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A Quantitative Approach to Product Market Fit (Python Code)
Go Here to Read this Fast! A Quantitative Approach to Product Market Fit (Python Code)
Tag: AI
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Knowledge Bases for Amazon Bedrock now supports metadata filtering to improve retrieval accuracy
At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With Knowledge Bases for Amazon Bedrock, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data using a fully managed Retrieval Augmented Generation (RAG) model. For RAG-based applications, the accuracy of the generated responses from FMs […]Originally appeared here:
Knowledge Bases for Amazon Bedrock now supports metadata filtering to improve retrieval accuracy -
Build knowledge-powered conversational applications using LlamaIndex and Llama 2-Chat
Unlocking accurate and insightful answers from vast amounts of text is an exciting capability enabled by large language models (LLMs). When building LLM applications, it is often necessary to connect and query external data sources to provide relevant context to the model. One popular approach is using Retrieval Augmented Generation (RAG) to create Q&A systems […]Originally appeared here:
Build knowledge-powered conversational applications using LlamaIndex and Llama 2-Chat -
Use everyday language to search and retrieve data with Mixtral 8x7B on Amazon SageMaker JumpStart
With the widespread adoption of generative artificial intelligence (AI) solutions, organizations are trying to use these technologies to make their teams more productive. One exciting use case is enabling natural language interactions with relational databases. Rather than writing complex SQL queries, you can describe in plain language what data you want to retrieve or manipulate. […]Originally appeared here:
Use everyday language to search and retrieve data with Mixtral 8x7B on Amazon SageMaker JumpStart -
Boost inference performance for Mixtral and Llama 2 models with new Amazon SageMaker containers
In January 2024, Amazon SageMaker launched a new version (0.26.0) of Large Model Inference (LMI) Deep Learning Containers (DLCs). This version offers support for new models (including Mixture of Experts), performance and usability improvements across inference backends, as well as new generation details for increased control and prediction explainability (such as reason for generation completion […]Originally appeared here:
Boost inference performance for Mixtral and Llama 2 models with new Amazon SageMaker containers -
Building Local RAG Chatbots Without Coding Using LangFlow and Ollama
A Quick Way to Prototype RAG Applications Based on LangChain
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Building Local RAG Chatbots Without Coding Using LangFlow and OllamaGo Here to Read this Fast! Building Local RAG Chatbots Without Coding Using LangFlow and Ollama
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Python List Comprehension Is Not Just Syntactic Sugar
“Pythonic” is not a good reason. Why is the performance better? When not to use it?
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Python List Comprehension Is Not Just Syntactic SugarGo Here to Read this Fast! Python List Comprehension Is Not Just Syntactic Sugar
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5 Powerful Strategies To Make Sure AI Doesn’t Steal Your Job — A Spotify Data Scientist’s Survival…
Why I stopped freaking out that AI will replace me and what I do instead
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5 Powerful Strategies To Make Sure AI Doesn’t Steal Your Job — A Spotify Data Scientist’s Survival… -
How to Think About Using Your Company’s Information with GenAI
Assessing the options for GenAI information integration along with considerations for your specific company
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How to Think About Using Your Company’s Information with GenAIGo Here to Read this Fast! How to Think About Using Your Company’s Information with GenAI
