DiscoverThe Data Exchange with Ben LoricaData Science and AI in Context
Data Science and AI in Context

Data Science and AI in Context

Update: 2023-01-26
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Description

Peter Norvig (of Google and Stanford) and Alfred Spector (of MIT) are part of the team of authors behind the must-read book Data Science in Context: Foundations, Challenges, Opportunities. We discussed their recent book and tool a deep dive into their Data Science Analysis Rubric, and we also talked about a trending topics in AI including looming regulations, synthetic data, and Large Language and Foundation Models.

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Detailed show notes can be found on The Data Exchange web site.

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In Channel
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Exhaustion of High-Quality Data Could Slow Down AI Progress in Coming Decades

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Generating high-fidelity and privacy-preserving synthetic data

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How technology is disrupting the venture capital industry

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Running Machine Learning Workloads On Any Cloud

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2023 Trends in Data Engineering and Infrastructure

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Preparing for the Implementation of the EU AI Act and Other AI Regulations

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The Open Source Stack Unleashing a Game-Changing AI Hardware Shift

The Open Source Stack Unleashing a Game-Changing AI Hardware Shift

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Data Science and AI in Context

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Evaluating Language Models

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2023 Opportunities and Trends: Data, Machine Learning, and AI

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Exploring DALL·E 2

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Data Science at Shopify and Stitch Fix

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What’s Next for Machine Learning in Time Series

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Efficient Methods for Natural Language Processing

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Responsible and Trustworthy AI

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Building a premier industrial AI research and product group

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An open source, production grade vector search engine

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Data Science and AI in Context

Data Science and AI in Context

Ben Lorica