When physician and AI work together, the patient benefits

The machine learning method by Iiris Sundin and her colleagues taken into account uncertainties of the world. This is important in decision-making. Photo Matti Ahlgren / Aalto University

The machine learning method by Iiris Sundin and her colleagues taken into account uncertainties of the world. This is important in decision-making. Photo Matti Ahlgren / Aalto University

Doctoral student Iiris Sundin learned in her studies that a machine learning model could make use of a physician's silent knowledge which usually is never written down. This kind of model predicts best how a given patient will react to specific treatment.

Artificial Intelligence opens up new avenues into health care, for example, but its potential is as of now not fully put to use. There are many reasons, but the most important one became clear to Iiris Sundin as she was starting her doctoral studies on machine learning: machine and Man must learn to work together.

"When I acquainted myself with the research of my advisor, Professor Samuel Kaski, on user modeling where the machine tries to understand the human, I realized the huge potential. Cooperation can mean other things than the human operating Excel or passively staring at projections on the screen," says Sundin, a doctoral student at the Department of Computer Science at Aalto University.

Samuel Kaski is the director of FCAI. Sundin's research combines Medicine, technology and many other interests of hers. She has also always wanted to work at something that benefits other people. On the other hand, she was interested in mathematics and programming.

The role of AI and machine learning in health care is researched a lot. Sundin's point of view is unique in having the machine make use of the doctor's knowledge to define the best possible care for the patient.

 

There are uncertainties in the world that must factor in when decisions are taken

Physicians have vast quantities of knowledge that is never written down and that is impossible to feed directly into a learning algorithm. Sundin and her colleagues have found out just how the machine could make use of such knowledge in e.g. figuring out the efficacy of a given type of medication.

Sundin and her colleagues have at their disposal, for example, data on gene specimens collected from cancerous cells, courtesy of FIMM, Institute for Molecular Medicine Finland. Researchers took a look at the mutations in the specimens and tried to predict which cancer medicine would work best for each patient.

We don't just discuss the average person, we acknowledge there are differences, and take it into account when reaching decisions.

It is crucial to remember that there are always uncertainties in the world, and thus, also a physician's knowledge of the effect of different mutations can be uncertain. The machine learning model devised by the research group takes this into account. The results show including expert knowledge in machine learning models and emphasizing data improve prognoses on how a given patient will react to a particular treatment.

So the model developed by researchers depicts realistically how sure people are of the different properties of real matters. "I would that such thinking were more common: we don't just discuss the average person, we acknowledge there are differences, and take it into account when reaching decisions. That way, things can be modeled in a more useful manner."

 

The researcher gets to tell something new about the world

Even though Sundin was fond of mathematics already as a child, and it comes naturally to her to see the world via mathematical thinking, art held a big role in her life, especially when she was young.

As a schoolgirl, she played the piano, sang in a choir, read books and attended art school. Now, she is into yoga, air acrobatics and camping. A researcher can be interested in many things, and creativity, for example, helps at work, too. "When you e.g. make posters for a conference, it is very useful if you can do some of the visual elements yourself."

The antics of engineering students were something Sundin grew up with. Both her parents graduated from the Helsinki University of Technology, and the family always celebrated First of May with parents’ college pals. All the adults sported the traditional tassel caps of engineering students. So engineering studies came naturally. "The degree of an engineer is really well-rounded and offers a good start. You can choose to be a researcher, industrial work or pretty much anything."

I realized researching was such great fun that I rather do more of the same.

Sundin completed her Master’s in Automation and System Technology. Although she never fancied herself a researcher, her interest in it was kindled when she was working on her dissertation. Sundin was modeling the properties of a drop of fluid on different surfaces.

Research offered a way to bring received mathematical ways of thinking and skills into the real world, and to tell something about that world. "I realized it was such great fun that I rather do more of the same."

 

”You succeed at work if you are open”

Sundin says she sometimes imagined researchers worked alone in their chambers. That is no longer the case, anyway. "You succeed better at work is you are open, socially adept and like to travel to conferences and network with the people there."

Research work is social. "You succeed better at work is you are open, socially adept and like to travel to conferences and network with the people there,” says Iiris Sundin. Photo Matti Ahlgren / Aalto University

Research work is social. "You succeed better at work is you are open, socially adept and like to travel to conferences and network with the people there,” says Iiris Sundin. Photo Matti Ahlgren / Aalto University

It is crucial for a doctoral student to possess the wish and motivation to understand things. The point of further studies is to delve into one fairly narrow area of learning very profoundly, something which can be demanding. Therefore, it is important to have tenacity and the ability to stick to it. "It is needed, if you want to make it to the end."

Even though Sundin has hitherto worked in basic research, she feels the methods developed need to be taken to a practical level, once the foundation laid by basic research is robust enough.

In the future, she hopes to apply what she has learned and continue work for the benefit of people and also the environment. "I hope to work at some Finnish institute doing research that help Finland make smarter decisions when it comes to the environment."

Authored by Anu Haapala
English translation by Susanna Bell

Expertise from FCAI selected to the Finnish government’s Research and Innovation Council

Photo Anni Hanén / Aalto University

Photo Anni Hanén / Aalto University

Samuel Kaski, Director of Finnish Centre for Artificial Intelligence (FCAI) and Professor at Aalto University, and Antti Vasara, CEO of VTT Finland, have been appointed to the Finnish Government’s Research and Innovation Council. The new council was elected on October 10.

FCAI is pleased that Finland sees the importance of artificial intelligence and the Finnish government displays trust in knowledge and research in general.

