Trends in AI: Towards Learning Systems That Require Less Annotation
There’s a lot of hype surrounding AI. Unfortunately, a lot of it is hyperbolic warnings about how we’ll lose our humanity and the machines will be smarter than we are. Just about every field and institution is preparing for an AI revolution. There’s even a brand new Minister of... Read more
Adversarial Attacks on Deep Neural Networks
Our deep neural networks are powerful machines, but what we don’t understand can hurt us. As sophisticated as they are, they’re highly vulnerable to small attacks that can radically change their outputs. As we go deeper into the capabilities of our networks, we must examine how these networks really... Read more
Why The New Era of Big Data Requires Innovative Privacy Initiatives
“Data can either be useful or perfectly anonymous but never both.” – Paul Ohm Privacy and data collection go together like peanut butter and jelly, but in the world of big data, it’s becoming increasingly difficult to work with anonymous data without crossing a privacy line. So what’s a... Read more
Known Unknowns: Designing Uncertainty Into the AI-Powered System
Uncertainty may be a fearful state for many people, but for data scientists and developers training the next wave of AI, uncertainty may be a good thing. Designing uncertainty directly into the system could help AI focus on what experts need to leverage state of the art AI and... Read more
Forging a Career Path in Data Science From Beginner to Expert – ODSC Career Expo
Data Science, data engineering, and machine learning jobs continue to rank as some of the most sought after and highly paid jobs on the planet, according to Thinknum. However, finding the right job is more important than ever. This may be a lucrative field, but many quickly find that... Read more
Watch: Applied Finance – The Third Culture with Steve Lawrence
What can financial analysts learn from computer scientists about data science? And can computer scientists change their approach to appeal to finance professionals? Data scientists typically argue about the relative merits of the statistical and algorithmic approaches to data mining (Leo Breiman – The Two Cultures). Anyone who has... Read more
Three Challenges for Open Data Science
There are three types of lies: lies, damned lies, and ‘big data.’ That’s the message Amazon machine learning director Neil Lawrence began his ODSC Europe 2016 lecture with before laying out the three largest challenges for open data science and our data-centered society. As Lawrence sees it, those challenges... Read more
Peter Wang on the State of the Union for Data Science in 2018
These are exciting times for data science and business. In his talk at ODSC East 2018, CTO and Co-founder at Anaconda Peter Wang presented a ‘state of the union’ on how data technologies are transforming business practices. Peter first described his work for Anaconda – the most popular Python... Read more