The Data Exchange with Ben Lorica

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange I speak with Kira Radinsky, Chairwoman & Chief Technology Officer at Diagnostic Robotics, a startup using AI to build a medical-grade triage and clinical-predictions platform. She is also a visiting Professor at Technion – Israel Institute of Technology.  Kira has extensive experience using data science and machine learning in a variety of settings, and she was one of the pioneers in using alternative data sources to augment forecasting models. Her earlier work includes models to predict social unrest as well as disease outbreaks.  The global pandemic has increased the need for experts in medical data mining, a field where Kira has made many significant contributions to.Download the 2020 NLP Survey Report and learn how companies are using and implementing natural language technologies.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange I speak with Max Pumperla, deep learning engineer at Pathmind and a contributor to many open source projects in data science and machine learning.  Max is speaking on applications of reinforcement learning to simulation problems at the upcoming Ray Summit, a free virtual conference scheduled for Sep 30th and Oct 1st.  Earlier this year I had Pathmind’s CEO Chris Nicholson on this podcast and he described how reinforcement learning might play a role in simulation problems. In this episode, Max provides an update and a technical description of how Pathmind uses reinforcement learning, RLLib, and Tune, to help users of AnyLogic, a widely used software for simulations in business applications.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange I speak with Weifeng Zhong, Senior Research Fellow at the Mercatus Center at George Mason University. He is the core maintainer of the open source Policy Change Index (PCI), a framework that uses machine learning and NLP to “process and read” large amounts of text to discern government priorities and policies. The initial PCI is focused on major policy shifts in China and uses NLP and machine learning to process and analyze  the People’s Daily.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange I speak with Ofer Razon, co-Founder & CEO at Superwise, a startup focused on building tools that help companies gain more visibility and control of machine learning models in production. Ofer and Superwise are part of a group in the early stage of building tools and best practices for scaling AI operations. The goal is to help multiple stakeholders build the necessary solutions to evaluate models, receive alerts and troubleshoot on time, validate, observe, and gather insights for more efficiency.  AI assurance will ultimately bring together different parts of an organization including business, data science and operational teams, legal and compliance, and privacy and security.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange I speak with Alan Nichol, co-founder and CTO of Rasa, the startup behind the popular open source framework for building conversational AI applications. I had Alan on as a guest in my old podcast, and that conversation was focused on components of Rasa and of chatbot applications. This time around we talked about the state of developer tools, as well as software engineering best practices for building conversational AI applications.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange, our special correspondent and editor Jenn Webb organized a mini-panel composed of myself and Paco Nathan, author, teacher, and founder of Derwen.ai, a boutique consulting firm specializing in Data, machine learning (ML), and AI.We began by discussing tools for scaling machine learning. Paco and I have been impressed with the growth in the number of libraries being built on top of Ray as well as the variety of use cases that are being addressed by Ray.We then discussed the upcoming Ray Summit, a FREE virtual conference featuring over 50 talks on machine learning, Python, serverless and cloud native technologies.We also looked back at the first eight months of this podcast (here’s an archive of previous episodes).  Both Paco and Jenn were instrumental in getting this podcast started, and I wanted to mark crossing the 30episode threshold with a short retrospective.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange I speak with Joel Grus, Principal Engineer at the Capital Group. He previously served as a Senior Research Engineer at the Allen Institute for AI, where he was a core engineer on AllenNLP, a PyTorch-based library for NLP research. Joel is also the author of one of the most widely read books in data science – Data Science from Scratch. Joel has a new book which I recommend highly:  Ten Essays on Fizz Buzz.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange I bring back Bruno Gonçalves, a data scientist working at the intersection of Data Science and Finance. Bruno was a guest on this podcast in April, when the COVID-19 cases were spiking in his home base in NYC. Prior to shifting over to data science, he spent several years as a researcher focused on mathematical models in Epidemiology – a field with a rich history dating as far back as the 1920s.  I wanted to bring him back to get an update on the mathematical models being used to model the global pandemic.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange I speak with Karthik Ramasamy (Senior Director Of Engineering at Splunk) and Arun Kejariwal (experienced engineering leader). The focus of our conversation was hiring technical talent such as software engineers, developers, data scientists, architects, etc.  The global pandemic has caused a global economic slowdown and massive layoffs across many industry sectors. But many companies are still hiring and companies are still competing for technical talent. In our bi-weekly newsletter, links pertaining to hiring and work culture have been very popular from the outset.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Lauren Kunze, CEO of Pandorabots, discusses the growth of Pandorabots as a leading chatbot development platform with collaborations with global brands. The podcast explores the versatility of chatbots, their role in combating loneliness, and the challenges of building good chatbots. It also covers integrating chatbots in companies, breakthroughs in natural language processing, and the rise of virtual chatbots and virtual talents.