Quantify yourself

Having spent quite a bit of this summer thinking about machine learning and artificial intelligence, it seems to me that there’s a very important transformation ongoing from a focus on the qualitative to a focus on the quantitative. The moment we start with A/B testing, deploying multi-armed bandits or training machine learning models, the very … Read more

AI: the fabric of computing

During the summer, I spent a week at a summer school on deep learning (DL). There were several reasons to attend, but one was to simply learn more about this trending topic. In many ways, it was a wonderful, though humbling, experience as the field is progressing at a rate that’s simply phenomenal. There are … Read more

Towards Operational AI

In the latest two articles, I outlined the two phases of adopting machine & deep learning (ML/DL). In the figure below, we show the steps that companies typically evolve through while adopting AI, ML and DL solutions. As shown in the figure, the third step, the subject of this article, is where ML/DL components are … Read more

Machine & Deep Learning: Experimentation Stage

This week I got the opportunity to speak at the initiative seminar organized by the Chalmers AI Research center (CHAIR). The key message in my presentation was that working with artificial intelligence (AI) and specifically machine & deep learning (ML/DL) constitutes a major software engineering challenge that is severely underestimated by companies that start to … Read more