Each one of us have experienced Artificial Intelligence (AI) in our daily lives- from customized Netflix recommendations to personalized Spotify playlists to voice assistants like Alexa – all of these show how integral AI-enabled systems have become a part of our lives.

On the business front, most organizations are heavily investing in AI/ML capabilities. Whether it is automation of critical business processes, building an omni-channel supply chain or empowering customer-facing teams with chatbots, AI based systems significantly reduce manual work and costs for businesses leading to higher profitability.

However, Machine-learning systems are only as good as the data the are trained upon. Many AI experts believe that AI should be trained not only on simple worst-case scenarios but also on historical events like the Great Depression of 1930s, the 2007-08 financial crisis and the current COVID-19 pandemic.

Today, as humans rely on AI, they cannot leave AI to function by itself without human oversight because machines do not possess a moral or social compass. AI is as good as the data it is trained upon, which, may reflect the bias and though process of its creators.

Read more at: https://www.lionbridge.com/blog/3-reasons-why-ai-needs-humans/

A Mass based digital agency Stone Temple collected 5,000 questions to ask both Google Home and Amazon Alexa and discovered that Google Home answered more than three times the amount of questions compared to Amazon Echo (3,383 versus 1,030). Out of all the queries Google Home answered, 2.3 % of the queries it answered were incorrect versus 6.3 % of the Amazon Echo device. So, Google Home seems to be the smarter device. With access to Google's repository, this is often hardly shocking. Amazon Alexa performed well, while apparently not counting on Google for its answers. Read more at: http://www.zdnet.com/article/google-home-versus-amazon-alexa-which-one-is-smarter/