMs.
🌲 Pinecone article:
https://www.pinecone.io/learn/openai-...
📌 Notebook:
https://github.com/pinecone-io/exampl...
🤖 AI Dev Studio:
https://aurelio.ai
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00:00 What is generative AI
01:40 Generative question answering
04:06 Two options for helping LLMs
05:33 Long-term memory in LLMs
07:01 OP stack for retrieval augmented GQA
08:48 Testing a few examples
12:56 Final thoughts on Generative AI
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