“Innovation distinguishes between a leader and a follower”

Steve Jobs

ABOUT reseach

Why do we research?

Developing industrial AI solutions can be extremely difficult. Limited labels, high variance and constantly changing conditions pose great challenges. We are continuously expanding the limits of what is possible through cutting-edge research. For this purpose, we work with the world's leading academic institutions and companies in order to constantly develop and differentiate ourselves from the competition.

Research with us!

Meta Learning

Meta Learning is a subfield of machine learning and is often also referred to as “learning to learn”. In Meta Learning, machine learning algorithms are trained to make predictions based on metadata, such as network architecture and data set characteristics, instead of raw data. Therefore, Meta Learning allows for generalization of learning problems and may lead to drastically increased efficiency when substituting otherwise expensive experimentation procedures. At craftworks, we research and use Meta Learning techniques for exactly that.

AutoML

Applying machine learning to real world problems is not only time consuming and resource intensive, but also challenging. Automated Machine Learning (AutoML) takes care of large parts of the machine learning process, such as feature engineering, model selection and hyperparameter tuning in an autonomous fashion. This frees up time of data scientists and, additionally, enables people not familiar with machine learning to leverage its power. Therefore, a team of our engineers is working on developing cutting-edge AutoML software.

Representation Learning

The field of Representation Learning is engaged with the automated discovery of optimum representations of data given a specific learning problem. Learning the representation instead of spending hours or even days crafting it manually using traditional feature engineering techniques is time saving, often leads to significantly superior outcomes and frequently exposes previously unknown structures in the data. At craftworks, we use Representation Learning techniques to solve challenges ranging from Natural Language Processing to Computer Vision.

Reinforcement Learning

Reinforcement Learning is an iterative optimization approach that is motivated by the way humans learn: trial-and-error. In combination with deep learning, Reinforcement Learning is used to teach machines highly complex games, make robots learn arbitrary tasks, optimize control systems of power plants and many more. At craftworks, we recognize the wide area of application and the huge potential of Reinforcement Learning. Therefore, we develop novel approaches for solving multi-agent problems with incomplete information.

Our Partners

We partner with world-leading academic institutions and companies such as

Media

11 March 2019
Machine Learning & Optimization make logistics more efficient at RailCargo Austria [GER]

Die Struktur der transportierten Güter verändert sich. Gleichzeitig wirft das Physical Internet immer deutlichere Schatten – für die Güterbahnen sind das keine guten Nachrichten. Mit dem „Backbone“-Projekt wollen craftworks GmbH, WU Wien, Fraunhofer Austria und die Rail Cargo Group die Bahn fit für das Physical Internet machen.

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20 February 2019
Machine Learning, and Hydroelectric Power: Part One

Crate.io partnered with craftworks to build a proof-of-concept for Illwerke VKW that uses CrateDB and machine learning to process, analyze, and deliver actionable business intelligence from the massive amounts of data being collected.

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15 January 2019
Augmented Intelligence - A Human-Machine Marriage on the Way to Complete Intelligent Automation

Nowadays, everybody is talking about Artificial Intelligence (AI). It has become a major buzzword of the yet young 21st century. But are we ready for a largely automated world driven by Artificial Intelligence?

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Upcoming Events

Past Events

9-10 October 2019

Augmented Intelligence – A Human-Machine Marriage on the Way to Complete Intelligent Automation
Simon Stiebellehner, Head of AI, craftworks GmbH

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28-29 November 2019

Self-Supervised Learning – Towards Autonomously Learning Machines
Simon Stiebellehner, Head of AI, craftworks GmbH

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23 May 2019

Continuous Integration and Deployment for Machine Learning Applications
Simon Stiebellehner, Head of AI and Bernhard Redl, Data Engineer, craftworks GmbH

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22 May 2019

Deep Learning for Predictive Quality & Predictive Maintenance
Daniel Ressi, Data Scientist, craftworks GmbH

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6-7 May 2019

When Labelled Data is Scarce - Semi-Supervised Learning for Visual Inspection at Miba
Simon Stiebellehner, Head of AI, craftworks GmbH

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Blog

Team
Meet The Team: Interview with Ciaran Baselmans and Elisabeth Ettinger

We are very happy to welcome Ciaran and Elisabeth in our team, not only because of their excellent knowledge but also because of their great team spirit. Learn more...

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Team
Meet The Team: Interview with Daniela Merz

Daniela joined us in January as our Head of People. Many years of experience in the fields of HR and People made Daniela an expert in this area and...

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Team
Meet The Team: Interview with Markus Muth

Markus is our newest team member, who is supporting our team as data engineer in the topics such as Machine Learning and Big Data. We wish you a pleasant...

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