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News

Two newly established national tech collaborations can give your company a competitive advantage in the global market

OPINION in computerworld

We are ready to help: Two newly established national tech collaborations can give your company a competitive advantage in the global market

(Photo: Dan Jensen) 

In 2020, Denmark got two new nationwide players in digital innovation, which can promote the power of innovation in the future digital technologies and business.

We keep hearing it: Digital innovation and the use of cutting-edge digital technologies are essential for companies when it comes to increasing Danish competitiveness by developing future-proof products, increasing productivity and streamlining companies.

At the same time, studies show that many companies still tend to put the brakes on instead of stepping on the gas when it comes to digital progress.

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News

DIREC Tech Talk: How do we create more successes like Humio?

DIREC TECH TALK

How do we create more successes like Humio?

The sale of Humio for billions of dollars has generated many headlines about the Danish entrepreneurial business recently. They all ask the same question: How do we bring Danish world-class research into play and develop more Danish tech successes? Thomas Riisgaard Hansen, Managing Director of DIREC, asked Humio’s founder and CTO Kresten Krab Thorup.

Thomas Riisgaard Hansen, Managing Director of DIREC, asked Humio’s founder and CTO Kresten Krab Thorup.

Watch the interview here:


When asked how we get more successes like Humio, Kresten Krab Thorup answers clearly:

“You need to think big from the start. Someone has to be the best, so why not you? If you can get some venture capital, then it is all about speeding up, getting things developed and released to the customers. As a founder, obviously you are selling out of your business, but you do it to speed things up.”

Collaboration with research environments could also be an interesting way forward, and when researchers and businesses work together, they should think of their joint idea as a bet:

“Think of it as a bet. Is your idea viable? If you have the impetus to do it yourself in the best possible way, you can get really far. And at the same time, it attracts various interesting profiles to your company. And it is the company that can execute. That is what we have succeeded in doing.”

In short, Humio enables insight into massive amounts of log data, which is often spread out on many different servers in the cloud. With Humio’s system, businesses can see what is happening to their servers and see log data in real time. Today, the system is used by large businesses such as Microsoft and Bloomberg.

Kresten Krab Thorup is a computer scientist from Aarhus University and is one of the co-founders of the IT company, Trifork. He founded Humio in 2016 with two former Trifork colleagues, Christian Hvitved and Geeta Schmidt. They started Humio because they saw a gap in the market for a solution that could handle analysis of large amounts of log data.

They developed a prototype and started out with 4-5 employees in the first year. Starting up has especially required a technical understanding of how to use the hardware in the best possible way and an understanding of cloud technology, explains Kresten Krab Thorup:

“Cloud has become a novel architectural constraint. Today, it is not the physical hardware that controls performance and what can be done. It is the price of a service. It is a direct input to the architecture. It is much cheaper to store in the cloud than on a regular hard drive, and if you can make it run at peak performance, it will be much cheaper. Understanding it is extremely important”.

Humio has chosen to create their own database. This is the very key to their technology. But you become more successful by bringing together diverse skills to create a solid business:

“It requires a whole ecosystem of diverse skills, including front and back-end developers, UX designers, salespeople and accountants,” he says and adds:

“Most people tend to get together with like-minded people. But it is important to get together with people who knows something completely different, because often it is at the interface that ideas develop.

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Bridge project

Verifiable and Safe AI for Autonomous Systems

Project type: Bridge Project

Verifiable and Safe AI for Autonomous Systems

The rapidly growing application of machine learning techniques in Cyber-Physical Systems leads to better solutions and products in terms of adaptability, performance, efficiency, functionality and usability. However, Cyber-Physical Systems are often safety critical (e.g., self-driving cars or medical devices), and the resulting need for verification against potentially fatal accidents is self-evident and of key importance. Most recently, in the EU White Paper: “On Artificial Intelligence – A European approach to excellence and trust” (February 2020) the safety risks that come with usage of AI are 
stipulated:
 
AI technologies may present new safety risks for users when they are embedded in products and services. For example, as result of a flaw in the object recognition technology, an autonomous car can wrongly identify an object on the road and cause an accident involving injuries and material damage. This in turn makes it difficult to place liability in case of malfunctioning:
Under the Product Liability Directive, a manufacturer is liable for damage caused by a defective product. However, in the case of an AI based system such as autonomous cars, it may be difficult to prove that there is a defect in the product, the damage that has occurred and the causal link between the two.
 
What is needed are new methods, where machine learning is integrated with model-based techniques such that machine-learned solutions, typically optimising expected performance, are ensured to not violate crucial safety constraints, and can be certified not to do so. Relevant domains include all types of autonomous systems, where machine learning is applied to control safety critical systems.

The research aim of the project is to develop methods and tools that will enable industry to automatically synthesise correct-by-construction and near-optimal controllers for safety critical 45 systems within a variety of domains. The project will involve a number of scientific challenges including representation of strategies – neural networks (for compactness), decision trees (for explainability). Also, development of strategy learning methods with statistical guarantees is crucial.

A key challenge is understanding and specifying what safety and risk means for model-free controllers based on neural networks. Once formal specifications are created, we aim at combining the existing knowledge about property-based testing, Bayesian probabilistic programming, and model checking.