The Research and Innovation Council is an advisory body chaired by Prime Minister Antti Rinne that addresses issues relating to the development of research and innovation policy that supports wellbeing, growth, and competitiveness.

The vice chairs are of the council are Hanna Kosonen, Minister of Science and Culture, and Katri Kulmuni, Minister of Economic Affairs. The other three governmental members are Li Andersson, Minister of Education; Anna-Maja Henriksson, Minister of Justice; and Maria Ohisalo, Minister of the Interior.

The other members of the new council are Heidi Fagerholm (Head of Early Research and Business Development at Merck KGaA), Peppi Karppinen (Dean at the University of Oulu), Ilkka Kivimäki (Partner at Maki.vc), Petra Lundström (Director at Fortum), and Vesa Taatila (Rector and CEO at the Turku University of Applied Sciences).

The Finnish "Ele­ments of AI" on­line course trains em­ploy­ees of the European Union

Photo Matti Ahlgren / Aalto University

Photo Matti Ahlgren / Aalto University

An extremely successful online course that is open to all on the basics of artificial intelligence, developed by the technology company Reaktor and FCAI, has been selected to be part of the voluntary continuing education for officials working for the European Union.

The kick-off for the course was held at an event organised on 18 September.

Artificial intelligence has the potential to provide solutions to a range of societal challenges, which is why its utilisation is an important focus area for the EU. Staff training is part of promoting the bloc’s AI strategy.

In Finland, a number of government ministries, the Tax Administration and more than 250 other organisations and companies have offered the course to their staff. 

Read more about the course

View a video on the course

Follow the phenomenon on social media: #elementsofai

 

Further information:

Ville Sinisalo, Reaktor
Phone +358 40 762 2019
ville.sinisalo@reaktor.com

Tanja Remes, University of Helsinki
Phone +358 50 415 0286
tanja.remes@helsinki.fi

Smartphone typing speeds catching up with keyboards

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A study of over 37,000 users shows that the ‘typing gap’, the difference typing speeds between mobile devices and physical keyboards is decreasing, and 10–19-year olds can type about ten words-per-minute faster than their parents' generation.

The largest experiment to date on mobile typing sheds new light on average performance of touchscreen typing and factors impacting the text input speed. Researchers from Finnish Centre for Artificial Intelligence (FCAI), University of Cambridge and ETH Zürich analysed the typing speed of tens of thousands of users on both phones and computers. Their main finding is that typing speeds on smartphones are now catching up with physical keyboards.

“We were amazed to see that users typing with two thumbs achieved 38 words per minute on average, which is only about 25% slower than the typing speeds we observed in a similar large-scale study of physical keyboards,” said Anna Feit, a researcher at ETH Zürich and one of the co-authors.

“While one can type much faster on a physical keyboard, up to 100 wpm, the proportion of people who actually reach that is decreasing. Most people achieve between 35-65 WPM.”

The authors call the difference between typing on a keyboard and a smartphone “the typing gap” and predict that as people get less skilled with physical keyboards, and smart methods for keyboards improve further (such as auto-correction and touch models), the gap may be closed at some point. The fastest speed the researchers saw on a touchscreen was a user who managed the remarkable speed of 85 words per minute.

Six hours a day phone time

The research team collected a dataset from over 37,000 volunteers in an online typing test, with the help of the typing speed test service TypingMaster.com. With the consent of the participants, they recorded the keystrokes they made while transcribing a set of given sentences to assess their typing speed, errors and other factors related to their typing behaviour on mobile devices. 

 The dataset is unique in its size and made publicly available. While the majority of volunteers were women in their early twenties and about half of the participants came from U.S., the dataset includes people from all ages and from over 160 countries. On average, the participants reported spending about 6 hours per day on their mobile device.

Anna Feit explains: “Such large amount of experience transfers to the development of typing skill and explains why young people, who spend more time with social media, communicating with each other, are picking up higher speeds.”

One finger, or two thumbs?

The best predictor of performance is whether you use one finger or two thumbs to type. Over 74% of people type with two thumbs, and the speed increase it offers is very large. The study also found that enabling the auto-correct of words offers a clear benefit, whereas word prediction, or manually choosing word suggestions, does not.

As Sunjun Kim, a researcher at Aalto University, explains, “The given understanding is that techniques like word completion help people, but what we found out is that the time spent thinking about the word suggestions often outweighs the time it would take you to type the letters, making you slower overall.” Most users used some type of intelligent support. Only 14% of people typed without auto-correction, word suggestions or gesture typing.

The study also exposed a strong generation effect. Young people, between 10 and 19 years of age are about 10 wpm faster than people in their 40s. Antti Oulasvirta, professor at Aalto University and researcher at FCAI: “We are seeing a young generation that has always used touchscreen devices, and the difference to older generations that may have used devices longer, but different types, is staggering.”

The authors found no benefit from formal training on the ten-finger typing system on physical keyboards. Oulasvirta continues: “This is a type of motor skill that people learn on their own with no formal training, which is very unlike typing on physical keyboards. It is an intriguing question what could be achieved with a careful training program for touchscreens.”

If you want to type faster on mobile, the researchers recommend using two thumbs and enabling auto-correction of words. 

The study will be presented at the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI), in Taipei, Taiwan, 2 October 2019. 

More information on the study, including the paper and the dataset: https://userinterfaces.aalto.fi/typing37k/. If you want to try the typing-speed test yourself, you can have a go at http://typingtest.aalto.fi/.

