Although there are lots of similarities across Software Development  and Data Science , they also have three main differences: processes, tooling and behavior. Find out. In my previous  article, I  talked about model governance and holistic model management. I received great response, along with some questions about the differences between

I’ll never forget my “aha” moment with bias in AI. I was working at IBM as the product owner for Watson Visual Recognition. We knew that the API wasn’t the best in class at returning “accurate” tags for images, and we needed to improve it. I was nervous about the

Breaking down the workforce options for AI developers to structure raw data for machine learning. Here is a look. While it may seem like artificial intelligence (AI) has hit the big time, a lot of work needs to be done before its potential really come to life. In our modern

The era of everything-as-a-service (XaaS) has provided both an opportunity and a challenge for companies across industries. The XaaS model, a subscription-based solution that makes cloud-based applications available on demand unlike the traditional license-based platforms of the past, delivers several noteworthy advantages over its predecessors. Between cost reductions and easier

Digital transformation dominates most CIO priority lists pertaining to questions such as:  How will digital transformation affect IT infrastructure? Will technology live on-premise or in the cloud? Depending on where that data lives, an organization requires different skill sets. If you’re building these resources in-house, then you need an infrastructure

How to implement an anonymous data collection scheme that allows the manufacturer to anonymously collect data from its end devices without knowing exactly which device it came from? Yes, this is one of the challenges for the second Blockchain Hackathon (part of LongHash Cryptocon Vol2) in Berlin on May 18-19