AI takes a deep diveRobotics is a prime area of development for the AI community so it’s no surprise that there are plenty of start-ups conducting research with the intention of taking the field further. Seattle company Olis Robotics caught the attention of GeekWire earlier this year with a solution designed to take robotics not just to the next level, but somewhere else entirely. According to CEO Don Pickering, “Olis Robotics’ innovation currently manifests in a plug-and-play controller loaded with our AI-driven software platform. The controller and our proprietary software can operate tethered robots on the ocean floor, satellite servicing robots using high-latency satellite links in space, or industrial robots cleaning up a dangerous chemical spill on land using 4G/5G networks. Our innovation will exponentially expand the role of robots to make an impact on human advancement and exploration.”
The smart money is on AIA recent study by Deloitte entitled AI Leaders In Financial Services, Common traits of Frontrunners in the Artificial Intelligence Race provides some good perspective on how AI is revolutionizing the Financial Services industry. The study reports key statistics that reflect the rapidly advancing use of AI technologies:
- Frontrunner financial services firms are achieving companywide revenue growth of 19% directly attributable to their AI initiatives, much greater than the 12% of follower firms achieve.
- 70% of firms participating in the study use machine learning in production environments today, and 60% are using Natural Language Processing (NLP).
- 60% of frontrunner financial services firms are defining AI success by improvements to revenue – 47% by improving customer experience.
- 49% of frontrunners have a comprehensive organizational strategy in place for AI adoption, which departments are expected to follow, giving them immediate scale and speed over rival firms.
- 45% of AI frontrunner firms are investing over $5M in AI initiatives today, 3X the level of starters or late adopters.
Machine learning goes wildNew AI software developed by researchers at the University of Oxford can recognize and track the faces of individual chimpanzees in their natural habitats. The software will allow researchers and wildlife conservationists to significantly cut back on time and resources spent analyzing video footage, according to a new paper. In Science Daily, Dan Schofield, researcher and DPhil student at Oxford University’s Primate Models Lab, School of Anthropology explained, “For species like chimpanzees, which have complex social lives and live for many years, getting snapshots of their behavior from short-term field research can only tell us so much. By harnessing the power of machine learning to unlock large video archives, it makes it feasible to measure behavior over the long term, for example observing how the social interactions of a group change over several generations.’ The computer vision model was trained using over 10 million images from Kyoto University’s Primate Research Institute (PRI) video archive of wild chimpanzees in Guinea, West Africa. The team at Oxford hopes the new software will help improve conservation efforts in areas where chimpanzees are endangered.
AI makes healthcare smarterSome important AI-related developments are happening in the healthcare industry, where a need for more timely and accurate disease identification, improved clinical decision support, and streamlined communication between physicians and their patients is driving a wealth of innovation. To illustrate how AI technology could revolutionize medical strategies, let’s look at how stroke is identified and treated. As the No. 5 cause of death and a leading cause of disability in the United States, there is significant interest in leveraging the latest technology for improved detection and care. Research teams are currently working on AI-driven tools that can automate identification of the type of stroke a patient has suffered, as well as the location of the clot or bleed. This can help specialists optimize decision-making around the appropriate treatment for a patient’s needs. Last year, The U.S. Food and Drug Administration approved an app called Contact developed by San Francisco-based startup Viz.AI. The app uses computer-aided triage software to search for large vessel occlusions in brain CTs, then sends a text message to a neurovascular specialist. The company markets this mobile health tool as a direct-to-intervention system.
What AI trends should we look for in 2020?
- Retail marketing. Rapid improvements in AI technology are driving increased adoption of AI-based customer service systems, which we can expect to be more prevalent in 2020 and beyond. Additionally, AI coupled with predictive analytics is set to help retailers identify buying trends and quickly launch automated campaigns that will inspire highly targeted customers to act. In-store experiences will become highly personalized as well, with computer vision (CV) solutions will bring the immersive “connected store” experience to life.
- Artificial Intelligence for IT operations (AIOps). Originally coined by Gartner in 2017, AIOps refers to the way data and information from an application environment are managed by an IT team using artificial intelligence. According to Gartner, “AIOps platforms enhance IT operations through greater insights by combining big data, machine learning and visualization. I&O leaders should initiate AIOps deployment to refine performance analysis today and augment to IT service management and automation over the next two to five years.”
- Autonomous Vehicles. This is a topic that’s taking up a lot of the spotlight when it comes to developments in AI. According to PwC predictions, 40% of mileage in Europe could be covered by autonomous vehicles by 2030. According to the US Department of Transportation, 63.3% of the $1,139 billion of goods shipped in 2017 were moved on roads. This makes road freight one of the largest emissions producers in the world. The benefits of self-driving cars and trucks are considerable in this light. They can drive for hours without losing concentration and can optimize fuel usage and routes to help improve energy and time management.