Contact information

Associate Professor Antti Oulasvirta
Aalto University, Finnish Centre for Artificial Intelligence
antti.oulasvirta@aalto.fi 

Dr. Anna Feit
ETH Zurich
anna.feit@inf.ethz.ch

Ten research papers from FCAI accepted to the prestigious NeurIPS conference

Photo Matti Ahlgren / Aalto University

Photo Matti Ahlgren / Aalto University

Research conducted at the Finnish Centre for Artificial Intelligence (FCAI) is well presented at this year’s NeurIPS conference. In total, the prestigious conference has accepted ten submissions from either Aalto University or the University of Helsinki.

“Especially in European terms, we did well this year and the number of publications is within the top 10 of European academic institutions,” says Antti Honkela, Associate Professor of Computer Science at the University of Helsinki.

NeurIPS is the largest and most prestigious conference on machine learning, and it has become increasingly popular in the past years. In 2018, the main conference was sold out in under 12 minutes and therefore this year’s registration was based on a lottery.

“When I visited NeurIPS for the first time 15 years ago, there were 207 publications and less than a thousand participants. This year, the conference lasts for about the same time but there will be more than 1,400 presentations and possibly more than 12,000 participants,” says Honkela.

Over the past 32 years, the NeurIPS conference has been held at various locations around the world. This year’s conference will be held in Canada, at the Vancouver Convention Center.

Honkela and his research group wrote one of the accepted papers, which Honkela sees as a valuable acknowledgement for his group’s hard work. Researchers studied privacy in machine learning, and due to this work, they can assure that no one’s privacy will be violated by using a learning algorithm utilizing, for example, health data. Honkela and his colleagues developed a new version of Markov chain Monte Carlo, one of the most widely used Bayesian algorithms.

Their version of the algorithm assures privacy for a larger variety of models than any previously designed algorithm. “Therefore, this algorithm opens new, important possibilities for statistical inference that aims to secure privacy,” explains Honkela.

Accepted papers from FCAI (Aalto University and the University of Helsinki):

Regularizing Trajectory Optimization with Denoising Autoencoders
Rinu Boney (Aalto University) · Norman Di Palo (Italian Institute of Technology) · Mathias Berglund (Curious AI) · Alexander Ilin (Aalto University) · Juho Kannala (Aalto University) · Antti Rasmus (Curious AI) · Harri Valpola (Curious AI)

Improved Precision and Recall Metric for Assessing Generative Models
Tuomas Kynkäänniemi (Aalto University; NVIDIA) · Tero Karras (NVIDIA) · Samuli Laine (NVIDIA) · Jaakko Lehtinen (Aalto University; NVIDIA) · Timo Aila (NVIDIA)

Differentially Private Markov Chain Monte Carlo
Mikko Heikkilä (University of Helsinki) · Joonas Jälkö (Aalto University) · Onur Dikmen (Halmstad University) · Antti Honkela (University of Helsinki)

On Adversarial Mixup Resynthesis
Christopher Beckham (Mila, Polytechnique Montréal) · Sina Honari (Mila, Polytechnique Montréal) · Alex Lamb (Mila, University of Montreal) · Vikas Verma (Aalto University) · Farnoosh Ghadiri (Mila, Polytechnique Montréal) · R Devon Hjelm (Mila, University of Montreal; Microsoft Research) · Yoshua Bengio (Mila, University of Montreal) · Chris Pal (Mila, Element AI, Polytechnique Montréal)

High-Quality Self-Supervised Deep Image Denoising
Samuli Laine (NVIDIA) · Tero Karras (NVIDIA) · Jaakko Lehtinen (Aalto University; NVIDIA) · Timo Aila (NVIDIA)

Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer
Wenzheng Chen (University of Toronto) · Huan Ling (University of Toronto; NVIDIA) · Jun Gao (University of Toronto) · Edward Smith (McGill University) · Jaakko Lehtinen (Aalto University; NVIDIA) · Alec Jacobson (University of Toronto) · Sanja Fidler (University of Toronto)

Machine Teaching of Active Sequential Learners
Tomi Peltola (Aalto University) · Mustafa Mert Çelikok (Aalto University) · Pedram Daee (Aalto University) · Samuel Kaski (Aalto University)

ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
Cagatay Yildiz (Aalto University) · Markus Heinonen (Aalto University) · Harri Lähdesmäki (Aalto University)

Identifying Causal Effects via Context-specific Independence Relations
Santtu Tikka (University of Jyväskylä) · Antti Hyttinen (University of Helsinki) · Juha Karvanen (University of Jyväskylä)

Variational Bayesian Decision-making for Continuous Utilities
Tomasz Kuśmierczyk (University of Helsinki) · Joseph Sakaya (University of Helsinki) · Arto Klami (University of Helsinki)

The full list of accepted papers is available on the NeurIPS website.

FCAI activities are well underway

Following the Academy of Finland Flagship status granted in the beginning of 2019, a lot of great things are going on in FCAI: excellent research is taking place and our flagship activities and organization are now getting their shape step by step. This fall, FCAI will advance many of its central functions, including Research Programmes and Highlights, and organize several events.

Tackling the shortcomings of the current AI and demonstrating the impact

The core of FCAI is formed around its goal-driven research programs. They are designed to pursue the ambitious goal of FCAI: to create AI methods and systems that are data efficient, trustworthy, and understandable. The first five programs have started their operations this year and two new programs are now in a ramp-up phase. The new programs, Autonomous AI and AI in Society, will further advance FCAI’s research mission by building fundamental AI solutions to enable diverse applications and tackling questions of societal change brought by AI development. To further concretize the impact AI brings in to various disciplines, FCAI has launched five multidisciplinary FCAI Highlights. The Highlights are run in close collaboration with the Research Programs and they aim to provide concrete AI-based solutions to illustrate the scientific and socio-economic impact of the Research Programs.

