With the exponential growth of computing power, greater availability of data, advances in smart AI algorithms and more synergy between different disciplines, Artificial Intelligence (AI) has gone into overdrive. Artificial Intelligence is playing an increasingly important role in solving social and economic issues and is increasingly a determining factor in terms of our prosperity and well-being. It is a multidisciplinary field that impacts all business sectors, as well as our private lives and society. AI has many forms and applications: from facial recognition to translation apps, from fighting fraud to making better medical diagnoses or personalised treatment plans. AI applications are also already being used for pesticide use reduction, energy conservation, personalised education, cheaper maintenance of roads, railways and bridges, and self-driving cars, robots and drones. AI additionally influences what we buy, watch or read. And that's just the beginning. AI will soon be everywhere.
Different learning strategies
AI aims to realise behaviour by machines that resembles natural intelligence. A learning strategy in artificial intelligence (AI) refers to the methods and techniques used to train or teach an AI system. There are different learning strategies, depending on the type of AI algorithm and the specific learning objective:
- Supervised machine learning
This is when an algorithm is able to classify based on certain features or patterns or make predictions based on a test dataset and associated labels. - Unsupervised learning
This is when an algorithm categorises without using existing labels. - Reinforcement learning
This is when an algorithm learns about the best strategy based on interaction with the environment. - Deep Learning
This strategy is often used to solve more complex and abstract problems. It is a subcategory of Machine Learning, which focuses on building and training deep neural networks.
Increasingly, hybrid forms are being developed for AI, in which humans and AI work together.
Becoming and remaining a leading player
Although the Netherlands has a strong competitive position when it comes to AI, the rest of the world is certainly not standing still. Indeed, in economies around us, the large-scale development and deployment of AI is being strongly encouraged by governments. To avoid missing opportunities, preserve our autonomy and not saddle society with technology that does not serve our interests, it is important that we continue to invest in AI talent, research and innovation. This is the only way to maintain and further strengthen our strong competitive position. To this end, an integrated approach is required, with intensive government involvement. For this reason, the Dutch AI Coalition (NL AIC) was set up in 2019 as one of the coalitions under the umbrella of Digital Holland (formerly Top Sector ICT)
By fostering cooperation and co-creation among various stakeholders and promoting research and innovation, the NL AIC plays an important role in promoting the development and application of AI in the Netherlands. Together, companies, knowledge institutions, governments and civil society organisations are shaping the Netherlands' AI agenda and driving European cooperation. It thus offers a response to the plans of AI giants like China and the US, while respecting Dutch and European norms and values. The aim is to achieve impactful AI innovations in at least 10 economic and social sectors within three years. A multi-year AiNed programme has been drawn up - a national growth fund investment programme that will run until 2027.
Action Agenda
Under the coordination of Digital Holland — and in close consultation with coalitions and representatives from the field — work is underway on the AI/Data Action Agenda, which stems from the National Technology Strategy (NTS).