Goto

Collaborating Authors

Virtual Reality: Overviews


Artificial intelligence in medicine and healthcare: a review and classification of current and near-future applications and their ethical and social Impact

arXiv.org Artificial Intelligence

This paper provides an overview of the current and near-future applications of Artificial Intelligence (AI) in Medicine and Health Care and presents a classification according to their ethical and societal aspects, potential benefits and pitfalls, and issues that can be considered controversial and are not deeply discussed in the literature. This work is based on an analysis of the state of the art of research and technology, including existing software, personal monitoring devices, genetic tests and editing tools, personalized digital models, online platforms, augmented reality devices, and surgical and companion robotics. Motivated by our review, we present and describe the notion of 'extended personalized medicine', we then review existing applications of AI in medicine and healthcare and explore the public perception of medical AI systems, and how they show, simultaneously, extraordinary opportunities and drawbacks that even question fundamental medical concepts. Many of these topics coincide with urgent priorities recently defined by the World Health Organization for the coming decade. In addition, we study the transformations of the roles of doctors and patients in an age of ubiquitous information, identify the risk of a division of Medicine into 'fake-based', 'patient-generated', and 'scientifically tailored', and draw the attention of some aspects that need further thorough analysis and public debate.


A Review of Another 5 Major Tech Trends In 2020

#artificialintelligence

In our recent blog, we covered some exciting tech trends hitting 2020 such as autonomous driving, hyperautomation and more. There are many areas however with even more developments, ones you may have heard of and ones that you may have not. Technology is accelerating at such a rapid pace that every industry will be affected as well as the everyday consumer. We examine a further 5 top tech trends hitting our doors in 2020. At this stage, we all know or have at least heard of the cloud.


AI & New Retail: Recent Developments and Future Trends

#artificialintelligence

The traditional retail industry is facing challenges as the rapid development and continuous improvement of AI tools and techniques ushers in the era of New Retail. Many once-successful brick and mortar shops are at risk of disappearing altogether if they fail to adapt to the changing marketplace. As the concept of "New Retail" spreads globally, many Fortune Global 500 retail companies are implementing AI technologies such as computer vision and NLP in unmanned stores and warehouses or virtual stores, and are accelerating supply chain upgrades to better position themselves for the future of shopping. Global Retail Industry Market Size The steady growth of the global economy and per capita disposable income have triggered a surge in the retail industry over the past few years. The global retail industry market was valued at nearly US $23.5 trillion in 2017, a 5.3 percent year-on increase.


AI & New Retail: Recent Developments and Future Trends

#artificialintelligence

The traditional retail industry is facing challenges as the rapid development and continuous improvement of AI tools and techniques ushers in the era of New Retail. Many once-successful brick and mortar shops are at risk of disappearing altogether if they fail to adapt to the changing marketplace. As the concept of "New Retail" spreads globally, many Fortune Global 500 retail companies are implementing AI technologies such as computer vision and NLP in unmanned stores and warehouses or virtual stores, and are accelerating supply chain upgrades to better position themselves for the future of shopping. Global Retail Industry Market Size The steady growth of the global economy and per capita disposable income have triggered a surge in the retail industry over the past few years. The global retail industry market was valued at nearly US $23.5 trillion in 2017, a 5.3 percent year-on increase.


Currents Trends in IT

#artificialintelligence

Given that we are currently in the age of digital transformation, technological trends stand out among all others. The digital mesh will consist of automated devices, robots, humans, services and content, all driven by disruptive technological trends. We are here to discuss the top trends of IT in 2019 that are going to shape the future of business operations for the rest of the year. Artificial intelligence (AI) essentially involves harnessing the power of algorithms and machine learning to teach machines to identify, comprehend and mimic human behavior. Though it has been around for quite some time, this year we have witnessed AI combined with machine learning (ML) entering into the business platform to enable smart business operations.


OpenEDS: Open Eye Dataset

arXiv.org Machine Learning

We present a large scale data set, OpenEDS: Open Eye Dataset, of eye-images captured using a virtual-reality (VR) head mounted display mounted with two synchronized eyefacing cameras at a frame rate of 200 Hz under controlled illumination. This dataset is compiled from video capture of the eye-region collected from 152 individual participants and is divided into four subsets: (i) 12,759 images with pixel-level annotations for key eye-regions: iris, pupil and sclera (ii) 252,690 unlabelled eye-images, (iii) 91,200 frames from randomly selected video sequence of 1.5 seconds in duration and (iv) 143 pairs of left and right point cloud data compiled from corneal topography of eye regions collected from a subset, 143 out of 152, participants in the study. A baseline experiment has been evaluated on OpenEDS for the task of semantic segmentation of pupil, iris, sclera and background, with the mean intersectionover-union (mIoU) of 98.3 %. We anticipate that OpenEDS will create opportunities to researchers in the eye tracking community and the broader machine learning and computer vision community to advance the state of eye-tracking for VR applications. The dataset is available for download upon request at https://research.fb.com/programs/openeds-challenge