We welcome everyone to FCAI Community event on 21 October to get more information about FCAI. You can also approach the respective coordinating professor to learn more about the FCAI Research Programs and Highlights.

Growing community: FCAI Special Interest Groups and AIX Forum

To further serve the multidisciplinary AI ecosystem, we are also developing other mechanisms to engage in FCAI, aimed at people from our host organizations as well as from elsewhere.

During the fall we will introduce FCAI Special Interest Groups (SIGs) to gather people around a common theme of interest, e.g. a specific sub-field of AI or an application area of AI. We have three SIG pilots, FCAI SIG in Language, Speech and Cognition, FCAI SIG in Health, and FCAI SIG in 6G and AI – and more will soon be initiated. 

We are also excited to present a new transdisciplinary series, AIX Forum. AIX Forum is designed to function as a meeting place for people applying AI in their specific domain, people working in similar problems in some other domain, and people actively developing new AI tools and methods that can potentially be applied in these domains. The first AIX Forum AI and Traffic was organized in September in collaboration with The Traffic Research Unit (University of Helsinki). Several other AIX seminars will be organized during the fall extending also outside the capital area.


AI Day 2018 brought together over 550 people from academia, industry and public sector to exchange knowledge and ideas on AI. Photo: Matti Ahlgren

AI Day 2018 brought together over 550 people from academia, industry and public sector to exchange knowledge and ideas on AI. Photo: Matti Ahlgren

Creative collaboration of academia, industry, and public sector

Alongside with top-quality research FCAI aims to create high impact with close collaboration with industry and public sector. 

We are very proud of our versatile collaboration with various partners and are keen to strengthen this ecosystem even further. FCAI is actively growing its partner network. Most recently we have started cooperation with Neste and the City of Helsinki in summer 2019. We will also soon launch a streamlined FCAI membership model to better answer the needs and wishes of our members and researchers.

In November FCAI will organize the annual AI Day to bring together researchers, companies, students and the public sector to exchange ideas and to form news contacts in the fast-developing field of AI. The popular event will take place in Otaniemi on November 26. You can read more about AI Day here. The registration will open soon with an early bird registration option, so stay tuned!

In parallel with the close cross-sector collaboration, FCAI focuses on educational efforts to make the impact AI creates in society more understandable and accessible for everyone. One of our biggest goals on this front includes the initiative to provide basic AI literacy for all. This ambitious objective has been most notably advanced by the hugely popular MOOC Elements of AI that has reached almost 200 000 registered participants from more than 100 countries. The course was translated into Finnish in early 2019 and translations into other languages, including German and Swedish, as well as two follow-up courses are in preparation.

How to get involved?

Do you want to contribute to our mission? Please feel free to join our mailing list, to register as FCAI Community Member or come to our events to learn more!


FCAI RESEARCH AND IMPACT IN A NUTSHELL

Contact information at https://fcai.fi/organization/#research

FCAI Research Programs and coordinating professors 

R1: Agile probabilistic AI, Aki Vehtari
R2: Simulator-based inference, Jukka Corander
R3: Next-generation data-efficient deep learning, Harri Valpola and Alexander Ilin
R4: Privacy-preserving and secure AI, Antti Honkela
R5: Interactive AI, Antti Oulasvirta
R6: Autonomous AI, Ville Kyrki
R7: AI in society, Petri Ylikoski

 

FCAI Highlights and coordinating professors

A: Easy and privacy-preserving modeling tools, Arto Klami
B: AI-driven health, Pekka Marttinen
C: Intelligent service assistant for people in Finland, Tommi Mikkonen
D: Intelligent urban environment, Kai Puolamäki
E: AI-driven design of materials, Patrick Rinke

 

Major upcoming events

21 October: FCAI Community Event
26 November: AI Day 2019

See more upcoming events at https://fcai.fi/events





FCAI receives the Aalto Research Impact Award 2019

Aalto University recognized FCAI at the Opening Ceremony of the Academic Year by granting the Aalto Research Impact Award 2019 to the FCAI team. Aalto Impact awards recognize outstanding impact and they are given for the excellent work done during the previous academic year.

FCAI is a joint effort of an active community. We appreciate that Aalto University recognised the achievements of the big team who has started the initiative. FCAI is still expanding and developing new ways to contribute to the research and impact and we are hoping to see even more talents joining FCAI in future.

In the same ceremony, FCAI Manager Outi Kivekäs was granted the Aalto Success Enabler Award 2019 for the work done with her earlier team concerning the Academy of Finland profiling funding applications.

Read more in the Aalto University news:

https://www.aalto.fi/en/news/eight-teams-awarded-at-the-opening-ceremony

 

How is AI re­vo­lu­tion­iz­ing traffic? A new series of events shows prac­tical im­pacts of AI in our lives

AIX Forum, a new series of events, brings AI developers and users together. The aim of the AIX Forum is to find new ways to make use of AI in different areas of society.

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This autumn, FCAI will launch new AIX Forum events that seek new ways to apply AI in practice. The first event of the series on traffic will take place on September 4 in Helsinki.

The mission of FCAI researchers is to develop AI applications that answer real-life needs in different areas of life. The new train of events wants to find new practical solutions for those needs.

“AI applications challenge common practices in many fields, and the pace of change is fast. At AIX Forum events, researchers who focus on AI or other topics, companies and public sector representatives can find new ways to make use of AI,” says Petri Myllymäki, Vice Director of FCAI and Professor of Artificial Intelligence and Machine Learning at the University of Helsinki.

