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Interview: Targeting is Becoming a Data Science Problem

I recently caught up with Miguel Araujo, Director of Data Science at Semasio, to explore the question: with the impending loss of the cookie and changing nature of tracking user IDs, what does the future of targeting look like? Moving forward, advertisers must reference and merge a plethora of user attributes to make predictions about target audiences. As such, the traditional boundaries of targeting will begin to erode — becoming more of a data science problem.

Video Highlights: COVID Data Community Profile Report

With the COVID-19 data now open to the public, the need for better analysis and aggregation of that information in the U.S. has skyrocketed. If you’re interested in learning more about the current trends impacting the nation and the data that backs it up, check out the Datapalooza COVID Data Community Profile video presentation below, hosted by data journalism firm, CareSet.

Interview: Feature Stores for Machine Learning

In this interview, Mike Del Balso from Tecton and Willem Pienaar from Feast answer our questions and explain why feature stores are key to building machine learning models and deploying them to production to power new applications.

Interview: Andy Horng, Co-Founder and Head of AI, Cultivate

I recently caught up with Andy Horng, Co-Founder and Head of AI at Cultivate, to get a sense for the technology underlying the company’s AI-powered leadership development platform. NLP plays an important role, and as a result they’re using the RoBERTa language model for very good results.

Interview: Bernie Wu, Head of Business Development, MetalSoft

I recently caught up with Bernie Wu, Head of Business Development at MetalSoft, to address core industry trends like the evolution within companies where integrated technologies from Big Data to AI are driving entirely new ways for how businesses operate and how these leaps impacting their infrastructures and workload and where he sees the next generation of computing heading.

Interview: Global Technology Leader PNY

We recently caught up with our friends over at PNY to discuss a variety of topics affecting data scientists conducting work on big data problem domains including how “Big Data” is becoming increasingly accessible with big clusters with disk-based databases, small clusters with in-memory data, single systems with in-CPU-memory data, and single systems with in-GPU-memory data. Answering our inquiries were: Bojan Tunguz, Senior System Software Engineer, NVIDIA and Carl Flygare, NVIDIA Quadro Product Marketing Manager, PNY.

Interview: Justin Grossbard, Co-founder and CEO, Compare Forex Brokers

I recently caught up with Justin Grossbard, Co-founder and CEO of Compare Forex Brokers, to discuss his perspective for how big data has made a significant impact on financial markets, including Forex. He also assesses the success in incorporating machine learning and algorithmic trading techniques to expand upon execution and trading strategies in order to make more informed decisions.

Interview: Felix Dorrek, Ph.D.

I recently caught up with Felix Dorrek to discuss his research in the area of deep generative networks. The interview touches on the technology’s power, practical applications, importance to business in 2020, as well as generating synthetic data. Felix holds a Ph.D. in mathematics from the Vienna Technical University where he conducted research in the field of Convex Geometry.

Interview: Mike Hudy, Ph.D., Chief Science Officer at Modern Hire

I recently caught up with Mike Hudy, Ph.D., Chief Science Officer at Modern Hire, to discuss the use of AI in the hiring process. Hint: it includes a robust and specific code of ethics, implementation with a specific problem in mind, and lots of transparency.

Interview: Beerud Sheth, CEO of Gupshup

I recently caught up with Beerud Sheth, CEO of Gupshup, to discuss the state-of-the-art for conversational AI and chatbot technology. He also gives us an idea for future areas of evolution for AI chatbots.