The recent enlargements to new Member States are challenging steps forward in the development of the European Union (EU). Such developments, together with the achievement of a single market, require a new approach to the Knowledge economics. Nowadays, the concept of Knowledge as a source of economic development gains popularity, giving rise to the term “Knowledge Based Economies”. On the basis of the growing importance of the knowledge, it may be said that only those economies could compete internationally in near future who would develop and integrate the basic ingredients of Knowledge into their economic systems and models: research and development (R&D) activities, human capital, degree of openness to international trade and information and communication technologies (ICT) diffusion. Keeping in mind this view, the aim of the paper is to analyze clusters and distances existing among the EU’s member by using the Self-Organizing Map (SOM) artificial neural network methodology. The results seem to confirm the goodness of the underlying theoretical paradigm