Digest #2019.09.16 – The State of AI and ML
16 September 2019
- Machine Learning and AI in 2019: A recent survey conducted by Dresner Advisory Services shows Machine Learning and AI to rank as highest priority for enterprises. R&D, Marketing, Sales, Insurance, Fintech, Telco, Retail and Healthcare enterprise rank machine learning as their biggest bet and believe it is critical to their success. “2019 is a record year for enterprises’ interest in data science, AI, and machine learning features they perceive as the most needed to achieve their business strategies and goals.”
- Using Machine Learning in health-tech: With humans becoming increasingly health conscious and risk-averse, we’re seeing a boom in health-tech. Machine Learning is staying on top of the game here as well; researchers at MIT have invented a cardiovascular risk identifier. With heart disease being the most common cause of death in the world, the system called ‘CardioRisk’ uses a patient’s raw electrocardiogram (ECG). Using Machine Learning techniques the ECG is analysed against datasets and the system produces a risk score that places the patient in a relative risk category. “The intersection of machine learning and healthcare is replete with combinations like this — a compelling computer science problem with potential real-world impact.”
- Training on Large Images Using Spatial Partitioning on Cloud TPUs: The pain of training your Machine Learning models without enough space on a single chip can now be put to ease – You can now leverage a new spatial partitioning capability on cloud TPUs. This makes it possible to split up a single model across several TPU chips allowing processing of much larger input data sizes. Use this guide to learn how to configure spatial partitioning properly for your applications.