The scientific value of the project are new fundamental theories, algorithmic methods and tools together with evaluation of their performance and adequacy in industrial settings. These are important contributions bridging between the core research themes on AI and Verification in DIREC.

For capacity building the value of the project is to educate PhD students and Post Docs in close collaboration with industry. The profile of these PhD students will meet a demand in the companies for staff with competences on both machine learning, data science and traditional software engineering. In addition, the project will offer a number of affiliated students projects at master-level.

For the growing number of companies relying of using AI in their products the ability to produce safety certification using approved processes and tools will be vital in order to bring safety critical applications to the market. At the societal level trustworthiness of AI-based systems is of prime concern within EU. Here methods and tools for providing safety guarantees can play a crucial role.

The project involves the research themes of Verification (WS7), AI (WS2), and CyPhys (WS6).

March 1, 2021 – March 1, 2024 – 3 years

Total budget DKK 9,12 million / DIREC investment DKK 3,73 million

Participants

Project Manager

Kim Guldstrand Larsen

Professor

Aalborg University
Department of Computer Science

E: kgl@cs.aau.dk

Thomas Dyhre Nielsen

Professor

Aalborg University
Department of Computer Science

Andrzej Wasowski

Professor

IT University of Copenhagen
Department of Computer Science

Martijn Goorden

PostDoc

Aalborg University
Department of Computer Science

Esther Hahyeon Kim

PhD Fellow

Aalborg University
Department of Computer Science

Mohsen Ghaffari

PhD fellow

IT University of Copenhagen
Department of Computer Science

Thomas Asger Hansen

Head of Analytics and AI

Grundfos

Gitte Rosenkranz

Project Manager

HOFOR

Brian Boyles

Marketing and Pre-Sales

Seluxit

Malte Skovby Ahm

Research and business lead

Aarhus Vand

Daniel Lux

CEO

Seluxit

Karsten Lumbye

Chief Innovations Officer

Aarhus Vand

Kristoffer Tønder Nielsen

Project Manager

Aarhus Vand

Martin Zimmermann

Associate Professor

Aalborg University
Department of Computer Science

Christian Schilling

Assistant Professor

Aalborg University
Department of Computer Science

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News

Redefining healthcare – a conversation with Managing Director of DIREC, Thomas Riisgaard Hansen

REDEFINING HEALTHCARE

A conversation with Managing Director of DIREC, Thomas Riisgaard Hansen

CEO and President of Falck, Jakob Riis shares his conversation with Managing Director of DIREC (Digital Research Centre Denmark), Thomas Riisgaard Hansen. Thomas considers digitalisation an imperative for health as a mean not only for optimisation but also to create better outcomes.

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DIREC TALKS

DIREC TALKS: Software Engineering of Mobile, Ubiquitous and Robotic Systems

Software Engineering of Mobile, Ubiquitous and Robotic Systems

Software engineers developing mobile, IoT, wearable and ubiquitous systems are faced with a range of challenges, e.g. to create useful solutions that help users. Mikkel Baun Kjærgaard presents engineering tactics and open-source software technologies that help implement tactics in practice.

The rapid development in computing hardware, and sensor and user interface technologies enable the creation of more and more powerful computing solutions. Mobile, IoT, wearable and ubiquitous systems are designed to help us in our everyday life as well as in any profession. They heavily use machine learning components to automate and provide intelligent features. When working in concert with robot technology the solutions can also physically act in the world.

Software engineers developing such solutions are faced with a range of challenges to create useful solutions that consistently help users wherever they go, at an affordable cost and with a variety of hardware configurations. This means that successful solutions must deliver functionality that adapt to available resources at a given moment, e.g., in terms of sensor data accuracy, available energy, user interface options, processing power and communication options. To remain lawful, they also need protect privacy.

In this DIREC talk Mikkel Baun Kjærgaard will present and discuss engineering tactics to address such concerns and open-source software technologies that help implement tactics in practice. The tactics and software technologies are the result of more than 15 years of use-inspired basic research in projects with heavy industry involvement. The talk will give examples of ongoing projects researching tactics and software technologies for the design of systems with robotic elements. The talk will conclude with directions for future research.

MIKKEL BAUN KJÆRGAARD

PROFESSOR, MAERSK MC-KINNEY MOLLER INSTITUTE,
UNIVERSITY OF SOUTHERN DENMARK
Speaker

MIKKEL BAUN KJÆRGAARD

Mikkel Baun Kjærgaard conducts research within the areas of ubiquitous computing (synonymous with pervasive computing), mobile computing, Internet of Things (IoT), artificial intelligence and energy informatics. He has developed new methods for improving indoor positioning using location fingerprinting, designed systems for sensor fusion for improved indoor positioning, developed methods for addressing power consumption issues for mobile sensing and positioning.

He has researched new applications within sensing of crowd behaviors and position-based logistics for large building complexes. Furthermore, he has developed systems for occupant sensing, designed building operating system services and developed applications of these within energy informatics for improving the energy efficiency and flexibility of buildings. His research results have been published at premier venues within pervasive computing such as ACM MobiSys, ACM BuildSys, Pervasive, ACM Ubicomp, IEEE Percom, IEEE Pervasive Computing and Elsevier Pervasive and Mobile Computing. The results of his research have also enabled several industrial strength research prototypes that have been commercialized.