Dr. Ulrich Kerzel

earned his PhD under Professor Dr Feindt at the US Fermi National Laboratory and at that time made a considerable contribution to core technology of NeuroBayes. After his PhD, he went to the University of Cambridge, where he was a Senior Research Fellow at Magdelene College. His research work focused on complex statistical analyses to understand the origin of matter and antimatter using data from the LHCb experiment at the Large Hadron Collider at CERN, the world’s biggest research institute for particle physics. He continued this work as a Research Fellow at CERN before he came to Blue Yonder as a Principal Data Scientist.
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Recent Posts

Building Robust AI Systems – Part II

IN General — 02 August, 2017

Building a robust Artificial Intelligence (AI) system is a challenging task: The previous blog post covered many of the more technical aspects from data handling and storage, dealing with data quality, deploying AI models and operational excellence. The technical setup to calculate billions of predictions that deliver optimal decisions needs to be…

Building Robust AI Systems – Part I

“What's the first thought that comes to mind when you think of Artificial Intelligence (AI)? Perhaps it’s a scene from a science fiction movie? Or – more realistically – AlphaGo, developed by the Google owned company DeepMind that learned to beat the best players at the complex game of Go? Perhaps you wonder about job security? MIT Technology Review

My Metric is Better Than Yours – Optimizing Business Decisions with AI

P. Sondergaard, Senior VP at Gartner famously said: “Algorithms are where the real value lies”. Artificial Intelligence (AI) and machine learning are reshaping entire industry sectors and verticals, creating the foundation of the next industrial revolution.

We Need to Talk About Your Data - Data Quality in the Age of AI

IN Machine Learning — 21 June, 2017

A short while ago I attended an industrial conference about production machines and engineering. This specific community is about five years behind retailers in understanding the impact that Artificial Intelligence (AI) and machine learning can make when integrated into their processes.

Building AI Applications – It’s More than Sticking AI in Front of It

Recent advances in machine learning and artificial intelligence (AI) — as well as technological improvements — have enabled a wide(r) range of businesses to integrate AI into their offering or integrate AI in their business processes.

Big Data vs. Artificial Intelligence

In recent years, almost all companies have jumped on the bandwagon to invest in Big Data. Each year, Matt Turck compiles a comprehensive list of Big Data companies that shows the relevant players on the market. Although such a list is ultimately incomplete, the recent versions have become so complex and detailed that they become hard to read, even…

How to Build an AI Strategy

A recent article by Harvard Business Review opens with “every serious technology company has now an Artificial Intelligence (AI) team in place.” The author raises an important point when claiming “Please don’t hire a Chief Artificial Intelligence Officer” by highlighting: “For them, AI is a competitive advantage, but not part of their core product.”…

The (new) Relationship between Humans and Artificial Intelligence

In the previous blog posts, we have explored how machine learning and artificial intelligence (AI) are at the heart of the next industrial revolution towards an algorithmic economy. We discussed how these technologies reshape businesses by automating up to 99% of all operational decisions.

How Artificial Intelligence Optimizes Decisions in the Presence of Uncertainty (Part 2)

In the previous post,we explored why people find thinking in probabilities difficult and how our world, despite our daily experiences telling us otherwise, is ultimately governed by probabilities. We then discussed how predictions for business decisions also need to be based on predicting probabilities and probability distributions, such as the one…

How Artificial Intelligence Optimizes Decisions in Uncertainty (Part 1)

IN Machine Learning — 29 March, 2017

Harvard Business Review recently published an article called “You Can’t Make Good Predictions Without Embracing Uncertainty” about the impact of uncertainty on making good decisions. While the article focused more on strategic decisions and how to incorporate uncertainties into the various influencing factors to come to a better decision, the…