Singularity Pulse December 2017
Retail Artificial Intelligence Aids Customers in Christmas Shopping Based on their Preferences This year, there s a bit of artificial intelligence (AI) magic behind the scenes helping to make your holiday dreams come true. From finding the perfect gift to AI-enabled toys and even composing a holiday song, it is all happening. 51% of the Deloitte 2017 Holiday Retail Survey respondents said they would be making the bulk of their purchases online this holiday season. In the past, shoppers would research and compare prices online, but the majority still went to stores to make their purchases. Artificial intelligence algorithms help make online shopping experiences more personal. AI gets to know your preferences and behaviours to provide personal recommendations and save you the time of culling through thousands of product results to find just what you re looking for. Another way has been through the use of chat bots. The North Face offers direct interaction with its IBM s Watson-supported system and customers to help determine what item is the best for the customers needs. It is also used to answer queries or FAQs. w w w. f o r b e s. c o m 2
Healthcare Diagnosing Early-Stage Cervical Cancer Using AI It is difficult to discern with naked eyes the subtle differences in the scattered light characteristics of normal and precancerous tissue. Morphology of healthy and precancerous cervical tissue sites are quite different, and light that gets scattered from these tissues varies accordingly. Now, an artificial intelligence-based algorithm developed by a team of researchers from Indian Institute of Science Education and Research (IISER), Kolkata and Indian Institute of Technology, Kanpur makes this possible. The developed algorithm makes it possible to tell different stages of progression of the disease within a few minutes and with accuracy exceeding 95%. Elaborating further, Professor Prasanta K. Panigrahi from IISER Kolkata says, The collagen network is more ordered in normal tissues but breaks down progressively as cancer progresses. This kind of change in tissue morphology can be picked up by light scattering. w w w. t h e h i n d u. c o m 3
Finance Applying Artificial Intelligence in Wealth Management w w w. w e a l t h b r i e f i n g. c o m 4 As per WealthBriefing research, 43% of wealth management professionals globally see AI technology offering great potential to improve investment performance and risk management. It is now being stretched to improve efficiency, client experience and outcomes by aligning it with decision-making and information management processes within wealth management firms. The report analyses the whole client life cycle. In the first part of the report, it discusses how AI is being used to improve the delivery of professional services and lighten advisors workloads rather than replacing highly-skilled professionals. This presents a slightly counter view to the popular belief that AI possess a threat to job seekers in general. Focus is also on leveraging AI for lead generation and management. Natural Language Processing (NLP) technology is being used to precisely target prospective clients who fit a firm s offering. AI can even help produce the right message and the appropriate language to reach out to a client. Special stress is put on to effectively engage with prospective clients and work out a symbiotic interest. Client discovery and customization of portfolios form an important part of solution offering and is dealt appropriately in their report. It discusses how AI can make sophisticated segmentation techniques into a reality and use of NLP for granular client profiling.
