AI

Learn the architecture and data requirements needed to create your own Q&A engine with ChatGPT/LLMs. Link

Want to record voice memos, automatically transcribe and summarize them, and send the transcripts and summaries to Notion? Link

Large Language Models (LLMs) are incredibly powerful, yet they lack particular abilities that the “dumbest” computer programs can handle with ease. Logic, calculation, and search are examples of where computers typically excel, but LLMs struggle. Link

This notebook shows how to use Named Entity Recognition (NER) for hybrid metadata + vector search with Pinecone. Link

The electronic translation of images of typed, handwritten, or printed text into machine-encoded text is known as optical character recognition (OCR). The source could be a page that has been scanned, a photo of the page, or text that has been overlaid on an image. OCR is used to convert the text from these sources into machine-readable form. Link

Build and deploy LLM prompt APIs easily Link

Assemble, configure, and deploy autonomous AI Agents in your browser. Link

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses. Link

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The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. Link

This notebook showcases basic functionality related to Deep Lake. While Deep Lake can store embeddings, it is capable of storing any type of data. It is a fully fledged serverless data lake with version control, query engine and streaming dataloader to deep learning frameworks. Link

How to Use Deep Lake as a Vector Store in LangChain Link

DocsGPT is a cutting-edge open-source solution that streamlines the process of finding information in project documentation. With its integration of the powerful GPT models, developers can easily ask questions about a project and receive accurate answers. Link

For complicated data extraction you need a robust library. The Kor Library (created by Eugene Yurtsev) is an awesome tool just for this. Link

This is part 4 of our blog series on Generative AI. In the previous blog posts we explained why Ray is a sound platform for Generative AI, we showed how it can push the performance limits, and how you can use Ray for stable diffusion. Link