AI has been facing a PR problem. Too often AI has introduced itself as a misogynist, racist and sinister robot. Remember the Microsoft Twitter chatbot named Tay, who was learning to mimic online conversations, but then started to blur out the most offensive tweets? Think of tech companies creating elaborate

Design thinking continues to be all the rage amongst organizations of all kinds – from academia to startups, to agencies and consultancies, or large enterprises. The concept is popular today not because it’s new per se, but its approach to problem-solving fits well with the digital transformation that companies are

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