In preparation for including an artificial intelligence (AI) system in Sensā one must first understand and grasp the concept of what is an AI.
Fortunately I had learned some concepts of machine learning and basic knowledge of AI in the university. But in order to build and AI system for Sensā I needed to acquire more knowledge first on what the platform is suppose to do and second on how to best achieve that goal.
Artificial intelligence is a computer program that is capable of executing tasks that usually humans can do like problem solving (playing chess,etc.), learn something faster, planning, etc… To sum it up is an area of computer science that aims to create intelligent machines.
The applications of AI are very diverse and go from finance, health, education, business intelligence, audio playlist, shopping, etc…
Now talking about the actual process of learning we have a new concept, machine learning. Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data.
Sensā is going to make use of a field in machine learning called deep learning. Deep learning uses multi-layer Deep Neural Networks (DNNs) to learn representations of data with many levels of abstraction that will make sense when recognising image, sound and text.
We have been accepted in Nvidia inception program that helps AI startups to progress in this area. They not only have a vast knowledge of deep learning and AI but also hardware capable of making all of that work much faster than traditional CPUs by using GPU architecture.
As for deep learning frameworks we decided to test a couple of them and see what best fits with our platform. We are going to test Caffe2 and TensorFlow because of the integration with mobile platforms, large community behind them and popularity within big companies.
Once we have something up and running, we will share it with you. Until then thanks for reading.