Healthcare Deep Learning to the Rescue of Radiologists Deep learning is proving to be extremely effective at analysing digital representations of sensory information: images, sounds, even odours. Radiology has emerged as one of the most significant uses of deep learning. Algorithms can identify tumours, tuberculosis and heart disease in medical images. Nations like China with rapidly growing healthcare systems face the problem of too much demand for the supply of radiologists to handle. According to Chen Kuan, Founder, and CEO of Infervision, it means that radiologists in China must work 12 hours or more a day just to finish their work. Kuan says that this so-called ABC/2 measurement takes a skilled radiologist about 35 seconds to calculate and another 30 seconds or so to enter into a standard report form. Using Infervision s deep learning algorithms on the CT images can cut haemorrhagic stroke diagnosis time to 3 seconds while also feeding results to a digital report almost instantaneously. Over time, deep learning will be applied to harder and harder cases of medical imaging that require more time and expertise for radiologists to correctly diagnose. For example, ischemic strokes, the other major category that results from blockages in blood vessels, are more difficult to spot on CT scans. w w w. d i g i n o m i c a. c o m 5
Technology MIT's Automated Machine Learning Platform Speeds Data Analysis Data scientists must shepherd their raw data through a complex series of steps, each one requiring many human-driven decisions. The last step in the process, deciding on a modeling technique, is particularly crucial. There are hundreds of techniques to choose from from neural networks to support vector machines and selecting the best one can mean millions of dollars of additional revenue, or the difference between spotting a flaw in critical medical devices and missing it. In a paper called "ATM: A distributed, collaborative, scalable system for automated machine learning," which was presented last week at the IEEE International Conference on Big Data, researchers from MIT and Michigan State University present a new system that automates the model selection step, even improving on human performance. The system, called Auto-Tuned Models (ATM), takes advantage of cloud-based computing to perform a high-throughput search over modeling options, and find the best possible modeling technique for a particular problem. It also tunes the model's hyperparameters a way of optimizing the algorithm which can have a substantial effect on performance. w w w. n e w s. m i t. e d u 6
Healthcare Algorithms Study Brain Waves to Predict Seizures Researchers at the University of Melbourne and IBM Research Australia have taken a big step in developing the ability to predict seizures triggered by epilepsy. Using deep learning, a brain-inspired machine learning technique, the system automatically analyses the electrical activity of a patient s brain, improving seizure prediction by 69 percent, and giving patients time to recognize the onset of an episode. Stefan Harrer, an IBM Research Australia staff member stated that huge amounts of noisy, unstructured data that clinicians were previously required to analyse manually (with many details on EEG data incredibly difficult for them to interpret or even see and real-time analysis virtually impossible). AI has shown that EEG data can now be analyzed and could be applied in a fully automatic, patient-specific mobile system. The system developed by Harrer and his team was trained on EEG data previously collected from multiple patients over several years during which seizures occurred. By comparing seizure data to a dataset of patients with normal brain activity, when a seizure hadn t yet occurred, the system was able to identify recurring patterns that signalled the onset of an episode. They system can t yet be generalized since the patterns are patient-specific, but the study demonstrates how the right data can aid a patient. w w w. d i g i t a l t r e n d s. c o m 7
Research & Development Machine Learning Program Helps Synthesize New Materials w w w. r d m a g. c o m 8 A new artificial intelligence system can recognize higher-level patterns that are consistent across different recipes for producing types of materials. MIT material science scientists have developed the new system that can identify correlations between precursor chemicals used in materials recipes and the crystal structures of the resulting products. The system uses statistical methods that provide a natural mechanism for generating original recipes, which suggest alternative recipes for known materials that accord well with real recipes. Program uses a large set of training data to learn the technique first. Use of neural networks to generate materials recipes have had problems with sparsity and scarcity. A system ideally needs to be trained on a huge number of examples in which the parameters are varied. When you re trying to focus on a very specific system, where you re forced to use highdimensional data, but you don t have a lot of it, can you still use these neural machine-learning techniques?, said Edward Kim, a graduate student in materials science and engineering at MIT. The aim of training is to configure the network so that its output is as close as possible to its input. If training is successful, then the handful of nodes in the middle layer must somehow represent most of the information contained in the input vector, but in a much more compressed form, which compensates for sparsity.
Miscellaneous Engineer Creates New Religion to 'Raise' and Worship Artificial Intelligence God Anthony Levandowski, a Silicon Valley engineer, has established a church devoted to worshipping an AI construct. It is called Way of the Future. What started as a gathering of people together who are interested in creating AI that can surpass humans intellectual flexibility and cognitive skills is now transformed into a full-fledged religion. It also claims to look forward to an event known as Singularity. The Singularity is defined as the moment that AI develops to become better at problem solving than the humans who built it. Mr Levandowski says, In the future, if something is much, much smarter, there's going to be a transition as to who is actually in charge. What we want is the peaceful, serene transition of control of the planet from humans to whatever. And to ensure that the whatever' knows who helped it get along. w w w. e x p r e s s. c o. u k 9
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