Amazing to see the energy of the OpenAI developer community. These models are starting to unlock real opportunity to build on top of them, whether for side projects, new products, or integrations into established services.
INNOVATION
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Groq’s AI Inference Performance Improvements and Future Direction
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With hundreds of times performance improvements on #inference for various #AI workloads, Groq has the technology solutions meeting the direction AI is headed. Hear David Holz's interview on the Stratechery podcast: https://
groq.link/stratechery -
Self-Driving Vehicles Still in Early Development Stages
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Experts tell me that self-driving vehicles are still in their infancy
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GPU Demand Surge Expected as Generative AI Applications Emerge
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What does 2023 have in store for AI? Our CEO Nick Elprin predicts GPU demand will soar as more deep learning apps emerge to cure disease. @NVIDIAAI
's Manuvir Das concurs that new generative AI realities will do the same. @VentureBeat has the full takes: https://
domino.buzz/3ZpKgco -
Stay Updated on Latest AI Innovations Weekly
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Join 1k+ AI enthusiasts to stay updated on the latest AI innovations happened in the last week with Unwind AI's weekly newsletter! It covers: Latest AI developments News from the Industry Tools of the Trade Hot Takes AI Meme of the Week https://
unwindai.substack.com/p/be-in-the-lo
op-with-all-things-ai
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LangChain Improves Documentation for Existing AI Functionality
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This functionality was already in LangChain (h/t @johnjnay for pushing to get it in in the first place) We've just improved documentation GREATLY around this capability, since it was a bit hidden s/o to people in the discord for making me realize we lacked documentation here
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LangChain Recursive Character Text Splitting Example Notebook
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Check out example notebook: https://
langchain.readthedocs.io/en/latest/modu
les/utils/combine_docs_examples/textsplitter.html#recursive-character-text-splitting
… Shout out to @krrish_dh and others in the discord for helping ideate + test! -
LangChain Question Answering Examples and LLM Applications
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Check out example notebooks: https://
langchain.readthedocs.io/en/latest/modu
les/chains/combine_docs_examples/question_answering.html
… Shout out to @johnjnay
, @BruceHammer
, and others in the discord for helping to ideate + test John's already started to use it in some more awesome work on llm-lobbyist: -
LangChain 0.0.59 Adds Map-Rerank Chain and Text Splitting
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New LangChain version makes it easier than ever to combine LLMs with your own data Brand new map-rerank chain
Recursive Text Splitter
Customize summarization and question answering `pip install langchain==0.0.59` -
Map-Rerank Chain for Enhanced Question Answering Systems
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Brand new map-rerank chain This chain can be used for question answering. It maps over documents, trying to both (a) answer a question, (b) assign a score to how good the answer is It then picks the answer with the highest score