Machine learning is a hot issue in this age of artificial intelligence. Nobody could have predicted that computer vision and predictive analytics would break new ground. Face recognition on smartphones, language translation software, and self-driving cars are all examples of how we are increasingly seeing both of them in our daily lives. What may appear to be science fiction is becoming a reality, and it is only a matter of time before we achieve Artificial General Intelligence. Machine Learning Course in Chennai at FITA Academy provides the best practical sessions to develop your skills technically.

Ever felt bored when you are all alone? Had a thought of talking to someone who could give you witty replies? If that is the case why not train one to be? I mean a deep learning model. Yes, since the past half-decade deep learning has grown humongously powerful with evolution of state-of-the-art architectures and algorithms that were brought up into the limelight as part of tons of research that's happening around the world.

The hype machine is cranked up to an 11 on the topic of machine learning (sometimes called artificial intelligence, though I don't call it that because AI is not really intelligence and there's nothing artificial about it). Machine learning will either empower the world or take it over, depending on what you read. But before you get swept away by the gust of hot air coming from the technology industry, it's important to pause in order to put things into perspective. Maybe just explaining it in reasonable terms will help. Shortly after the first caveman figured out how to make fire, the second caveman wanted to learn how to make fire, too.

Many aspects can be taken into account in order to assess the power and potential of a cognitive architecture. In this paper we argue that ConsScale, a cognitive scale inspired on the development of consciousness, can be used to characterize and evaluate cognitive architectures from the point of view of the effective integration of their cognitive functionalities. Additionally, a graphical characterization of the cognitive power of artificial agents is proposed as a helpful tool for the analysis and comparison of Machine Consciousness implementations. This is illustrated with the application of the scale to a particular problem domain in the context of video game synthetic bots.