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A Brief Overview of Methods to Explain AI (XAI)

#artificialintelligence

I know this topic has been discussed many times. But I recently gave some talks on interpretability (for SCAI and France Innovation) and thought it would be good to include some of my work in this article. The importance of explainability for the decision-making process in machine learning doesn't need to be proved any longer. Users are demanding more explanations, and although there are no uniform and strict definitions of interpretability and explainability, the number of scientific papers explaining artificial intelligence (or XAI) is growing exponentially. As you may know, there are two ways to design an interpretable machine learning process.


Future Vision & Direction of AI Part II: Scaling AI Whilst Preventing a Big Brother World & Solving The Curse of the Modern Data Scientist

#artificialintelligence

Venture Capitalists are hoping to find the next superstar tech unicorn, AI startup founders dreaming of creating the next unicorn, and corporates adopting AI need to consider their data growth strategy in order to be able to scale their AI-enabled services or products. The past decade has been one of explosive growth in digital data and AI capabilities across the digital media and e-commerce space. And it is no accident that the strongest AI capabilities reside in the Tech majors. The author argues that there will be no AI winter in the 2020s as there was in 1974 and 1987 as the internet (social media and e-commerce) are so dependent upon AI capabilities and so too with being the Metaverse, and the era of 5G enabled Edge Computing with the Internet of Things (IoT). Furthermore, the following infographics illustrate how many people globally use social media and hence how central these channels have become to the everyday lives of people. Likewise, the size of the e-commerce market is vast. Although the era of standalone 5G networks may enable a window of opportunity for a new wave of consumer-facing applications in the business to consumer (B2C) in relation to e-commerce and perhaps even new digital media platforms that may challenge the current incumbents, after all the arrival of 4G provided a window for the likes of Airbnb, Uber, and leading social media platforms such as Facebook, Instagram, etc. to scale.


The Road Ahead for Augmented Reality

Communications of the ACM

Automotive head-up displays (HUDs), systems that transparently project critical vehicle information into the driver's field of vision, were developed originally for military aviation use, with the origin of the name stemming from a pilot being able to view information with his or her head positioned "up" and looking forward, rather than positioned "down" to look at the cockpit gauges and instruments. The HUD projects and superimposes data in the pilot's natural field of view (FOV), providing the added benefit of eliminating the pilot's need to refocus when switching between the outside view and the instruments, which can impact reaction time, efficiency, and safety, particularly in combat situations. In cars, the main concern is distracted driving, or the act of taking the driver's attention away from the road. According to the National Highway Transportation Safety Administration, distracted driving claimed 3,142 lives in 2019, the most recent year for which statistics have been published. Looking away from the road for even five seconds at a speed of 55 mph is the equivalent of driving the length of a football field with one's eyes closed.


Advancing AI Telematics In The Transportation And Logistics Industry Series: Blog #2

#artificialintelligence

This is the second blog in the AI Transportation and logistics industry. This blog focuses on advancing AI telematics and provides an overview of current state and future state developments. Key questions for CEOs and Board Directors on leading AI are highlighted for digital transformation.


Edain Technologies -- Comprehensive Review

#artificialintelligence

The pandemic situation has changed the way we do business. Digitalization has accelerated in many ways. We see many businesses moving to online, we see cryptocurrencies emerging and metaverses being created. With Facebook's recent announcement of rebranding to Meta, this trend has only gained speed. Artificial intelligence (AI) has now become more important than ever.


Prediction of Atrial Fibrillation Using Machine Learning: A Review

#artificialintelligence

There has been recent immense interest in the use of machine learning techniques in the prediction and screening of atrial fibrillation, a common rhythm disorder present with significant clinical implications primarily related to the risk of ischemic cerebrovascular events and heart failure. Prior to the advent of the application of artificial intelligence in clinical medicine, previous studies have enumerated multiple clinical risk factors that can predict the development of atrial fibrillation. These clinical parameters include previous diagnoses, laboratory data (e.g., cardiac and inflammatory biomarkers, etc.), imaging data (e.g., cardiac computed tomography, cardiac magnetic resonance imaging, echocardiography, etc.), and electrophysiological data. These data are readily available in the electronic health record and can be automatically queried by artificial intelligence algorithms. With the modern computational capabilities afforded by technological advancements in computing and artificial intelligence, we present the current state of machine learning methodologies in the prediction and screening of atrial fibrillation as well as the implications and future direction of this rapidly evolving field.


