Today, a wide range of people and organizations worldwide (e.g. universities, companies, governments, etc.) actively use the public cloud. While there are dozens of public cloud vendors, three companies are currently the undisputed global market leaders: Amazon Web Services, Google Cloud and Microsoft Azure.
AI and Machine Learning are key areas of investment, growth and differentiation for many organizations and that is no exception for the three major public cloud vendors (AWS, GCP and Azure). In this context, pre-trained AI/ML API’s in combination with other Serverless services is one area that has been on the rise and with fast adoption.
News media websites are - and have been in the past years - in the epicenter of multiple society debates (e.g. fake news, public elections and geo-political influence, monetization and clickbait, etc.). Using simple software engineering techniques is fairly easy to periodically collect and extract metadata information from different news media websites (fake news or credible sources), and therefore allow us to gather interesting insights and draw some conclusions.
However, with AI/ML API’s at our disposal we could take this one step further. By leveraging those ready-made capabilities (e.g. Image Classification, Translation, Sentiment Analysis), we could enrich our metadata and gain valuable information and insights from the powerful pre-trained AWS AI/ML in a matter of milliseconds and without any kind the engineering or data science heavy lifting from our side.
What can AWS tell us about fake and credible news media websites?