Most AIX Forum events consist of three parts and will be held in English. The events typically start with a few, brief speeches in which experts from different fields present a problem that could be solved by using AI. The speeches are followed by panel discussions during which AI researchers and developers, together with the speakers, seek solutions for the presented problems. At the end of each event, there will be time for networking.

Traffic as the first X

The abbreviation AIX is derived from the term artificial intelligence and the letter X, which represents an application area of AI. FCAI organizes the first event, AI and Traffic, together with the Traffic Research Unit of the University of Helsinki.

The first event looks into traffic-related AI applications and relevant research from different perspectives. The goal is to find interesting research questions within the smart traffic technology discipline and estimate what type of broad, societal impact technology has on traffic development.

“In traffic, automation and algorithms change the traditional driver-vehicle setting in a fundamental way. This doesn’t apply only to the technology behind vehicles, instead also traffic planning, driver training, and traffic education will change,” says Otto Lappi, the Group Leader of the Traffic Research Unit and Discipline Coordinator of Cognitive Science.

“Human intelligence and AI will, for the first time, share a common, physical environment, and from the cognitive science perspective, this change comes with fundamental, complex, and still mainly unknown questions regarding how the informational workload will be divided between humans and computers,” adds Lappi.

The event is aimed at researchers focusing on traffic, transportation planning, traffic safety, automated vehicles, traffic infrastructure, or traffic education, and for anyone interested in these research topics. In the future, FCAI plans to organize AIX events around Finland. The future events will focus on AI in civil service and AI in medicine, among other topics.

Read more about AI Forum: AI and Traffic seminar here.

Further information

Petri Myllymäki
Vice Director of FCAI
Professor of Artificial Intelligence and Machine Learning, University of Helsinki
+358 40 553 1162
petri.myllymaki at helsinki.fi

Otto Lappi
Discipline Coordinator, Cognitive Science
Traffic Research Unit of the University of Helsinki
+358 29 412 9674
otto.lappi at helsinki.fi

Deep learning model developed by Finnish AI researchers detects diabetic eye diseases accurately

Professor Kimmo Kaski. Photo Aalto University

Professor Kimmo Kaski. Photo Aalto University

Finnish AI researchers have developed a deep learning system that shows great potential in detecting diabetic eye diseases, which could facilitate doctors’ work and decrease healthcare expenses.

According to the research findings published in Nature Scientific Reports, the deep learning model detects the severity grade of diabetic retinopathy and macular edema accurately. Diabetic retinopathy is one of the most common comorbidities of diabetes that, if untreated, may lead to severe vision loss. Macular edema refers to swelling under a specific part of the retina caused by diabetic retinopathy.

The deep learning model identified referable diabetic retinopathy comparably or better than presented in previous studies, although only a very small data set was used for its training. The model turned out to be more accurate in identifying diseases when the training images of patients’ fundus were of high quality and resolution.

Results suggest that such deep learning system could increase the cost-effectiveness of screening and diagnosis and that the system could be applied to clinical examinations requiring finer grading.

Currently, retinal imaging is the most widely used method for screening and detecting retinopathy, and medical experts evaluate the severity and the degree of retinopathy in people with diabetes based on the fundus or retinal images of the patient’s eyes.

As diabetes is a globally prevalent disease and the number of patients with diabetes is rapidly increasing, also the number of retinal images will increase, which in turn introduces a large labor-intensive burden on the medical experts as well as cost to the healthcare. An automated system that would either assist medical experts or work as a full diagnostic tool could alleviate the situation.

The research group consisted of researchers from Aalto University Department of Computer Science, Digifundus Ltd – a Finnish provider of diabetic retinopathy screening and monitoring services –, and Central Finland Central Hospital.

Link to the research article: https://www.nature.com/articles/s41598-019-47181-w

Further information
Kimmo Kaski
Professor, Computational Science
Finnish Center for Artificial Intelligence (FCAI)
Aalto University Department of Computer Science
kimmo.kaski@aalto.fi

FCAI supports Finland’s EU presidency aims for AI

The Finnish Centre for Artificial Intelligence (FCAI) supports Finland’s plans to focus on digital development and challenges of AI during the country’s presidency of the Council of the European Union. Finland is bringing these topics up in its programme for the presidency period, and Samuel Kaski, the director of FCAI and professor at Aalto University Department of Computer Science, sees that as an excellent thing.

“The EU needs to launch new big things in addition to the recently decided super computers, one of which will be placed in Finland. During its presidency, Finland of course needs to work for the whole EU, but at the same time, it is necessary that it doesn’t forget to continue working on its own AI programme at full speed,” says Kaski.

AI, and data and platform economies are key factors contributing to Europe’s growing productivity, prosperity, and wellbeing.  According to Finland’s programme for the presidency, maintaining economic growth and employment will depend on the ability of business and industry to make full use of the potential offered by digital technologies.

During its presidency, Finland wants to promote discussion on AI and digitalisation with a view to developing tomorrow’s capabilities. The economic potential of digitalisation and AI applications is enormous, and Europeans need to be frontrunners in tapping into these developments, politicians write in the report.

Businesses and academic institutions in China, United States, and the rest of the world compete fiercely for top AI talent. Kaski points out that China and the US are currently investing large sums of money in AI research. Therefore, one of the greatest challenges of European AI research is to be competitive. If Finland and the rest of Europe react to this competition too late, they will end up suffering from a brain drain.

“Fortunately, Europe isn’t helpless at all. At this moment, European top AI research is about to organize into strong networks and the EU is currently working on an investment plan. Finland is a frontrunner with its AI strategy, the latest version of which was just published, and it has been strongly involved in creating networks,” according to Kaski.

