AI Publications / Articles

( German only) appliedAI hat gemeinsam mit dem Förderschwerpunkt „Mittelstand-Digital“ des Bundesministerium für Wirtschaft und Klimaschutz einen kostenfreien Onlinekurs zur Einführung von KI speziell für kleine und mittlere Unternehmen entwickelt. Er bietet ein bisher einzigartiges, interaktives Paket aus Onlinekurs kombiniert mit einer Anwendungsfall-Bibliothek und einem Übungsheft für die direkte Verwendung im Unternehmen.

Today, Artificial Intelligence already plays a major role not only in improving the overall quality of customer service provision but also in the efficiency of how those services can be provided, thus also increasing the satisfaction of customer service employees. To help understand best practices today and identify technologies that will become relevant in the near future, we got together with our partners and experts from EnBW, Deutsche Telekom, Miele, Google, and IBM. Read this article to get more insights and key takeaways about AI in customer service!

For organizations, a big part of successfully building and deploying artificial intelligence at scale is establishing an AI unit. While it is mainly the role of the AI Center of Excellence to drive the execution, professionalization and scaling of AI, some organizations also have an AI Research Lab. Even though an AI CoE and an AI Research Lab are fundamentally different, many fail to distinguish between the two. This runs the risk of making the wrong decisions when it comes to staffing and building a team that can create an AI first culture. In this article we are looking at the main differences between an AI team and an AI Research lab in order to avoid costly mistakes.

Adversarial training has been shown to improve robustness of neural networks to certain classes of data perturbations. Despite constant progress, counterattacks appear immediately after each new method is proposed. This is because of a lack of bounds on the error that an attack can induce. In this TransferLab article we review a series of papers working towards certified error rates for networks using either special certification training objectives or arbitrary ones, including those employed for adversarial training.

Two billion people are cut off from any power grid. They live with makeshift generators or without electricity at all. This is a massive challenge, especially for health care in times of a global pandemic. Improving the situation and providing affordable and sustainable access to energy is critical. Read how Village Data Analytics together with the support of IBM are using satellite images to tackle this challenge.

A large number of initiated ML projects remain stuck at a PoC level and fail to reach the hurdle of going into production - studies report failure rates between 80% and 90%. What is the reason for this lack of impact in “traditional” enterprises and the high share of failed projects? One major reason that we observe with increasing frequency is the lack of an AI product mindset. In this article with Mindfuel we address the challenges faced in todays teams and explore the need for a dedicated discipline and role to make data-driven products successful. We call this role the data product manager.

In this TransferLab Blog we present an overview of the theory behind three popular and related algorithms for gradient based policy optimization: natural policy gradient descent, trust region policy optimization (TRPO) and proximal policy optimization (PPO). After reviewing some useful and well-established concepts from mathematical optimization theory, the algorithms can be introduced in a very unifying manner.

In this TransferLab Blog we review recent work analyzing in detail the type of error approximated by cross-validation and how standard error estimates produce optimistic confidence intervals, to then introduce a nested procedure providing tight confidence intervals around the type of error actually of interest in practice.

Within this article of the 'UnternehmerTUM Key Topic Series' you will get insights into the different modules of the course and get to know more about what you can expect when participating in the free online course 'Introduction to AI' in our trailer video!

Within this article of the 'UnternehmerTUM Key Topic Series' you will get insights into the different modules of the course and get to know more about how you and your company can profit from participating in the free online course 'Foundations of AI'!

In this TransferLab blog we discuss some current trends applying ML to the solution of differential equations, and the difficulties faced. We focus on a family of methods (PINNs / DGMs) and their advantages and shortcomings.

In the following interview, which is part of the UnternehmerTUM Key Topic Series, Philipp Hartmann, Director of AI Strategy at appliedAI, reveals how companies can identify realistic use cases, what mistakes companies make during implementation and how an effective implementation of AI can succeed.

Dr. Philipp Gerbert, Future Shaper at UnternehmerTUM and Director at appliedAI sat down to discuss how the Corona crisis is affecting Artificial Intelligence in Europe. Watch the interview here.

Corona is a black-swan event for AI and will put it to the test. We discuss some of the implications this development has for the future of the field.

A continuous series about AI strategy in small, digestible chunks. We cover a different topic every time we update this article.

How corporates and startups are setting the tone for the future and applying AI technology in an exemplary manner.