Implementing AI gives financial services firms numerous advantages
Machine Learning Digest is a curated weekly news overview for those who are concerned about the Machine Learning development across a spectrum of industries. It provides brief summaries and links to articles and news, describing the most remarkable events in the ML sphere. Learn about the latest news in machine learning development.
AI can be beneficial for financial services firms
Forbes on August 15, 2019
AI brought new opportunities to various spheres of human activity, and financial sector is no exception. Deloitte’s AI Leaders In Financial Services study sheds light on the ways financial services firms can benefit from AI forereaching their competitors. The analysis is performed on 1,100 interviews with leaders from US-based enterprises across different spheres currently implementing intelligent technologies.
Among the most outstanding insights, there are the following. 70% of all financial services firms involved in the research are already implementing machine learning, and 60% of the organizations are using Natural Language Processing (NLP). 60% of frontrunner financial services firms confirm that AI improves the revenue and 47% of firms say that AI positively affects customer experience. More than $5M are being invested in AI initiatives by 45% of AI frontrunner firms today. 65% of leading firms in financial services have major concerns when it comes to potential dangers and risks of AI.
Growing and regulating cannabis production with smart technologies
Forbes on September 8, 2019
While the cannabis industry is not a big adopter of new technologies, it is expected to face strong growth in the future and that is where AI can help it a lot.
According to the CEO and Director of CROP Corp, Michael Yorke, AI-based devices, such as AI in sensors and high-definition cameras can considerably ease the care about the plants by adjusting a number of inputs, such as water level, PH level, temperature, humidity, nutrient feed, light spectrum and CO2 levels. Tracking these parameters is essential for the improvements in growth and production of the plant. With the help of AI, it is possible to automate such processes as trimming and planting.
AI can identify the sex of the plants, detect sick plants, heal or remove sick plants from the environment, and track the plant growth rate to be able to predict size and yield. But even the smallest error can cost a cannabis business thousands, and incur harsh punishments such as losing their cannabis license,
Michael Yorke, the CEO and Director of CROP Corp.
Still, as there is still no legalization of the cannabis on a federal level in the US, there is a sharp need for special tracking systems.
Detecting pain level with AI among noncommunicative patients
MIT News on September 12, 2019
Smart technologies are widely used in healthcare and that is no surprise. As the world of medicine evolves, researchers have developed a system able to detect a patient’s pain level. The system analyzes brain activity of a patient with a help of a portable neuroimaging device. This is especially helpful when it comes to diagnosing and treating pain in unconscious and noncommunicative patients as the technology can reduce the risk of chronic pain after surgery.
Pain management and its accurate estimation is a of a great importance as overtreating pain puts a patient at risk of addiction to pain medication. Undertreated pain can end up in long-term chronic pain or other complications. While nowadays it is possible to gauge pain levels based to their patients’ own estimations of their feelings, it is sometimes challenging when it comes to people who can’t communicate effectively, for example, children, elderly patients with dementia, or patients undergoing surgery.
At the International Conference on Affective Computing and Intelligent Interaction, the researchers presented a paper describing a method to estimate pain in patients.
The way we measure pain hasn’t changed over the years. If we don’t have metrics for how much pain someone experiences, treating pain and running clinical trials becomes challenging. The motivation is to quantify pain in an objective manner that doesn’t require the cooperation of the patient, such as when a patient is unconscious during surgery.
Daniel Lopez-Martinez, a PhD student in the Harvard-MIT Program in Health Sciences and Technology and a researcher at the MIT Media Lab.