Gradient Flow #32: Data Cascades, Demand for Data Engineers, Exploiting ML models

Subscribe • Previous Issues This edition has 428 words which will take you about 2 minutes to read. “I would believe only in a god who could dance.” – Friedrich Nietzsche. Data Exchange podcast Machine Learning in Healthcare  I speak with Parisa Rashidi, Associate Professor at the Department of Biomedical Engineering and Director of the Intelligent HealthContinue reading “Gradient Flow #32: Data Cascades, Demand for Data Engineers, Exploiting ML models”

One Simple Chart: Data Engineering jobs in the U.S.

It’s been a few months since I looked at data on job postings. In my most recent post in Dec/2020 I focused on reinforcement learning (RL), which in terms of number of job postings, barely grew on a year-over-year basis. The good news is that it appears that employers are once again starting to postContinue reading “One Simple Chart: Data Engineering jobs in the U.S.”

Data Cascades: Why we need feedback channels throughout the machine learning lifecycle

A team from Google Research shares lessons learned from high-stakes domains. Data has been an undervalued component of AI development since the dawn of AI. We are now seeing the beginnings of a much-needed shift in how data is viewed. In a recent post, we described the growing interest in metadata management systems as aContinue reading “Data Cascades: Why we need feedback channels throughout the machine learning lifecycle”

Gradient Flow #31: AI in Healthcare, Data Quality, Understanding Neural Networks

Subscribe • Previous Issues This edition has 368 words which will take you about 2 minutes to read. “There’s a Fog of War, but there’s also a Fog of Peace.” – Eric Grosse Data Exchange podcast The Mathematics of Data Integration and Data Quality    Ryan Wisnesky is the CTO and co-founder of Conexus, a startup thatContinue reading “Gradient Flow #31: AI in Healthcare, Data Quality, Understanding Neural Networks”

2021 AI in Healthcare Survey Report

By Ben Lorica and Paco Nathan. Applications of AI in Healthcare ​pose a number of challenges and considerations which differ substantially from other business verticals. We conducted an industry survey specifically about AI in healthcare, to understand more about current trends and issues. A total of 373 respondents from 49 countries participated in the survey.Continue reading “2021 AI in Healthcare Survey Report”

Gradient Flow #30: Pricing Data Products, National AI Strategy, Elastic Computing

Subscribe • Previous Issues This edition has 560 words which will take you about 3 minutes to read. “We hoped for the best, but it turned out as usual.” – Viktor Chernomyrdin Data Exchange podcast Challenges, Opportunities, and Trends in EdTech   Stanford’s Sharon Zhou has been teaching very popular courses on GANs (generative adversarial networks) onContinue reading “Gradient Flow #30: Pricing Data Products, National AI Strategy, Elastic Computing”

Gradient Flow #29: Business at the Speed of AI, Information Security, Trading Bubbles

Subscribe • Previous Issues This edition has 344 words which will take you about 2 minutes to read. “But nothing is more opaque than absolute transparency.” – Margaret Atwood. Data Exchange podcast Towards Simple, Interpretable, and Trustworthy AI   I speak with Sheldon Fernandez, CEO at Darwin AI, and Alex Wong, Professor at the University of Waterloo,Continue reading “Gradient Flow #29: Business at the Speed of AI, Information Security, Trading Bubbles”

2021 Business at the Speed of AI Report

By Ben Lorica and Jenn Webb. In this report, we consult with industry leaders who have extensive experience implementing AI technologies. They share insights and clear, practical advice gathered from building and managing world-class AI teams delivering some of the most widely used AI products. The big takeaway is that, with efficient and effective approaches,Continue reading “2021 Business at the Speed of AI Report”

One Simple Chart: online learning platforms, a year into the pandemic

Download the 2020 NLP Survey Report and learn how companies are using and implementing natural language technologies. Last year I examined usage of a few online learning platforms and found that a month into the pandemic, many of them were growing rapidly. Now that we have data to compare pre and post pandemic usage, let’sContinue reading “One Simple Chart: online learning platforms, a year into the pandemic”