Jan Bosch
Virtually any company that I work with is exploring its data sets and business processes to identify opportunities for productivity improvements, higher accuracy or lower cost. The constant question that these companies struggle with is how can artificial intelligence, and specifically machine learning (ML) and deep learning (DL), support existing processes and ways of working. … Read more
In earlier posts (such as here), I have discussed different approaches to software development and one of the key models for this is the HoliDev model where we combine requirements driven development, outcome-driven development (e.g. A/B testing) and AI-driven development. In the figure below, the HoliDev model is shown graphically. It may easily seem that … Read more
As I’m spending an increasing amount of time in the AI field with a variety of companies, I’ve noticed an interesting misconception in the ML/DL space. Many have a tendency to focus on data sets, experimenting with different models using a specific set of data and, finally, deploying a model in a specific context. This … Read more
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
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
During the last week I was reflecting on the change processes ongoing in several of the companies that I work with. Although I don’t want to generalize too aggressively, it seems to me that most companies are on a similar journey. Starting from a situation where the key value proposition of the company was expressed … Read more
Over the last weeks, I have been on the road a lot for various engagements with customers as well as for our research activities. In virtually every meeting, the whole area of artificial intelligence and especially machine and deep learning come up as a discussion topic. This is great as I think the whole AI/ML/DL … Read more
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
In last week’s article, I outlined the first phase of adopting machine & deep learning (ML/DL) which is concerned with experimentation and prototyping. 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 next step is the careful use of … Read more
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
