Vladislav Nenchev is a Senior AI Engineer, specialized in natural language processing, mathematics, software development, and architectural design. Vladislav is a solid AI expert who comes with two decades of
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.
The largest private AI lab in the Nordics takes the next step on its growth path and extends to Finland’s third-largest city, Tampere! With several clients and several employees in the region, Silo AI strengthens its presence in the area that’s also home to many leading industrial companies.
Silo AI expands into industrial optimization by acquiring the business of the technology consulting company FINNOPT. The acquisition strengthens Silo AI’s ability to create value to its global clientele in Industry 4.0 and autonomous vehicles, among others.
Barbara Heikkinen joins Silo AI in Palo Alto to develop smart health and bring AI to life sciences and healthcare
Machine learning operations, MLOps, is the organizational practice for operationalizing AI and accelerating ML development in a sustainable way. Once you’ve validated a couple of AI use cases by pilots and proofs-of-concept, scaling the development and the use of AI in your organization will require both a solid machine learning infrastructure and an aligned way of operating.
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.
The future of the papermaking process is data-driven. This can already be seen today in the collaboration between Kemira, the global chemicals company serving customers in the pulp and paper industry, and Silo AI, the largest private AI lab in the Nordics. The two companies are today announcing their collaboration, which has already resulted in a predictive AI-driven solution taken into production in board and paper production.
Kemira is now using an explainable AI solution to predict and prevent issues with paper and board quality and paper machine runnability. Our AI experts built a machine learning-driven solution that provides real-time predictions to a status dashboard.
We at Silo AI have worked closely with our customers for the past three years to understand how AI can make a significant impact. There is no silver bullet, but we have identified four principles that set the foundation for a successful implementation of AI.
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