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Building the Responsible AI Pipeline

Dataiku

This is a guest post from David Ryan Polgar, founder of All Tech Is Human.

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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Working with large language models (LLMs) for enterprise use cases requires the implementation of quality and privacy considerations to drive responsible AI.

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5 things on our data and AI radar for 2021

O'Reilly on Data

MLOps attempts to bridge the gap between Machine Learning (ML) applications and the CI/CD pipelines that have become standard practice. The Time Is Now to Adopt Responsible Machine Learning. Responsible Machine Learning (ML) is a movement to make AI systems accountable for the results they produce.

Data Lake 289
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How to become an AI+ enterprise

IBM Big Data Hub

We have all been witnessing the transformative power of generative artificial intelligence (AI), with the promise to reshape all aspects of human society and commerce while companies simultaneously grapple with acute business imperatives. We refer to this transformation as becoming an AI+ enterprise.

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Bringing an AI Product to Market

O'Reilly on Data

The Core Responsibilities of the AI Product Manager. Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Product managers for AI must satisfy these same responsibilities, tuned for the AI lifecycle.

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In-stream anomaly detection with Amazon OpenSearch Ingestion and Amazon OpenSearch Serverless

AWS Big Data

In-stream anomaly detection offers real-time insights into data anomalies, enabling proactive response. If your use case requires the analysis of raw logs, you can streamline the process by bypassing the initial pipeline and focus directly on in-stream anomaly detection, indexing only the identified anomalies. Create a collection.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

FMs, as the name suggests, provide the foundation to build more specialized downstream applications, and are unique in their adaptability. This dynamic integration of streaming data enables generative AI applications to respond promptly to changing conditions, improving their adaptability and overall performance in various tasks.