Artificial Intelligence (AI), Machine Learning
As a foremost component of artificial intelligence (AI), machine learning is often based on artificial neural networks (ANNs), i.e., computational models inspired by biological neural networks. Such systems progressively and autonomously learn tasks by means of examples. They have successfully been applied to, e.g., speech recognition, text processing, and computer vision. An ANN comprises a set of connected units or nodes, which compare to biological neurons and are therefore called artificial neurons. Signals are transmitted along connections between the artificial neurons, similarly to synapses.
Many types of neural networks are known, starting with feedforward neural networks, such as multilayer perceptrons, deep neural networks, and convolutional neural networks. ANNs may possibly be implemented in hardware, e.g., as resistive processing units (crosspoint devices). However, the vast majority of implementations concern software implementations. In that respect, a recurring question is whether AI innovations are at all patentable. Computer programs are not patentable as such. However, can practical applications of AI be patented? The answer is yes, if the novel features of such inventions have technical character. This is a touchy point but, fortunately, European jurisdictions including Switzerland have a relatively clear legal framework in respect of such inventions. Our advisors, including our lawyers for legal advice in copyright in this arena, are: