Google has been researching on human brain and applying that knowledge on neuroscience which in turn makes it possible for computers to conducts tasks such as image recognition, language translation, speech recognition, natural language understanding and voice search engine. This tech has been applied on everyday apps such as Google Inbox which suggest quick replies to your email by using neural networks, Google Photos uses image recognition to recognize things such as hugs and pets in photos so you can search them more intuitively, and the Google app applies natural language processing to help you search for answers on the web using normal conversation language. Some of the experiments showcased in the event included Quick Draw which is a game that uses machine learning to know if you drew a given object in 20 seconds, AI Duet on the other hand is a system that lets you play a short tune using a piano and machine learning will convert it into a song and lastly Auto Draw, as the name suggest, the helps a user by automatically giving him or her a suggestion of what they could be drawing (like the way auto correct works), hence, they end up finishing their complete drawing much faster. According to Blaise Aguera ,Principal Scientist who leads a team at Google focusing on Machine Intelligence for mobile devices, “In the 20th century mankind thrived upon inventing machinery to improve productivity that saw the invention and renaissance of industries. However, in the 21st century the economy is going to grow through smart technology and artificial intelligence. This is a golden opportunity for young inventors to make their mark in history.” Tools are already available for researchers and developers to join in on Google’s open source machine learning project, Tensor Flow. Also, Cloud ML platform is already in place for interested individuals to create models that use this technology. Head up to those links and see if you could be part of the 21 Century economy growth catalysts as Blaise stated.

Google showcases their latest machine learning experiments on the Magic in the Machine forum - 3