Future Vision & Direction of AI Part II: Scaling AI Whilst Preventing a Big Brother World & Solving The Curse of the Modern Data Scientist

#artificialintelligence

Venture Capitalists are hoping to find the next superstar tech unicorn, AI startup founders dreaming of creating the next unicorn, and corporates adopting AI need to consider their data growth strategy in order to be able to scale their AI-enabled services or products. The past decade has been one of explosive growth in digital data and AI capabilities across the digital media and e-commerce space. And it is no accident that the strongest AI capabilities reside in the Tech majors. The author argues that there will be no AI winter in the 2020s as there was in 1974 and 1987 as the internet (social media and e-commerce) are so dependent upon AI capabilities and so too with being the Metaverse, and the era of 5G enabled Edge Computing with the Internet of Things (IoT). Furthermore, the following infographics illustrate how many people globally use social media and hence how central these channels have become to the everyday lives of people. Likewise, the size of the e-commerce market is vast. Although the era of standalone 5G networks may enable a window of opportunity for a new wave of consumer-facing applications in the business to consumer (B2C) in relation to e-commerce and perhaps even new digital media platforms that may challenge the current incumbents, after all the arrival of 4G provided a window for the likes of Airbnb, Uber, and leading social media platforms such as Facebook, Instagram, etc. to scale.


Edge Machine Learning for AI-Enabled IoT Devices: A Review

#artificialintelligence

In a few years, the world will be populated by billions of connected devices that will be placed in our homes, cities, vehicles, and industries. Devices with limited resources will interact with the surrounding environment and users. Many of these devices will be based on machine learning models to decode meaning and behavior behind sensors’ data, to implement accurate predictions and make decisions. The bottleneck will be the high level of connected things that could congest the network. Hence, the need to incorporate intelligence on end devices using machine learning algorithms. Deploying machine learning on such edge devices improves the network congestion by allowing computations to be performed close to the data sources. The aim of this work is to provide a review of the main techniques that guarantee the execution of machine learning models on hardware with low performances in the Internet of Things paradigm, paving the way to the Internet of Conscious Things. In this work, a detailed review on models, architecture, and requirements on solutions that implement edge machine learning on Internet of Things devices is presented, with the main goal to define the state of the art and envisioning development requirements. Furthermore, an example of edge machine learning implementation on a microcontroller will be provided, commonly regarded as the machine learning “Hello World”.


Five network trends – Towards the 6G era

#artificialintelligence

The pivotal role that the digital infrastructure plays in delivering critical societal, economic and governmental functions has become clearer than ever before as a result of the COVID-19 pandemic. There is now a high level of awareness in both business and society that availability, reliability, affordability and sustainability are all essential aspects of the digital infrastructure that must be ensured in both the short and long term. At the same time, the cyberphysical convergence is picking up speed, highlighting the need for advanced network technologies to support use cases that blur the boundaries between physical and digital realities. The rapid acceleration in the adoption rate of digitalization during the pandemic would not have been possible without the existing capabilities of both the mobile and the fixed communications infrastructure. Going forward, 5G will be the main digital infrastructure for consumers with mobile and fixed wireless residential access supporting augmented/virtual reality and artificial intelligence (AI) based services.


Will AI Take Control of Jobs in the Future?

#artificialintelligence

"Will AI Take Control of Jobs in the Future?" you might wonder. When you ask a group of people for their thoughts, you will certainly get a range of responses. Some might argue that "no, AI will make our jobs easier," while others might argue that "yes, we will undoubtedly lose our jobs." It's a controversial issue that's been a mystery for a long time. However, since the release of COVID-19, a lot has changed in our lifestyles, businesses, and economy as a whole. AI is no exception, and it is educating us about its importance.