Engineering challenges in building operational AI and how to avoid them – Daniel Skantze, Peltarion

There is a lot of hype around AI nowadays. Apart from the big players like Google, Facebook and Apple, AI remains complicated for most companies. This is true because the challenges in using AI lie not only in understanding the algorithms. It is also about the software engineering challenges of rapidly processing massive amounts of data, running training jobs on specialized hardware, orchestrating parallel jobs, visualizing data and output from models and much more. But on an even bigger picture, it also requires a different organisational mindset and workflow when moving the problem statement to the data. This presentation will go into some of these challenges, outline how we have approached them at Peltarion.