Webinars

In this webinar, we dived into the infrastructure and organizational requirements of getting real-time machine learning-driven insights and analytics, that help run your operations smoothly. With our invited guest Unity, we showed an example of how solid machine learning operations (MLOps) helps scale several machine learning products at once. Together with Kaisa Salakka from Unity Technologies, we learn about the value of being able to scale multiple ML products with confidence and how it is enabled by robust MLOps processes. After hearing about Kaisa's extensive experience in building and shipping ML products, we dive deeper into the best practices for MLOps with Jukka Remes from Silo AI, who has helped several global industry leaders build their operations around machine learning. The webinar is hosted by Teppo Kuisma, who has helped global industry leaders onboard AI with 20+ years of experience in digitalization and ICT. Based on Silo AI’s learnings from 100+ production-level AI projects, we’ll guide you through the best practices of operationalizing AI with scalable machine learning operations.

In this webinar, we focused on machine learning for predictive maintenance together with our invited guests, Hanna Grönqvist, Senior Data Scientist at Hiab, and Slawomir Nowaczyk, Professor in Machine Learning at the Halmstad University and a Lead AI Scientist at Silo AI. Hiab, part of Cargotec, is the leading provider of on-road load handling equipment. At Hiab, Hanna is leading the predictive maintenance initiatives, and she’ll be joining the webinar to speak about predictive maintenance at Hiab for smart and sustainable load handling. In addition, we have a pleasure to learn from Silo AI's Lead AI Scientist Slawomir Nowaczyk who has both academic and industry experience in building machine learning for predictive maintenance. Previously he has built autonomous monitoring capabilities for smart vehicles in collaboration with Volvo. Slawomir is a well-known researcher on the topic of machine learning and deep learning for predictive maintenance in Sweden. The webinar is hosted by Kai Knuutila, AI Solution Strategist at Silo AI, who previously led predictive maintenance projects at the global provider of glass processing technologies, Glaston.

Understanding the current situation is extremely valuable in many environments, ranging from manufacturing, managing operations to planning and executing complex logistics. Weather often plays a key role in forecasting the future outcomes of a planned process, but many other steps can be analyzed with computer vision too. The first part of the webinar will dive into improving situational awareness with computer vision. With concrete reference cases we will demonstrate the value of computer vision in getting insights about how many vehicles are present at a certain location, how many parcels have passed by and are waiting to be treated, as well as how many cargo ships are currently at a certain port. In the second part, Svante Henriksson from Hurricane Unwinder, a company lead by former Finnish Meteorological Institute researchers, teach how to revolutionize the way tropical cyclones are being tracked. Together with Hurricane Unwinder, we’ve built a computer vision solution that predicts tropical cyclones in the coastal areas of the Atlantic, the Pacific and the Indian Ocean and forecasts the hurricane intensity. The solution won the ESA’s Earth observation award Copernicus Masters in 2018. – Traditional numerical weather forecasts are not able to forecast the intensity of the storm at the same level of detail as satellite images do. There is no existing computer-vision-based product to predict intensity changes, although scientific research supports the approach. With the help of Silo AI, we’ve been able to create the world’s first forecasting solution with world-class accuracy, says Svante Henriksson, CEO of Hurricane Unwinder.