Motivated research groups, vibrant startup culture, and cooperation with companies are Finland’s strengths

According to FCAI, Finland needs to invest in its existing top talent and attracting new talent in order to stay in the front line of the global AI competition.

Finland needs to enhance its position by strengthening existing top expertise in small-data research and strong traditions in B2B operations. Finnish business operations rely strongly on B2B businesses. Moreover, remodelling funding and research, and encouraging businesses to invest in AI is crucial. FCAI has sent these key messages also to the new government of Finland.

Similar points were brought up in the final report of Finland’s Artificial Intelligence Programme 2019, written by the Ministry of Economic Affairs and Employment of Finland. The report was recently published in English, and FCAI supports its initiatives.

The experts of the ministry write that Finland’s strengths include highly motivated research groups focusing on emerging sectors, a vibrant startup culture, and close cooperation between research institutions and companies. According to the report, FCAI is an excellent example of an institution that develops AI-based solutions for processing small amounts of data and solving problems of B2B companies. It has an important role in boosting Finland’s strengths.

Overall, the establishment of FCAI and the flagship funding granted by the Academy of Finland is one of the main actions Finland has already taken in order to ensure that AI can be adopted more quickly and easily. This is an important step towards training and attracting top talent to Finland. “Through FCAI, the Finnish leading-edge research can form one hub in the international competence network,” experts of the Ministry of Economic Affairs and Employment write.

The complex challenges of AI applications and close cooperation with companies is at the core of FCAI’s operations. In order to having sufficient resources, these types of things are key factors in attracting top talent, experts of the ministry write.

Further information
Samuel Kaski
Director, FCAI
Professor, Aalto University Department of Computer Science
Phone +358 50 305 8694
samuel.kaski@aalto.fi

University of Helsinki announces AI-themed PhD positions – apply in September

University of Helsinki, one of the institutions behind FCAI, announces AI-themed doctoral candidate positions. The application period opens on Tuesday 3 September and ends on Tuesday 17 September.

Find more information about the positions, eligibility criteria and application process on the University of Helsinki website.

Outi Kivekäs appointed as the manager of FCAI: “unique chance to build this type of research community”

Photo Matti Ahlgren / Aalto University

Photo Matti Ahlgren / Aalto University

Outi Kivekäs, Doctor of Science, has been appointed as the manager of FCAI. She started in her new role at the beginning of May.

 “People speak about artificial intelligence everywhere,” says Kivekäs. “It is clear that the best AI researchers of Finland work for FCAI. In some areas, our researchers are already among the best ones in the whole world. This is a unique chance to be part of building this type of a research community.”

Kivekäs has her background in electrical engineering. Before starting in her new role, she worked several years at Aalto University Research and Innovation Services. She was leading the pre-award team that helped researchers to apply research funding.

Through her earlier experience, Kivekäs is very familiar with one of the organizations behind FCAI, Aalto University, and research conducted at it. Now she is excited about learning more about the two other organizations that initiated FCAI, University of Helsinki and  VTT Technical Research Centre of Finland.

Kivekäs has broad understanding of how universities work and what types of projects they run. She brings structure and experience about project management to FCAI. “Launching a large project is always slow in the beginning. In the coming months, we will organize the initiatives we have already started into a whole and encourage new people interested in applications of AI to join FCAI.”

FCAI and Aalto EE have joined forces for programs around AI

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Aalto University Executive Education (Aalto EE) and the Finnish Center of Artificial Intelligence FCAI are cooperating in AI training programs that are designed for executives, managers, and experts from different organizations. The programs have proven to be an impactful way of learning while working. The first deliveries of the programs have received excellent feedback and the next programs are coming up in the fall. 

Artificial Intelligence in Business

An intensive two-day program “Tekoäly liiketoiminnassa – teknologiasta strategiaan” provides leaders with a practical and comprehensive overview of artificial intelligence, data, and emerging business models and their impact on strategy, operations, and leadership. Taught by leading researchers in the field, the program focuses on issues such as the applications of artificial intelligence, the prerequisites for its implementation, and the strengths of people and AI. The program is held in Finnish.

Diploma in Artificial Intelligence

The Diploma in Artificial Intelligence gives you an in-depth understanding of the latest AI technologies and methods and how to apply them. The program is taught by experts from leading research organizations and includes keynotes from leading companies in industry. It is a joint program from Aalto PRO, University of Helsinki HY+ and the Finnish Center for Artificial Intelligence FCAI.

According to Suunto’s Program Quality Manager Ville Halkola, the program opened up the huge potential and possibilities of AI in a very concrete way. Read more here.

More information

Jonni Junkkari, Solutions Director,
Aalto University Executive Education
jonni.junkkari@aaltoee.fi
tel. +358 10 837 3860

 

High-level delegation from the Czech Republic Parlament Visited FCAI – Support for Ethical Application of AI

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A high-level delegation from the Czech Republic has visited FCAI. Ethical application of artificial intelligence was the core of the visit, as making use of AI ethically, calls for collaboration with like-minded countries in Europe.

During the visit of Mr Ivan Jukl, the Ambassador of the Czech Republic and his delegation, the need for systematic collaboration with small, European countries having parallel targets was emphasised.

“China and the US are investing massively in the development of AI.  To make the most of the opportunities offered by AI and stand up to competition, European countries need to join their forces. Cooperation rather than competition,” said Professor Petri Myllymäki, vice-director of FCAI in his speech.

The Czech Republic recently published the National Artificial Intelligence Strategy. Strategy outlines the seven priority areas in the field of artificial intelligence. The list includes for example the promotion of research and development activities by financing research and development and providing investment support. Development of the AI ecosystem in the Czech Republic and boosting international cooperation in the field of AI are among the top priorities as well.

