AI MUST READS — W44 2018, by City AI
Artificial Intelligence, Machine Learning and related fields are in a constant state of change. We want to inform but also encourage discussions on well presented topics we think are necessary in the context of putting AI into production. Every week we’re picking applied AI’s best articles plus adding a discussion starter
1. How Machine Learning Could Detect Medicare Fraud
How Machine Learning Could Detect Medicare Fraud
Machine learning could become a new weapon in the fight against Medicare fraud. Machine learning could become a useful…
In the U.S, Medicare fraud accounts for between $19 Billion to $65 Billion per year and a new, world’s first study, has revealed that the application of machine learning towards the deteticion of fraudlent medicare application could mean that the potential reclamation of these fraudlent claims could soon be a very real possibility.
One of the more interesting outcomes for this study is the fact that;
“ Surprisingly, researchers found that keeping the data set 90 percent normal and 10 percent fraudulent was the “sweet spot” for machine-learning algorithms tasked with identifying Medicare fraud.”
The study can be found here.
2. Alphabet’s DeepMind AI Algorithm Wins Protein-Folding Contest
Business Insider reported that DeepMind lost $366 million in 2017, and their spending on cutting-edge research shows no sign of slowing down. (Credit to article for this stat). Losses of this kind, and the ability to keep the funding at a similar level for the foreseeable future is a clear sign that advancements and research like this is only going to be achieveable by the huge technology companies like Google. Academics can only achieve so much, the achievements limited by the size and length of the grants that they recieve.
Whilst this achievement in its current state is more progress than milestone, the indicative nature of the potential future impact is arguably one of the bigger scientific/medical advancements of this year.