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Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence

arXiv.org Artificial Intelligence

Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.


Trustworthy AI: From Principles to Practices

arXiv.org Artificial Intelligence

Fast developing artificial intelligence (AI) technology has enabled various applied systems deployed in the real world, impacting people's everyday lives. However, many current AI systems were found vulnerable to imperceptible attacks, biased against underrepresented groups, lacking in user privacy protection, etc., which not only degrades user experience but erodes the society's trust in all AI systems. In this review, we strive to provide AI practitioners a comprehensive guide towards building trustworthy AI systems. We first introduce the theoretical framework of important aspects of AI trustworthiness, including robustness, generalization, explainability, transparency, reproducibility, fairness, privacy preservation, alignment with human values, and accountability. We then survey leading approaches in these aspects in the industry. To unify the current fragmented approaches towards trustworthy AI, we propose a systematic approach that considers the entire lifecycle of AI systems, ranging from data acquisition to model development, to development and deployment, finally to continuous monitoring and governance. In this framework, we offer concrete action items to practitioners and societal stakeholders (e.g., researchers and regulators) to improve AI trustworthiness. Finally, we identify key opportunities and challenges in the future development of trustworthy AI systems, where we identify the need for paradigm shift towards comprehensive trustworthy AI systems.


7 Great Examples of Artificial Intelligence in Daily Life

#artificialintelligence

The term Artificial Intelligence (AI) may conjure up images of futuristic robots and scenes from movies like The Matrix. While some highly sophisticated applications of AI still feel as though they belong to a distant future, Artificial Intelligence is in fact already all around us in daily life. Through AI technology, machines are trained to evaluate stimuli in an intentional and intelligent manner, adapt to it, and make decisions. And according to McKinsey & Company's 2020 global survey on the State of AI, over half of organizations are already using AI to facilitate at least one business function. In truth, the vast majority of us are already interacting with Artificial Intelligence every day.


Pervasive AI for IoT Applications: Resource-efficient Distributed Artificial Intelligence

arXiv.org Artificial Intelligence

Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems to robotics control and military surveillance. This is driven by the easier access to sensory data and the enormous scale of pervasive/ubiquitous devices that generate zettabytes (ZB) of real-time data streams. Designing accurate models using such data streams, to predict future insights and revolutionize the decision-taking process, inaugurates pervasive systems as a worthy paradigm for a better quality-of-life. The confluence of pervasive computing and artificial intelligence, Pervasive AI, expanded the role of ubiquitous IoT systems from mainly data collection to executing distributed computations with a promising alternative to centralized learning, presenting various challenges. In this context, a wise cooperation and resource scheduling should be envisaged among IoT devices (e.g., smartphones, smart vehicles) and infrastructure (e.g. edge nodes, and base stations) to avoid communication and computation overheads and ensure maximum performance. In this paper, we conduct a comprehensive survey of the recent techniques developed to overcome these resource challenges in pervasive AI systems. Specifically, we first present an overview of the pervasive computing, its architecture, and its intersection with artificial intelligence. We then review the background, applications and performance metrics of AI, particularly Deep Learning (DL) and online learning, running in a ubiquitous system. Next, we provide a deep literature review of communication-efficient techniques, from both algorithmic and system perspectives, of distributed inference, training and online learning tasks across the combination of IoT devices, edge devices and cloud servers. Finally, we discuss our future vision and research challenges.


Arlo Video Doorbell now takes commands from Google Assistant

Engadget

You no longer have to live in an Amazon-focused household for Arlo's Video Doorbell to make the most sense. Arlo has introduced Google Assistant support to deliver notifications and send commands. If you're worried about the ruckus outside, you can ask Google to "show me the front door" and get a video feed sent to a smart display like the Nest Hub Max. The Video Doorbell normally sells for $150. That's more than rivals like Ring's new starter doorbell, but it gives you the choice of both Alexa and Google Assistant.


A Survey on Edge Intelligence

arXiv.org Artificial Intelligence

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence. The aim of edge intelligence is to enhance the quality and speed of data processing and protect the privacy and security of the data. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this paper, we present a thorough and comprehensive survey on the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, namely edge caching, edge training, edge inference, and edge offloading, based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare and analyse the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, etc. This survey article provides a comprehensive introduction to edge intelligence and its application areas. In addition, we summarise the development of the emerging research field and the current state-of-the-art and discuss the important open issues and possible theoretical and technical solutions.


Google Nest Hub Max review: bigger, better and smarter display

The Guardian

Google's latest smart display is larger and can recognise your face for proactively showing you personalised information making it just that little bit smarter than competitors. The £219 Nest Hub Max is Google's second own-brand smart display and is essentially a super-sized version of the excellent original Home Hub (now renamed Nest Hub). But where the Nest Hub is a veritable bargain at £119 or frequently much less, the Nest Hub Max is a different proposition at a little under twice the price. A bigger screen is definitely better for viewing from across a room. The 10in 720p HD screen is bright, crisp enough at normal viewing distances and has Google's ambient EQ colour tone system so that photos on it look very much like printed photos, not displayed on an overly white and clinical LCD screen.


4K HDTV on sale, plus Google Home Hub, Nintendo Switch, Ring Video Doorbell Pro, and more for April 13

Mashable

To celebrate this day, why not get yourself an Audio-Technica LP120X-USB direct-drive analog turntable for $298.00 after applying SAVE100 coupon code at checkout. Normally retails for $398, so you're saving yourself 25% off. What makes this deal so great is that it comes with a Mackie MDB-USB stereo box, allowing you to get the sound you want. If this is the first time you've heard about Record Store Day, it's an annual event for independent record stores and music lovers that come together to spread the word and celebrate their unique culture. No problem, keep scrolling as we have gathered more deals from Amazon, Walmart, Home Depot, B&H Photo-Video, BuyDig, Dell Small Business, Best Buy, Macy's, Adorama, and BuyDig for Saturday, April 13: What are the best deals today?


Four people are allowing strangers to control their smart homes

Engadget

For the next seven weeks, anyone who's inclined can go to 205 Hudson Street in New York City and take over someone else's apartment. Smart devices like the kettles, lighting and speakers of four homes connect directly to laptops in the corner of an art gallery. Cameras are trained on bathrooms, kitchens and living areas. Visitors can sit down and become a human Alexa, playing music, eavesdropping on conversations through microphones and communicating with the inhabitants via text-to-speech. Each home -- three in Brooklyn, one in San Francisco -- will be "live" for two hours a day.


Ring finally has a doorbell cam for renters and apartment dwellers

PCWorld

Ring's latest video doorbell attaches to the peephole on a front door, making it suitable for renters or apartment residents who often cannot drill into the wall next to the door. Announced at CES, the Ring Door View Cam delivers live high-definition video with the same features as Ring's other doorbells. The battery-operated unit comes in two parts. The outside half is styled along the same lines as Ring's Video Doorbell Pro, although instead of one lens, there are two: The top one is the conventional peephole door viewer, so the old analog function is retained, and the one beneath it is the video camera. The indoor half has the viewing lens for the conventional peephole and is where the battery is installed.