The visit was hosted by Petri Myllymäki and Ilmari Lastikka, Vice Precident, VTT International affairs. Delegation of the Czech Republic consisted of Ivan Bartos, chairman of the Committee on Public Administration, Martin Kupka, vice-chairman of the Committee on Public Administration, Adam Kalous, vice-chairman of the Committee on Public Administration and Jiri Dolejs, member of the Committee on Public Administration.

Finland will host one of the most powerful supercomputers in the world

One of the most competitive supercomputers in the world will be placed in Kajaani, Finland.

According to the CSC Datacenter that will host the new supercomputer, the new machine will be about ten times more powerful than the most powerful supercomputer currently in Europe.

Computing power is required in leading research in a wide range of disciplines, including artificial intelligence.

This type of supercomputing and data infrastructure helps position Europe as one of the world leaders in supercomputing. It allows European researchers to access top-level computing resources.

The decision to place the supercomputer in Finland was made by the EuroHPC Joint Undertaking, a high performance computing initiative supported by the European countries and the European Union.

More information in the press release by the CSC Datacenter

City of Helsinki becomes a partner of FCAI

The City of Helsinki has announced that it will become a partner of the Finnish Center for Artificial Intelligence (FCAI).

By joining FCAI, Helsinki wants to support its goals in terms of collaboration with universities, competitiveness, and digitalization.

In particular, this decision aids collaboration between Helsinki, the University of Helsinki, and Aalto University. It also supports actions that help to attract more innovations and investments to the Finnish capital region.

FCAI is a nation-wide competence center for Artificial Intelligence in Finland, initiated by Aalto University, the University of Helsinki, and VTT Technical Research Centre of Finland.

Espoo, the neighboring city of Helsinki, is already one of the partners of FCAI.

More information on the City of Helsinki website (in Finnish)

Finland Offers AI Training to Inmates

Photo: Matti Ahlgren / Aalto University

Photo: Matti Ahlgren / Aalto University

Finland has taken an important step in supporting artificial intelligence education of inmates. All inmates in Finnish prisons have now access to the Elements of AI online course, a widely popular introductory course on artificial intelligence.

The inmates can access the course by using prison workstations or test devices of the Smart Prison Project.

The Smart Prison Project is currently one of the most central projects of the Criminal Sanctions Agency. It aims to facilitate access to online services for inmates. The goal is that each inmate in Hämeenlinna women’s prison would get their own device to their prison cell.

The devices used for the project are currently tested at two prisons in cities of Hämeenlinna and Turku. Project manager Pia Puolakka recently visited Turku prison and met inmates testing the devices.

“The test group has around 10 people who have all received an individual device. A number of them displayed their interest in taking this course,” says Puolakka.

 

Free courses on timely topics help to tackle social problems

Earlier this year, the Criminal Sanctions Agency started collaboration with the technology company Vainu. In the project, Vainu offers inmates a chance to work by classifying data to train artificial intelligence algorithms.

“After we launched the Vainu project, we were thinking, how we can also support education and reskilling of the inmates concerning this timely topic. Then it crossed my mind that we could try this course out,” says Puolakka.

The Criminal Sanctions Agency believes that offering artificial intelligence training to inmates is important. Understanding artificial intelligence and how it can be applied becomes increasingly important in the future.

“This is an easy way to get familiar with the topic. I’ve even started doing the course myself. It provides a lot of useful information.”

Puolakka points out that, in terms of digitalization, people from different social backgrounds are often in unequal positions. She believes that courses like Elements of AI are one way of tackling these types of problems.

“The fact that universities offer free online courses that are easy to access and focus on timely topics, is excellent.”

The lead instructor of the Elements of AI, Associate Professor Teemu Roos from the University of Helsinki agrees. He finds it very important that the course is also available in prisons.

“Access to education is a human right and people in exceptional life situations need special attention. We have been working hard to reach out beyond the highly educated and tech-savvy audiences of typical online courses.”

 

Facilitating non-experts’ understanding of AI

The Elements of AI course has been designed to be easy to understand by non-experts. It requires no programming or complex mathematical skills. In addition to the basic principles of AI, the course focuses on societal implications, including threats to privacy and the changing work life.

“It doesn’t matter if you’re behind the bars, AI is affecting everyone’s life. There are also important ethical and political questions concerning the use of AI. What we are trying to do is support the public discourse by making the topic easier to understand by non-experts,” says Roos.

The free online course, Elements of AI, is organized by the Finnish Center for Artificial Intelligence FCAI and IT consultancy company Reaktor. FCAI is a nation-wide competence center for Artificial Intelligence in Finland, initiated by Aalto University, University of Helsinki, and VTT Technical Research Centre of Finland.

Launched in May 2018, Elements of AI soon became the most popular course ever offered by the University of Helsinki. Currently, the course that attendees can take in three languages – English, Finnish and Swedish – has 170,000 registered users. People from 110 countries have already completed the course.

FCAI brings its expertise to the development project of Finnish language resources

FCAI partner Vake Oy – a state-owned investment and development company in Finland –  launches its development program for Finnish artificial intelligence in May 2019. The first project aims to create Finnish language resources (application libraries, language models, and training materials) needed by developers of artificial intelligence devices and software requiring man-machine interaction in Finnish. The final goal is to develop components enabling the use of Finnish in artificial intelligence alongside the major languages of the world. The work begins with a preliminary study conducted by Vake Oy, the Department of Digital Humanities at the University of Helsinki, the FIN-CLARIN consortium, the Aalto University, Business Finland, and the Technology Industries of Finland to establish development priorities. FCAI contributes by bringing strong research expertise on new machine learning methods for language technologies.

