China’s drive for innovation is skewing the technology balance of power and has caught worldwide attention.
With heavy investments in research, especially in artificial intelligence (AI), China has not only created a challenging environment for its international tech competition, but paved the way for its digital forerunner position. The country’s strong support of scientific research at universities and research labs, whether through increased government funding or collaboration with companies, seems to play a huge role in China’s emergence as big player in AI.
According to a 2016 White House Report on AI cited in the New York Times, the vast number of Chinese papers on deep learning – a hot research area within AI – has already surpassed those published by US researchers. Chinese patent submissions linked to AI have more than tripled in recent years, beating Europe by far, yet still trailing behind the AI pioneer, the United States (Economist).
Why the Universal Interest in the Field of AI?
AI seeks to build machines or systems that imitate human behavior. Machine learning, a branch within the area of AI, is generating programs purely based on data, without being explicitly programmed. The recent rise of deep learning fueled by Big Data and strong computing infrastructure offers the possibility to create software that is turning the heads of business leaders all over the globe. They are lured by machine learning’s rich applicability and potential to optimize almost any business process, from enhanced individualized customer experience to risk prediction. According to Forbes, in 2016 investments in AI hit record numbers and remain on a continuous growth course – one of multiple signs that AI is on the brink of becoming an integral part for companies and organizations.
Yet while China and the U.S. fight over technological supremacy, investing strongly in scientific research to ensure their lead in AI, Europe lags behind. This is for several reasons according to the Financial Times, ranging from a lack of venture capital to the difference of European member states’ laws and languages to overall stricter data privacy regulations imposed. So how can European companies keep pace with this intense AI competition? What are they doing to enhance performance and impact in AI and machine learning? And how will they be able to drive innovation in this area in the future?
European companies are slow to answer questions like these. Although there are several startups in Europe mushrooming in the field of AI – with the UK, Germany, France, and Spain leading the way (Economist) – infrastructure and education need to be boosted to make headway in the AI race. To prepare for the future of AI, universities should embrace specific AI areas, such as semi- or unsupervised learning or the interpretability of machine learning models. Throughout their academic career, students in the field need to be equipped with solid knowledge in for instance machine learning technologies, model evaluation, parallel computing and data handling.
Tighter collaboration between business and academia will also be key to push European innovation forward. An early European Commission report about the state of European university-business cooperation revealed that in today’s knowledge economy such strategic partnerships are vital for the global competitiveness of Europe.
Creating a Global Academic Partner Web
As a response to this Europe-wide political appeal, SAP has increased collaboration with the research community. SAP engages in a number of initiatives, from sponsoring university events to explicit collaborations, such as the Future Soc Lab located near Berlin, which was built together with the Hasso Plattner Institute (HPI) and other industry partners. The lab offers young talents the full package of cutting-edge hard- and software and in this way fosters applied research with a focus on computer science and business information systems.
Another example is SAP Next-Gen, an innovation community for SAP Leonardo. SAP Next-Gen enables customers and partners to connect with academic thought leaders, researchers and students at more than 3,200 educational institutions in 111 countries, as well as with startups, tech community partners, venture firms, purpose driven partners, and SAP experts to reimagine the future of industries with SAP Leonardo, seed in disruptive innovation with startups, and build skills for digital futures.
Getting Ahead of AI
When it comes to the competitive AI and machine learning environment, SAP has realized how important a direct line to academia is for driving innovation. The machine learning research team from the SAP Innovation Center Network has built a global partnership network with top-ranking universities, such as MIT, Stanford, NYU or the University of Amsterdam. This collaboration benefits the research partners, who get funding and real industry problems to work on, while the additional pool of expertise and machine learning models give SAP a pole position to empower future applications.
According to Tassilo Klein, senior researcher at SAP, creating a cooperative network with universities enables the industry to quickly adopt the latest technology: “We work with a variety of machine learning researchers coming from top-tier universities all over the world. This gives us the unique opportunity to learn about new trends and methods, and to directly integrate them into our machine learning product portfolio. The projects we usually engage in have a time frame ranging from a half up to three years and are selected to be in strategically highly relevant fields. Clearly, this kind of collaboration helps us recognize emerging trends, while at the same time ensuring that the projects can be tailored to specific industry requirements.”
Academic Research Collaborations from Root to Crown
Working with students is another important part of SAP’s approach to enlarge the academic network in the machine learning field. The recent Bachelor Podium in Potsdam demonstrated how tech talents are getting on board to solve machine learning challenges. HPI Students from the IT-Systems Engineering study program presented their bachelor projects, unique business cases developed together with industry partners.
As part of this, a team from the SAP S/4HANA organization was supported by the SAP Innovation Center Network’s strategic projects team to provide a logistics use case including historical sales order data to a group of seven students. Their project examined options to apply machine learning techniques to the problem of sales order delay prediction. Throughout the year, the scholars got further backing of the experts from the machine learning research team of the SAP Innovation Center Network to finalize their machine learning solution that mitigates the risk of late product delivery.
Jan Kossmann, HPI PhD student and project supervisor, values the close collaboration between SAP and HPI: “The bachelor projects are a great opportunity for students to work on real-world problems in realistic settings together with industry partners like SAP. Certainly, one of the highlights for the students was the presentation of their prototype at our booth at this year’s SAPPHIRE NOW in Orlando.”
SAP benefits by cementing ties with the emerging machine learning talents that contribute fresh insights and new ideas to optimizing internal business processes. The company sees the tandem of business and academia as an important building block to extend its pool of expertise and to push the frontiers of AI, and, en passant, it can do its bit to strengthen Europe’s future role in the global tech race.