Building a platform for generative AI applications https://
huyenchip.com/2024/07/25/gen
ai-platform.html
… After studying how companies deploy generative AI applications, I noticed many similarities in their platforms. This post outlines these common components, what they do, and implementation
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Building Generative AI Application Platforms: Common Components
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Cohere Rerank 3 Language Models Now Available on Azure
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Leverage Cohere’s enterprise-grade language models today, Rerank 3 English: https://
azuremarketplace.microsoft.com/en-us/marketpl
ace/apps/cohere.cohere-rerank-3-english-offer?tab=Overview
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Rerank 3 Multilingual: https://
azuremarketplace.microsoft.com/en-us/marketpl
ace/apps/cohere.cohere-rerank-3-multilingual?tab=Overview
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Rerank 3 Foundation Model Now Available on Azure AI Studio
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Rerank 3 is now available on Microsoft @Azure AI Studio. We’re excited for users to leverage our cutting-edge foundation model for improved search precision through Azure’s robust infrastructure.
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Cohere Rerank Boosts Atom AI Search Accuracy by 20%
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Customers like @atomicworkhq are using Rerank to power their digital assistant, Atom AI, and saw over 20% improved search accuracy and relevance, providing faster, more precise answers to complex IT support queries. https://
cohere.com/customer-stori
es/atomicwork
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Praising Innovative AI Tool Excellence and Future Development
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Delighted to showcase such a worthy tool! Keep up the excellent work; we can't wait to see what is next from you all!
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Seven Ways Marketers Leverage Generative AI for Brand Engagement
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In this video, I explore seven innovative ways #marketers can leverage generative #AI to enhance brand #engagement and streamline processes. Discover how #GenerativeAI tools like #ChatGPT and #Google #Gemini can transform your #marketing #strategy.
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Chat with Your Data: Summarizing PDF Files in Apps
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Step 4: Chat with your data Finally, once the data has been ingested into the app, chat with your data. Here we are asking it to summarize the pdf file.
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Setting Up RAG System with Clarifai and Llama 3.1
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Step 2: Import the RAG class and set up the RAG system by passing your Clarifai App URL and the Llama 3.1 8B instruct model URL from the community. Create a Clarifai app and get your App URL. Here is the model URL: https://
clarifai.com/meta/Llama-3/m
odels/llama-3_1-8b-instruct
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Upload Data to Clarifai App Vector Database
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Step 3: Upload the data Once you upload the data, it will embed and index the data into your Clarifai app. Clarifai Apps acts as your vector database.
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Install Clarifai SDK Llama-index and Configure Personal Access Token
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Step 1: Install the Clarifai Python SDK, Llama-index, and set your Clarifai Personal Access Token as an environment variable. Sign up for the platform, and you can access the PAT here: https://
clarifai.com/settings/secur
ity
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