Silo AI Content

The latest articles, webinars, podcasts and more for you to learn how you can benefit from artificial intelligence.
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Towards autonomous navigation, localization, and mapping

Autonomous navigation, localization, and mapping mean the ability of the autonomous system to create a map of the surrounding environment, localize the machine on that map and make the navigation planning accordingly. These features are crucial in the development of autonomous machinery, vehicles, and vessels, and are often enabled by techniques such as sensor fusion.

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Webinar recap: Silo AI x NVIDIA webinar – Situational awareness for vessels, Case: Groke Technologies

Groke Technologies is paving the way for autonomous navigation solutions in the marine industry. On June 2, 2021, we had the opportunity to learn about the future of the marine industry with Groke Technologies, a Finnish marine company. With the help of Silo AI experts and the use of NVIDIA’s products, Groke is utilizing sensor fusion technologies to achieve better situational awareness of a vessel’s surroundings.

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Physical AI Systems — AI with a body

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.

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MLOps is not a platform, it’s a human process assisted by platforms

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.

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Rolls of paper at Kemira

Kemira and Silo AI leverage machine learning to predict and prevent process disturbances and quality issues in paper and board production

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.

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Kai Knuutila joins Silo AI to empower industrial companies with edge AI

We’re excited to get Kai Knuutila join our team as a Lead AI Solutions Strategist. Kai is a long-term digitalization and technology professional, with experience in leading teams in multiple technology areas ranging from software, hardware, semiconductors to IoT, wearables and AI. With a solid work experience of 22+ years, of which 17 spent at two technology giants Intel and Nokia, Kai is an experienced senior technology strategist and advisor.

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AI Recommender Systems

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.

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