At Google, we list AI projects we don’t do’

At Google, there are thousands of projects, supported by machine learning. They are impacting so many products from Gmail, Smart Reply, autonomous driving, Google Assistant to cloud AI functions. Google has been pushing forward a few core aspects related to AI. The first is data, it is so important to AI development. Google’s mission [has been] to organise the world’s knowledge. So, we have learned a lot of experience from data, but we’re also sharing a lot with the community and the researchers. Google Cloud has a public beta programme where we are sharing a very large scale of data, including YouTube with millions of datasets, videos shared free with the AI community. Also, there is Genomics Public Datasets, as well as Open Images Dataset. So, we’re not only keeping it to ourselves.

Right now, doctors and nurses in the hospital have to make runs every day in order to take care of the patients. But AI technology and machines don’t sleep. Also, how do we make the healthcare system more efficient? For example, genomic analysis, disease prediction, as well as pharmaceutical drug discovery, takes years. How do we leverage AI technology to accelerate that? Recently, we have been collaborating [with an organisation] to improve their genomics prediction approach from weeks to one day.

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