The Data Exchange with Ben Lorica

Ben Lorica
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May 19, 2022 • 47min

Dataflow Automation

Jeremiah Lowin is co-founder and CEO of Prefect, the company behind the popular open source data workflow orchestration system with the same name. We discussed the major design changes in Prefect 2.0, their move towards treating “code as workflows”, data engineering challenges facing data and ML teams today, and implications of looming trends in machine learning and AI.Download the FREE Report: State of Workflow Orchestration → https://www.prefect.io/lp/gradientflow?utm_source=gradientflow&utm_medium=newsletterSubscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
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May 12, 2022 • 48min

Practical Machine Learning and Deep learning

Sebastian Raschka is lead author of a new book from Packt entitled “Machine Learning with PyTorch and Scikit-Learn”.  He is also an Assistant Professor of Statistics at the University of Wisconsin (Madison), and serves as the Lead AI Educator at Grid.ai.  Download a FREE copy of our recent NLP Industry Survey Results:  https://gradientflow.com/2021nlpsurvey/Subscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
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May 5, 2022 • 26min

Machine Learning for Optimization

This week’s guests are Ade Fajemisin (Postdoctoral Researcher) and Donato Maragno (PhD Student) of the University of Amsterdam. They were co-authors of a recent paper (“Optimization with Constraint Learning: A Framework and Survey”) that explores how machine learning can be used to learn constraints in optimization problems. Download the FREE Report: Trends in Data, Machine Learning, and AI → https://gradientflow.com/2022trendsreport?utm_source=DEpodcastSubscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
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Apr 28, 2022 • 27min

Efficient Scaling of Language Models

This week’s guests are Barret Zoph and Liam Fedus, research scientists at Google Brain. Our conversation centered around Large Language Models (LLM), specifically recent work by Barret, Liam, and their collaborators on efficient scaling of large language models.Download a FREE copy of our recent NLP Industry Survey Results:  https://gradientflow.com/2021nlpsurvey/Subscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
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Apr 21, 2022 • 31min

Data Science at Stitch Fix

Olivia Liao is Senior Director of Data Science at Stitch Fix, a company that uses data science and expert stylists to deliver personalization at scale. We discuss how they blend data science and domain expertise, how they tune recommendations in light of logistics and supply chain constraints, and how they incorporate new developments in large language models, multimodal  models and Responsible AI.Download a FREE copy of our recent NLP Industry Survey Results:  https://gradientflow.com/2021nlpsurvey/Subscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
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Apr 14, 2022 • 45min

The 2022 AI Index

Jack Clark is co-director of the AI Index Steering Committee. In this episode we discuss key findings of the fifth edition of the AI Index. The report uses multiple metrics (benchmarks, publications, patents, legislation, etc.) to track progress in AI (mainly deep learning) in key areas that include computer vision, speech recognition, and language models. Download the FREE Report: Trends in Data, Machine Learning, and AI → https://gradientflow.com/2022trendsreport?utm_source=DEpodcastSubscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
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Apr 7, 2022 • 46min

Why You Need A Time-Series Database

This week’s guests are Ajay Kulkarni (CEO) and Mike Freedman (CTO), co-founders of Timescale, the startup behind the popular relational database for time-series and analytics. Mike is also a Professor of Computer Science at Princeton University. Our conversation took place a few weeks after Timescale raised a massive funding round and achieved unicorn status. Download the FREE Report: 2022 Data Engineering Survey Report → https://gradientflow.com/2022desurvey/?utm_source=DEpodcastSubscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
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Mar 31, 2022 • 35min

Data Science at Shopify

This week’s guest is Wendy Foster, Director of Engineering & Data Science at Shopify. We discussed applications of data science within Shopify, how they organize their data teams, the lifecycle of a data science project within the company, and how they approach emerging challenges like Responsible AI, large language models, and multimodal models.Download the FREE Report: Trends in Data, Machine Learning, and AI → https://gradientflow.com/2022trendsreport?utm_source=DEpodcastSubscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
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Mar 24, 2022 • 31min

An AI Risk Management Framework

This week’s guests are Elham Tabassi of the National Institute of Standards and Technology (NIST) and Andrew Burt, Managing Partner of BNH.ai, the first law firm focused on AI compliance, risk mitigation, and related topics. We discuss the new NIST framework – “AI Risk Management Framework” – intended for voluntary use to manage risks in the design, development and use of AI products and systems. Download the FREE Report: Trends in Data, Machine Learning, and AI → https://gradientflow.com/2022trendsreport?utm_source=DEpodcastSubscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
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Mar 17, 2022 • 40min

An open source and end-to-end library for causal inference

This week’s guests are Amit Sharma (Principal Researcher) and Emre Kiciman (Senior Principal Researcher) of Microsoft Research. We talk about practical applications of causal inference, a set of tools and techniques that enable data teams to draw causal conclusions based on data.  Amit and Emre are part of the team behind DoWhy, a new open source library for estimating causal effects based on historical data alone, particularly useful when we cannot run an experiment because of time, expense, or ethical concerns.Download the FREE Report: Trends in Data, Machine Learning, and AI → https://gradientflow.com/2022trendsreport?utm_source=DEpodcastSubscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.

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