Resources /

The AI Productivity Challenge

  • Björn Brinne
    Björn BrinneHead of Data Science

An introductory paper on how to drive productivity in the areas of machine learning and deep learning.

Artificial intelligence, in particular the subfields of machine learning and deep learning, have shown remarkable progress in recent times. There is a general consensus that over time every business will need to start using AI if they are to be competitive and successful. AI is not something for the future nor something only for the large technology titans but rather a technology that is increasingly entering the mainstream.

The data scientist has emerged as an essential resource

Björn Brinne, Head of Data Science at Peltarion

Why read this?

This is an introductory paper on how to drive productivity in the areas of machine learning and deep learning. The paper highlights some of the key barriers to getting good outcomes in these projects and then outlines some potential functions or capabilities organizations should consider as they look at technologies to help support their AI programs.

Read and download The AI Productivity Challenge.

  • Björn Brinne

    Björn Brinne

    Head of Data Science

    Björn Brinne has over a decade of experience working in data science at companies such as Truecaller, King and Electronic Arts before joining Peltarion. He holds a Ph.D. in theoretical physics from Stockholm University and has contributed to many research papers across a range of academic fields, including computer science, string theory and computational biology.