Artificial Intelligence

Datacast Episode 103: Computational Economics, Statistical Arbitrage, and Adaptable Data Consolidation with Eric Daimler

Datacast Episode 103: Computational Economics, Statistical Arbitrage, and Adaptable Data Consolidation with Eric Daimler

Dr. Eric Daimler is an authority in Artificial Intelligence with over 20 years of experience in the field as an entrepreneur, executive, investor, technologist, and policy advisor. Eric has co-founded six technology companies that have done pioneering work in areas ranging from software systems to statistical arbitrage.

As a Presidential Innovation Fellow during the Obama Administration, Eric helped drive the agenda for U.S. leadership in research, commercialization, and public adoption of AI. He has also served as the Assistant Dean and an Assistant Professor of Software Engineering at Carnegie Mellon’s School of Computer Science. He specializes in public policy and economics, helped launch Carnegie Mellon’s Silicon Valley Campus, and founded its Entrepreneurial Management program. His academic research focuses on the intersection of Machine Learning, Computational Linguistics, and Network Science.

As a frequent keynote speaker, Eric has presented at venues including the engineering schools of MIT, Stanford, and Harvard. He studied at Stanford University, the University of Washington-Seattle, and Carnegie Mellon University, where he earned his Ph.D. in its School of Computer Science.

Datacast Episode 80: Creating The Sense of Sight with Alberto Rizzoli

Datacast Episode 80: Creating The Sense of Sight with Alberto Rizzoli

Alberto Rizzoli is co-Founder of V7, a platform for deep learning teams to manage training data workflows and create image recognition AI. V7 is used by AI-first companies and enterprises, including Honeywell, Merck, General Electrics, and MIT.

Alberto founded his first startup at age 19 and made the MakerFaire’s 20 under 20 list. In 2015, he began working on AI with Simon Edwardson while studying under Ray Kurzweil, leading to the creation of the first engine capable of running large deep neural networks on smartphone CPUs. Later, this project became Aipoly, a startup that helped the blind identify over 3 billion objects to date using their phones.

Alberto's work on AI granted him an award and personal audience by Italian President Sergio Mattarella and Italy’s Premio Gentile for Science and Innovation. V7's underlying technology won the CES Best of Innovation in 2017 and 2018.

What I Learned From Attending REWORK AI Applications Summit 2021

What I Learned From Attending REWORK AI Applications Summit 2021

Last month, I attended REWORK’s AI Applications Virtual Summit, which discovers machine learning tools and techniques to improve the financial, retail, and insurance experience. As a previous attendee of REWORK’s in-person summit, I have always enjoyed the unique mix of academia and industry, enabling attendees to meet with AI pioneers at the forefront of research and explore real-world case studies to discover the business value of AI.

In this long-form blog recap, I will dissect content from the talks that I found most useful from attending the summit. The post consists of 13 talks that are divided into 3 sections: (1) AI in Finance and RegTech, (2) AI in Retail and Marketing, and (3) AI in Insurance.

Datacast Episode 61: Meta Reinforcement Learning with Louis Kirsch

Datacast Episode 61: Meta Reinforcement Learning with Louis Kirsch

Louis Kirsch is a third-year Ph.D. student at the Swiss AI Lab IDSIA, advised by Prof. Jürgen Schmidhuber. He received his B.Sc. in IT-Systems-Engineering from Hasso-Plattner-Institute (1st rank) and his Master of Research in Computational Statistics and Machine Learning from University College London (1st rank). His research focuses on meta-learning algorithms for reinforcement learning, specifically meta-learning algorithms that are general-purpose, introduced by his work on MetaGenRL. Louis has organized the BeTR-RL workshop at ICLR 2020, was an invited speaker at Meta Learn NeurIPS 2020, and won several GPU compute awards for the Swiss national supercomputer Piz Daint.

Datacast Episode 45: Teaching Artificial Intelligence with Amita Kapoor

Datacast Episode 45: Teaching Artificial Intelligence with Amita Kapoor

Amita Kapoor is an Associate Professor in a college at the University of Delhi. She has 20+ years of teaching experience. She is the co-author of various best-selling books in the field of Artificial Intelligence and Deep Learning. A DAAD fellow, she has won many accolades, with the most recent Intel AI Spotlight award 2019 in Europe. As an active researcher, she has more than 50 publications in international journals and conferences. She is extremely passionate about using AI for the betterment of society and humanity in general.

Recommendation System Series Part 2: The 10 Categories of Deep Recommendation Systems That Academic Researchers Should Pay Attention To

Recommendation System Series Part 2: The 10 Categories of Deep Recommendation Systems That Academic Researchers Should Pay Attention To

In this post and those to follow, I will be walking through the creation and training of recommendation systems, as I am currently working on this topic for my Master Thesis. Part 2 provides a nice review of the ongoing research initiatives with regard to the strengths, weaknesses, and application scenarios of these models.

Recommendation System Series Part 1: An Executive Guide to Building Recommendation System

Recommendation System Series Part 1: An Executive Guide to Building Recommendation System

In this post and those to follow, I will be walking through the creation and training of recommendation systems, as I am currently working on this topic for Master Thesis. Part 1 provides a high-level overview of recommendation systems, how they are built, and how they can be used to improve businesses across industries.

A Friendly Introduction to Data-Driven Marketing for Business Leaders

A Friendly Introduction to Data-Driven Marketing for Business Leaders

Taking an algorithmic approach to attribution is just the beginning of driving change by moving toward a more detailed, data-driven approach in marketing.

Top 10 Practices to Operationalize Your Data Science Projects in the Real World

Top 10 Practices to Operationalize Your Data Science Projects in the Real World

I want to use this post to share the top 10 practices to deploy your machine learning models into production in the real world.