An embodied AI system can actively perceive the world around them in order to gather information through sensors such as vision, process this information on different cognitive levels, both autonomously and in interaction with a human, and finally make plans or decisions based on the outcome. In the autonomous vehicle case, the internal processing consists of planning future driving actions in interaction with the surrounding world and possibly also with a driver.
Our Lead AI Scientist Hedvig Kjellström has been dedicating her academic career for researching the interface between humans and robots, observing how computer vision can help machines understand humans better in terms of what we say, how we gesture and how we move.
Hedvig Kjellström, Professor at KTH, is joining Silo AI Sweden as a Lead AI Scientist, with a focus on computer vision-driven solutions. Hedvig holds a PhD in Computer Science from KTH, with the topic of her doctoral thesis focusing on 3D reconstruction of human motion in video.
Within the past month, four Silo.AI employees completed their doctoral studies and received their PhDs. We’re celebrating the big milestone this Friday, and want to recognize their academic accomplishments with
With our CEO as one of the co-organizers, we were happy to be a part of the 5th Systemic Risk Analytics conference at the Bank of Finland, together with RiskLab
The conversation is past the point of whether or not artificial intelligence (AI) is impacting or is going to impact our everyday lives. That said, today the discussion still oftentimes
In our weekly research club we review a paper that covers some upcoming and interesting topic around AI, be it machine learning, natural language processing or computer vision related. This
At Silo.AI we have a weekly research club where we look into interesting techniques and methods within the fast-moving field of AI. Last week, I gave a presentation on Multi-agent Reinforcement
We’re happy to announce that our next Silo.AI Academy webinar, open to our community members and others working with the research or implementation of machine learning, will take place on
Artificial intelligence and its various techniques are booming everywhere on many different levels. As Google Trends for this hot topic skyrocket, we want to bring the human aspect back into
The story of Silo.AI has many beginnings, but one of the most foundational of all is the work we carried out, first with the European Central Bank (ECB), and later
Privacy is a big challenge when dealing with vast amounts of data, which is the basis of artificial intelligence. People whose data is being collected, treated and analysed are often
When an industry becomes more competitive, job applicants need to possess additional skills that help them to start smoothly at work and to be distinguished from candidates with similar qualifications
Some weeks ago the International Conference on Machine Learning (ICML2018) concluded. It is one of top 3 conferences in Machine Learning and Artificial Intelligence in the world. This year it
Finland’s TurkuNLP group has reached the highest aggregate ranking in the global natural language parsing Shared Task 2018, beating 25 other top universities and company research groups in performance. Filip Ginter, the head of TurkuNLP, is an AI scientist in Silo.AI’s NLP team.
Bayesian networks can be used to compute probabilities of causes given effects. Bayesian networks belong to a class of models called probabilistic graphical models. Probabilistic models are particularly good in handling uncertainty.
Managing AI projects poses a new set of challenges compared to, for instance, managing traditional software development projects. We examine some of these challenges.
From text-based news, we extract company and network-level signals that show when companies are at higher probability of stock price decline. Using the described methodology, we were able to show that companies which reached the maximum risk value in our risk model, during any given quarter is up to 13 percentage points more likely to have stock price decline one month later than the average company.
The era of information – We live in a time period characterized by the shift from traditional industries to an economy based on information technology. Thanks to this, companies are more aware every day of the value of the information they accumulate in a seemingly natural way.
The purpose of this article is to introduce the concept and explain it by giving examples of its implications for the artificial intelligence sector in line with Silo.AI’s work on the topic and GDPR compliance. And, most especially, to explain the ways to help prevent organisations leaving privacy to chance and encourage them to have it by design instead.