What can you build with LLM chatbots powered by retrieval-augmented generation (RAG)? The Chat endpoint makes it easy to build RAG-powered chatbots. In this LLM University chapter, learn the foundations of LLM chatbots and the Chat endpoint. https://
txt.cohere.com/exploring-chat
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@cohere
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Building RAG-Powered Chatbots with LLM Chat Endpoints
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Hackathon Knowledge Assistant: Build with Coral, Chat and RAG
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Come build a knowledge assistant! Our next hackathon is all about Coral. Learn how it was made with Chat and RAG, build new applications, and win cool prizes. Thanks to our hackathon partners @langchain @weaviate_io and @lablabai
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Building Chatbots with Chat RAG and Memory
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We’re excited to host our next Maker Spotlight live demo session today! Join Cohere community champions Arjun Patel and @Coffee_and_NLP in conversation with AI engineer @an1z8 as he walks us through leveraging Chat + RAG to build chatbot applications with memory and context.
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Coral Adds PDF Web Grounding Conversation Capabilities
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We’ve added new grounding capabilities to Coral Showcase. You can now have conversations with uploaded PDFs and specified web domains, complete with source citation.
— Cohere (@cohere) 17 octobre 2023
Try these capabilities today at https://t.co/mGGBYJql2Q pic.twitter.com/GypJpDYaObWe’ve added new grounding capabilities to Coral Showcase. You can now have conversations with uploaded PDFs and specified web domains, complete with source citation. Try these capabilities today at http://
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RAG Capabilities Enable Intelligent Application Features
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Developers can use these capabilities to build intelligent features into their applications. To learn more, visit our documentation on RAG:
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Learning Text Embeddings with Cohere and LLMU
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You can learn more about text embeddings from @SerranoAcademy with LLMU: https://
docs.cohere.com/docs/text-embe
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Understanding Text Embeddings: How NLP Captures Language Meaning
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How does natural language processing (NLP) capture the meaning of language so well? Here’s AI scientist and LLM University lead Luis Serrano with a simple explanation of text embeddings. Enjoy. pic.twitter.com/mANM5wkqbs
— Cohere (@cohere) 13 octobre 2023How does natural language processing (NLP) capture the meaning of language so well? Here’s AI scientist and LLM University lead Luis Serrano with a simple explanation of text embeddings. Enjoy.
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Comprehensive LLM U Curriculum: Master Large Language Model Development
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Our comprehensive curriculum aims to give you a foundation in large language model technology, equipping you with the skills needed to develop your own applications and deploy within your business. The complete 7 modules of LLM U can be found here: https://
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Cohere Platform Module 7: Foundation Models and API Overview
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In Module 7: The Cohere Platform you'll get a comprehensive overview of our platform. We cover our serving framework, the types of foundation models available, our API endpoints, and the range of applications which can be built.
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Module 6: Mastering Prompt Engineering Techniques
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In Module 6: Prompt Engineering you'll learn the best practical techniques for constructing an effective prompt to help you get the intended output from a generative model. This module also covers the basics on validating & evaluating outputs.