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Looking Ahead: The Future of Data Preparation for Generative AI

Data Science Blog

Sponsored Post Generative AI is a significant part of the technology landscape. The effectiveness of generative AI is linked to the data it uses. Similar to how a chef needs fresh ingredients to prepare a meal, generative AI needs well-prepared, clean data to produce outputs.

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Streamline RAG applications with intelligent metadata filtering using Amazon Bedrock

Flipboard

Retrieval Augmented Generation (RAG) has become a crucial technique for improving the accuracy and relevance of AI-generated responses. The effectiveness of RAG heavily depends on the quality of context provided to the large language model (LLM), which is typically retrieved from vector stores based on user queries.

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Empower your career – Discover the 10 essential skills to excel as a data scientist in 2023

Data Science Dojo

These skills include programming languages such as Python and R, statistics and probability, machine learning, data visualization, and data modeling. This includes sourcing, gathering, arranging, processing, and modeling data, as well as being able to analyze large volumes of structured or unstructured data.

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Deploying Gen AI in Production with NVIDIA NIM & MLRun

Iguazio

In less than three years, gen AI has become a staple technology in the business world. In November of 2022, OpenAI launched ChatGPT, with explosive growth of over 1 million users in just five days, galvanizing the widespread use of gen AI. We introduce their new solution model deployment - NVIDIA NIM.

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Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning Blog

Data governance – This tooling should be hosted in an isolated environment to centralize data governance functions such as setting up data access policies and governing data access for AI/ML use cases across your organization, lines of business, and teams.

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LLMOps demystified: Why it’s crucial and best practices for 2023

Data Science Dojo

Large Language Model Ops also known as LLMOps isn’t just a buzzword; it’s the cornerstone of unleashing LLM potential. From data management to model fine-tuning, LLMOps ensures efficiency, scalability, and risk mitigation. This includes tokenizing the data, removing stop words, and normalizing the text.

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Integrating AI into Asset Performance Management: It’s all about the data

IBM Journey to AI blog

Imagine a future where artificial intelligence (AI) seamlessly collaborates with existing supply chain solutions, redefining how organizations manage their assets. If you’re currently using traditional AI, advanced analytics, and intelligent automation, aren’t you already getting deep insights into asset performance?

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