What Algorithms Are and What You Should Know About Them This article is part one of “What Algorithms Are and What You Should Know About Them” by senior reacher Janne Kauttonen and RDI Communications Specialist… What Algorithms Are and What You Should Know About Them
As artificial intelligence continues to reshape the business landscape, companies face complex challenges in implementing AI effectively. Through its comprehensive analysis of over 70 European companies’ AI adoption journeys, the Finnish AI Region (FAIR) project reveals critical insights into current trends, challenges, and success factors in AI implementation. This article presents key findings from FAIR’s AI consultancy services, offering valuable perspectives on AI maturity levels, technical expertise requirements, and sector-specific applications across startups and established businesses.
This article is part two of “Opportunities and Pitfalls of Generative AI from an SME Perspective” by senior reacher Janne Kauttonen and RDI Communications Specialist Martti Asikainen, originally published in Finnish in Haaga-Helia University of Applied Sciences’ eSignals Pro.
This article is part one of “Opportunities and Pitfalls of Generative AI from an SME Perspective” by senior reacher Janne Kauttonen and RDI Communications Specialist Martti Asikainen, originally published in Finnish in Haaga-Helia University of Applied Sciences’ eSignals Pro.
Even with major advancements in artificial intelligence (AI), many companies find it hard to turn these innovations into real business benefits. A report by Boston Consulting Group (BCG) found that, out of over 1,000 companies surveyed worldwide, only 4% have developed strong AI capabilities across their operations and are consistently seeing significant value.
Efficiency, productivity, and artificial intelligence. Better processes and fewer errors. Currently, high expectations are placed on AI, but it’s still premature to suggest that it will replace human labor entirely.
Supercomputers are the backbone of modern technological advancements, powering everything from AI-driven innovations to groundbreaking scientific research. With their unmatched processing capabilities, they enable the analysis of vast data sets and solve problems that would take standard computers months to tackle.
The new AI regulation (AI Act), which came into effect in August 2024, aims to ensure the reliability of AI systems used within the EU and safeguard fundamental rights. This regulation adopts a risk-based approach, imposing obligations primarily on companies that provide high-risk AI systems.
We are thrilled to announce the release of the “Practical Guide to Building Generative AI Applications”, authored by M.Sc. Gintare Saali from the Helsinki XR Center.
Health stands as a cornerstone in the lives of individuals worldwide, with a significant portion of public sector funding dedicated to sustaining and improving health care systems. In an era marked by increasing complexity and challenges within the health care sector[1], the quest for innovative and effective management solutions has never been more critical[2]. This landscape is fraught with systemic issues that demand a thoughtful, data-driven approach to overhaul existing paradigms.