Sound is a significant future interface. More than half of Google searches are estimated to be voice-controlled in 2020. The market research agency Canalys has estimated that there will be nearly 100 million smart speakers in households this year. International giants like Amazon, Apple and Google are selling millions of smart speakers a year, and the Russian Yandex and the Chinese e-commerce company Alibaba have developed smart speakers for their own language areas.

“In the market for voice-controlled devices and applications, developers naturally focus on the major languages to maximize the market potential of services. The ambitions of the current Finnish players are not limited to product development for our own small linguistic area, but companies need initial testing and references from the domestic market to succeed. Consumers will be excluded from these fast-growing services, unless we invest in Finnish resources,” says Development Director Tuomas Teuri from Vake.

Reference (only in Finnish): https://vake.fi/fitiedotteet/#150519

Nordic Five Tech establishes new network for artificial intelligence

The Nordic AI Network aims to make the Nordic region a global hub in AI research, education and innovation.

The Nordic AI Network will begin activities already this year. Photo: Maria Knutson Wedel/Chalmers University of Technology.

The Nordic AI Network will begin activities already this year. Photo: Maria Knutson Wedel/Chalmers University of Technology.

Today, the Nordic Five Tech alliance of leading technical universities in Denmark, Finland, Norway and Sweden announces the creation of the Nordic Artificial Intelligence Network. With global interest in the many opportunities of artificial intelligence (AI), the network will bring together, and harness, leading expertise in the field with the aim of taking the landmark step to make the region a global hub in AI research, education and innovation. 

The Nordic AI Network will begin activities already in 2019 with selected events. In coming years, it will share educational resources, stimulate research collaborations, as well as study and share best practices and business models for collaboration with industry. Its activities will, overall, set the stage to communicate Nordic excellence in the field of AI and obtain competitive funding at both the national and European levels. 

‘AI is set to change the world and the Nordics must be part of this tremendous shift. Bringing expertise from across our countries under one umbrella through the Nordic AI Network is a crucial step in making the Nordics a global hub in artificial intelligence. We are very pleased to launch the network and build up activities in coming months,’ says Ilkka Niemelä, President of Aalto University. 

‘The Nordic Five Tech alliance has very strong AI research groups. We are uniquely positioned to apply AI for the benefit of society both because it is a part of our mission as technical universities and due to our shared culture of collaborating with both the business community and public institutions. Together our alliance is stronger than the individual universities and we can share our best practices both in relation to research and education to the benefit of all in the Nordic region,’ says Anders O. Bjarklev, President of the Technical University of Denmark in Denmark. 

Made up of Aalto University, Chalmers University of Technology, the Technical University of Denmark (DTU), KTH Royal Institute of Technology and the Norwegian University of Science and Technology (NTNU), the Nordic Five Tech universities are each home to research institutes and centres dedicated to AI, like the Finnish Center for Artificial Intelligence.

The decision to create the Nordic AI Network was made at the meeting of Nordic Five Tech presidents on 26 April 2019. 

More information:
Ville Kyrki
Associate Professor, Intelligent machines
ville.kyrki@aalto.fi
tel: +358504082035

fcai team’s Award Winning Research At AISTATS 2019

Markus Heinonen receiving the prize

Markus Heinonen receiving the prize

A paper by an FCAI team, “Deep learning with differential Gaussian process flows” was awarded the 2019 Notable paper award at the 2019 AI & Statistics conference, one of only three papers to be awarded the honour out of a field of over one thousand submissions. The international congress, which took place over three days in Okinawa, Japan, was an opportunity for several hundred A.I. researchers from around the globe to get together and discuss their work, and FCAI researchers and students were there presenting talks and posters.

The prize winning paper was written by Pashupati Hegde, Markus Heinonen, Harri Lähdesmäki, and Samuel Kaski and came out of a collaboration between the research groups of Professor Lähdesmäki and Professor Kaski.

New methods for Deep Learning

In deep learning, hundreds of successive computations are combined together to learn very complex tasks. This how computers and phones now recognize faces in images or translate languages. In the new paper by the FCAI team, combining all the computations together is replaced with a continuous transforming flow of inputs, which are used to perform the learning task in way that’s easier to interpret. The work also presents a new connection between deep learning and a group of mathematical models called “stochastic dynamical systems”. This connection means that, compared to common neural networks, the new method can understand how much uncertainty there is in the prediction process. This understanding of uncertainty means the new method excels at learning models where there are smaller amounts of data – potentially useful for future applications like personalized medicine or drug design.

Researchers from FCAI also presented the following talks and posters:

Talks

  • Deep learning with differential Gaussian process flows

    • Pashupati Hegde,  Markus Heinonen, Harri Lähdesmäki, Samuel Kaski

  • Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning

    • Aapo Hyvärinen

Posters

  • Analysis of Network Lasso for Semi-Supervised Regression

    • Alexander Jung, Natalia Vesselinova,

  • Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution

    • Topi Paananen, Juho Piironen (Curious AI); Michael Andersen, Aki Vehtari  

  • Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features

    • Arno Solin  

  • Harmonizable mixture kernels with variational Fourier features

    • Zheyang Shen, Markus Heinonen, Samuel Kaski  

  • On Structure Priors for Learning Bayesian Networks

    • Jussi Viinikka, Aleksis Vuoksenmaa, Mikko Koivisto

  • Estimation of Non-Normalized Mixture Models

    • Takeru Matsuda, Aapo Hyvärinen