We believe that sharing what we learn about AI is our obligation. The AI-Hub is our public repository of the knowledge artifacts that we build for our partners. Here you can find relevant articles, materials, landscapes and much more. As a partner, you have access to even more, including our workshop materials, tools, etc.
German AI-Startup Landscape: 2022
Published on April 11, 2022
Cross-validation: what does it estimate?
Published on June 11, 2021
Erfolgreich mit Künstlicher Intelligenz - Kostenfreier Onlinekurs "KI-Kompetenz für Ihr KMU" (German only)
by Stephanie Eschmann on July 11, 2022
( 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.
How to leverage AI to support the European Green Deal
by Stephanie Eschmann on June 30, 2022
This whitepaper gives an overview of the many ways in which AI can help the fight against climate change and describes the requirements that are needed to use the potential of AI even better. It is an important contribution for anyone who wants to understand the key mechanisms and levers for AI to tackle climate change.
Culture, Change, Communication
by Samantha Warren on June 7, 2022
This report aims to draw attention to this often-neglected “soft” side of applying AI successfully. It highlights what is special about AI – after all, change is not a new concept – and offers concrete measures on how to address the issues of culture, communication, and change in the context of an AI transformation. In doing so, we rely on our experience from successful approaches to foster AI applications in larger enterprises.
AI in Customer Service
by Samantha Warren on June 3, 2022
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!
Value Assessment of AI Products and Applications
by Samantha Warren on May 2, 2022
The advent of artificial intelligence presents companies with both unique opportunities and – as practitioners’ experience has shown – unique challenges. In this whitepaper and the accompanying comprehensive valuation tool, appliedAI, in cooperation with its technology and industry partners, offers a lifeline to those who are confronted with one particularly vexing challenge of AI: Namely, how to best quantify and measure the value contribution of AI initiatives during the course of a company’s journey to AI maturity.
The Difference Between an AI Team and an AI Research Lab
by Samantha Warren on January 24, 2022
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.
The Enterprise Guide to Machine Learning
by Samantha Warren on January 20, 2022
Built together with our partners, this guide is an attempt to share the experience of ML practitioners in the enterprise sector. Here the contributors discuss and elaborate on the challenges companies face in the real world. Maintained by the appliedAI Initiative, the guide reflects a commitment from the partners of appliedAI to share their experiences and best practices when moving beyond the PoC.
Veränderung der Arbeitswelt durch KI – Das Beispiel Stiftung Pfennigparade
by Stephanie Eschmann on January 20, 2022
KI ist eine Schlüsseltechnologie, die neue Geschäftsbereiche eröffnet und mittels Optimierung von Prozessen die Effizienz durch gezielteren und damit nachhaltigeren Einsatz von Ressourcen steigern kann. Doch sie verändert auch bestehende Geschäftsfelder und fordert Unternehmen zum Umdenken, um den Anschluss an die KI-Transformation nicht zu verpassen. Auch die Stiftung Pfennigparade beschäftigt sich mit der Frage, wie sich ihre Geschäftsfelder durch KI ändern und welche neuen Chancen diese Veränderung mit sich bringt.
Certified error rates for neural networks
by Samantha Warren on January 13, 2022
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.
Enterprise Guide for Make-or-Buy Decisions
by Samantha Warren on November 25, 2021
This report is intended to provide helpful guidance for make-or-buy decisions with AI. Download the paper to view a structure of the make-or-buy questions, a framework with decision criteria for solving the make-or-buy question and a selection of the optimal partner and potential pitfalls of different partner types.
Life-saving Data from Satellite Images
by Stephanie Eschmann on October 20, 2021
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.
Artificial Intelligence for Boards - Gearing up for the Future of Business
by Stephanie Eschmann on October 18, 2021
Download our latest paper to learn what every board member needs to know about AI. Discover how AI affects various individual board roles, how these learnings can be readily be applied to boards and the 8 top priorities for Boards in the AI Journey.
Data Product Management - The Missing Link To Create Value From AI
by Samantha Warren on August 25, 2021
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.
Natural, Trust Region and Proximal Policy Optimization
by Samantha Warren on August 10, 2021
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.
Cross-validation: what does it estimate?
by Samantha Warren on June 11, 2021
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.
New online course "Introduction to AI" on KI-Campus
by Stephanie Eschmann on May 19, 2021
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!
appliedAI German Startup Pitch Lunch Series
by Samantha Warren on April 23, 2021
The appliedAI pitch lunches are a series of events that are giving voice to some of the most interesting companies featured on the 2021 German AI Startup Landscape. The objective of these events is to connect the most promising startups in Germany with appliedAI’s partner network to spark discussion and potential collaborations.
Artificial Intelligence in Business and Economy - Free Online Course
by Stephanie Eschmann on April 16, 2021
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'!
Maturity Level Case Study - Linde
by Stephanie Eschmann on March 17, 2021
In 2017, Linde, the global leader in industrial gases, joined the appliedAI initiative as a partner to accelerate the use of AI. Linde is working to implement AI solutions across all business units to increase productivity and competitiveness across the value chain and master the journey to AI maturity. Read here how.
Solving PDEs With Neural Networks
by Samantha Warren on January 31, 2021
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.
Technical Insight Series - Machine Learning Platform Evaluation
by Stephanie Eschmann on November 26, 2020
Read the following article to get insights on what the Machine Learning pipeline evaluation process for Wacker and Infineon looked like, which problems the companies were facing while using Machine Learning and what approach appliedAI conducted to set up and evaluate ML pipelines.
European AI Startup Landscape
by Samantha Warren on November 25, 2020
On November 17, 2020 the first version of the European AI Startup Landscape was launched which includes over 500 startups from France, Germany and Sweden. Check it out here.
Maturity Level 2 Case Study - EnBW (Energie Baden-Württemberg)
by Stephanie Eschmann on October 14, 2020
How did EnBW manage to implement AI into their organization, what hurdles did they have to overcome during implementation and what role has appliedAI played within their transformation since joining our partner network in early 2019? Find the answers to these questions and more here.
"AI is Always Just a Tool" - Interview with Dr. Philipp Hartmann, Director of AI Strategy at appliedAI
by Stephanie Eschmann on October 5, 2020
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.
Response to the 2020 European Commission’s White Paper on AI
by Stephanie Eschmann on August 27, 2020
In February of 2020, the European Commission Published the "White Paper On Artificial Intelligence - A European approach to excellence and trust". appliedAI and our partners have come together to publish a Position Paper outlining our response to the White Paper.
How Corona Crisis is Affecting Artificial Intelligence in Europe - 5 Questions to Dr. Philipp Gerbert
by Stephanie Eschmann on July 1, 2020
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.
Maturity Level 1 Case Study - World Food Programme
by Stephanie Eschmann on June 9, 2020
On 27 February 2020, the team at appliedAI joined the The United Nations World Food Programme Innovation Accelerator for a workshop to tackle the question "how AI can be used to help achieve zero hunger by 2030".
Artificial Intelligence - the Key to Intelligent Business of the Future?
by Stephanie Eschmann on June 8, 2020
AI has been regarded as the most disruptive future technology in the digital change for several years. But is the potential of AI as promising as the media often present it? How can companies benefit and how do they already work with AI? Read this UnternehmerTUM key topic article to learn more.
Building the organization for scaling AI
by appliedAI on February 19, 2020
We cover best practices for how to build the organization for scaling AI. Discover the elements needed for a comprehensive AI strategy, an outline for prototypical organizational setup and key learnings from mature AI scalers.