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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This week’s guests are leading researchers in recommendation systems: Paolo Cremonesi is Professor of Computer Science and Maurizio Ferrari Dacrema is a Postdoc at Politecnico di Milano, where they are both part of the RecSys research group. Paolo is also the Reproducibility co-chair for the upcoming RecSys Conference.

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This week’s guest is Hyun Kim, co-founder and CEO of Superb AI, a startup building tools to help companies manage data across the entire machine learning application lifecycle. This includes tools to label, store, and monitor data assets that power all computer vision applications. We also discussed emerging trends in machine learning and AI including synthetic data, reinforcement learning, and self-supervised learning.

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This week’s guest is Nicolas (Nic) Hohn, Chief Data Scientist, McKinsey/QuantumBlack Australia. Nic led a team of data scientists charged with helping America’s Cup winning team,  Emirates Team New Zealand, test new designs for hydrofoils – important sailing boat components that could be modified based on rules set forth by race organizers. More precisely the QuantumBlack team used Ray RLlib to design an AI agent that could learn to sail the boat for a given design at an optimal speed, and this AI agent proved crucial during the design process.

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In this episode of the Data Exchange I speak with 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 Travis Addair, he previously led the team at Uber that was responsible for building Uber’s deep learning infrastructure. Travis is deeply involved with two popular open source projects related to deep learning:

• He is maintainer of Horovod, a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
• And Travis is a co-maintainer of Ludwig, a toolbox that allows users to train and test deep learning models without the need to write code.

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In this episode of the Data Exchange, I speak with Yonatan Geifman, CEO and co-founder of Deci, as well as with Ran El-Yaniv, Chief Scientist and co-founder of Deci and Professor of Computer Science at Technion. 

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