This week’s guest are Rayid Ghani,  Distinguished Career Professor in the Machine Learning Department and the Heinz College of Information Systems and Public Policy at Carnegie Mellon University, and Andrew Burt, co-founder and Managing Partner of BNH.ai, a new law firm focused on AI compliance, risk mitigation, and related topics.  BNH is the first law firm run by lawyers and technologists focused on helping companies identify and mitigate risks associated with machine learning and AI.

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This week’s guest is Charles Martin, independent researcher and founder of Calculation Consulting, a boutique consultancy focused on data science and machine learning. Along with Michael Mahoney and Serena Peng, Charles is co-author of a recent Nature paper on new methods for evaluating and tuning deep learning models (“Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data”).

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This week our special correspondent and editor Jenn Webb organized a mini-panel composed of myself and Jesse Anderson, Managing Director at the Big Data Institute. Jesse is the author of a recent book entitled “Data Teams: A Unified Management Model for Successful Data-Focused Teams”. This conversation was focused on key areas in data engineering.

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This week our managing editor Jenn Webb and I speak with Sean Taylor, Data Science Manager at Lyft. Sean was previously a research scientist and manager at Facebook where he was instrumental in the creation and release of Prophet, a very popular open source library for time-series forecasting.

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This week’s guests are Steven Feng, Graduate Student and Ed  Hovy, Research Professor, both from the Language Technologies Institute of Carnegie Mellon University. We discussed their recent survey paper on Data Augmentation Approaches in NLP (GitHub), an active field of research on techniques for increasing the diversity of training examples without explicitly collecting new data. One key reason why such strategies are important is that augmented data can act as a regularizer to reduce overfitting when training models.

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This week’s guest is Brad King, CTO of Scality, a company that builds software-defined file and object storage systems for hybrid & multi-cloud settings. Storage and compute are the basic building blocks of (cloud) computing platforms and this episode highlights all the important considerations and recent innovations in storage technologies that data engineers, architects, and machine learning professionals need to know.

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In this episode, our managing editor Jenn Webb and I speak with Chris White, CTO of Prefect, a startup building tools to help companies build, monitor, and manage dataflows. Prefect originated from lessons Chris and his co-founder learned while they were at Capital One, where they were early users and contributors to related projects like Apache Airflow.

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This week’s guests are Reza Hosseini, Staff Software Engineer, and Albert Chen, Staff Data Scientist, both at Linkedin. Reza and Albert are part of the team behind the new open source library Greykite, a flexible and fast library for time-series forecasting.

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This week’s guest is Sercan Arik, Research Scientist at Google Cloud AI. Sercan and his collaborators recently published a paper on TabNet, a deep neural network architecture for tabular data. It uses sequential attention to select features, is explainable, and based on tests Sarjan and team have done spanning many domains, TabNet outperforms or is on par with other models (e.g., XGBoost) on classification and regression problems.

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This week’s guest is Connor Leahy, AI Researcher at Aleph Alpha GmbH, and founding member of EleutherAI, (pronnounced “ee-luther”) a collective of researchers and engineers building resources and models for researchers who work on natural language models. As NLP research becomes more computationally demanding and data intensive, there is a need for researchers to work together to develop tools and resources for the broader community. While relatively new, EleutherAI has already released a models and data that many researchers are benefitting from.

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