Augmented Utilitarianism for AGI Safety

arXiv.org Artificial Intelligence

In the light of ongoing progresses of research on artificial intelligent systems exhibiting a steadily increasing problem-solving ability, the identification of practicable solutions to the value alignment problem in AGI Safety is becoming a matter of urgency. In this context, one preeminent challenge that has been addressed by multiple researchers is the adequate formulation of utility functions or equivalents reliably capturing human ethical conceptions. However, the specification of suitable utility functions harbors the risk of "perverse instantiation" for which no final consensus on responsible proactive countermeasures has been achieved so far. Amidst this background, we propose a novel socio-technological ethical framework denoted Augmented Utilitarianism which directly alleviates the perverse instantiation problem. We elaborate on how augmented by AI and more generally science and technology, it might allow a society to craft and update ethical utility functions while jointly undergoing a dynamical ethical enhancement. Further, we elucidate the need to consider embodied simulations in the design of utility functions for AGIs aligned with human values. Finally, we discuss future prospects regarding the usage of the presented scientifically grounded ethical framework and mention possible challenges.


Improving Route Choice Models by Incorporating Contextual Factors via Knowledge Distillation

arXiv.org Artificial Intelligence

Route Choice Models predict the route choices of travelers traversing an urban area. Most of the route choice models link route characteristics of alternative routes to those chosen by the drivers. The models play an important role in prediction of traffic levels on different routes and thus assist in development of efficient traffic management strategies that result in minimizing traffic delay and maximizing effective utilization of transport system. High fidelity route choice models are required to predict traffic levels with higher accuracy. Existing route choice models do not take into account dynamic contextual conditions such as the occurrence of an accident, the socio-cultural and economic background of drivers, other human behaviors, the dynamic personal risk level, etc. As a result, they can only make predictions at an aggregate level and for a fixed set of contextual factors. For higher fidelity, it is highly desirable to use a model that captures significance of subjective or contextual factors in route choice. This paper presents a novel approach for developing high-fidelity route choice models with increased predictive power by augmenting existing aggregate level baseline models with information on drivers' responses to contextual factors obtained from Stated Choice Experiments carried out in an Immersive Virtual Environment through the use of knowledge distillation.


VRKitchen: an Interactive 3D Virtual Environment for Task-oriented Learning

arXiv.org Artificial Intelligence

One of the main challenges of advancing task-oriented learning such as visual task planning and reinforcement learning is the lack of realistic and standardized environments for training and testing AI agents. Previously, researchers often relied on ad-hoc lab environments. There have been recent advances in virtual systems built with 3D physics engines and photo-realistic rendering for indoor and outdoor environments, but the embodied agents in those systems can only conduct simple interactions with the world (e.g., walking around, moving objects, etc.). Most of the existing systems also do not allow human participation in their simulated environments. In this work, we design and implement a virtual reality (VR) system, VRKitchen, with integrated functions which i) enable embodied agents powered by modern AI methods (e.g., planning, reinforcement learning, etc.) to perform complex tasks involving a wide range of fine-grained object manipulations in a realistic environment, and ii) allow human teachers to perform demonstrations to train agents (i.e., learning from demonstration). We also provide standardized evaluation benchmarks and data collection tools to facilitate a broad use in research on task-oriented learning and beyond.


The Industrial Internet of Things: A guide to deployments, vendors and platforms

ZDNet

Technologies such as 5G, IoT sensors and platforms, edge computing, AI and analytics, robotics, blockchain, additive manufacturing and virtual/augmented reality are coalescing into a fertile environment for the Industrial Internet of Things (IIoT), which is set to usher in what's often described as the Fourth Industrial Revolution or Industry 4.0. Here's how analyst firm IoT Analytics sees the relationship between the broader IoT and the IIoT/Industry 4.0 sector: This ebook, based on the latest ZDNet / TechRepublic special feature, explores how infrastructure around the world is being linked together via sensors, machine learning and analytics. In this brave new world, supply chains will have end-to-end transparency thanks to sensors, data networks and analytics capabilities at key points. All other things (trade barriers, for example) being equal, parts and raw materials will arrive just in time at highly automated factories, and the fate of the resulting products will be tracked throughout their lifetimes to eventual recycling. Similarly, 'smart farms' will combine emerging IIoT-related technologies into integrated high-resolution crop production systems based on robotics, big data and analytics.