Professor Mark K. Smith, CEO of ContactEngine, discusses how artificial intelligence (AI) can lend itself towards sustainability Not a day goes by without a company, charity, government or some other gas-guzzling, forest-burning, ocean-destroying organisation making a grand claim about net-zero, carbon neutral or otherwise pledging to single-handedly save the planet by twenty-whenever. We'll get the brag out of the way quickly – ContactEngine is already carbon negative – but, following the noise around COP26, the threat of irreversible climate change provides a good reason to discuss sustainability in AI more generally. Cloud-based computing has rightly come under increased scrutiny in recent years for its energy use. Greenpeace estimates that by 2025, the tech sector could consume 20% of the world's electricity, a huge rise from its current 7%, and one that will be largely driven by cloud computing. As it stands, a lot of this energy use doesn't come from renewable sources, with nearly 4% of all CO2 emissions coming from data transfer and infrastructure – a figure 60% higher than aviation.

The dynamics of the global commercial artificial intelligence market continues to change over time, thanks to the persistent advancements in technology. This research report offers a detailed and insightful assessment of the global commercial artificial intelligence market, taking primary trends and the future prospects of this market in consideration. Various segments of this market, based on a number of parameters, have also been evaluated to gain a clear overview of the dynamics in the worldwide commercial artificial intelligence market. The global commercial artificial intelligence market demonstrates a highly fragmented and competitive business landscape. The leading companies in this market, including NVIDIA, Intel, IBM, Google, Microsoft, AWS, General Vision, GE, Siemens, and Mitsubishi Electric, are all competing on the basis of R&D, innovations, and new product launches.

This article is part of a VB special issue. Read the full series here: The metaverse - How close are we? Some companies believe that the metaverse -- a yet-to-be-realized, internet-like series of connected worlds -- has enormous potential in the enterprise. For example, it could be used to improve work productivity by allowing employees to train or collaborate in workplace-like virtual environments. Or it could host home and office tours, a boon for a real estate market contending with pandemic travel restrictions.

The conversation is on hold. The Edge community has hit the road... or they're staying home. Preparing for the academic year to begin, wrapping up projects and starting new ones, celebrating with family and friends or contemplating in solitude. After a hiatus, Edge is pleased to revive Summer Postcards: Edgies reporting in from wherever they are and on whatever they're doing, as the dog days wind out and the season comes to a close. As the world slowly returns to a "new normal" with enduring COVID restrictions in the midst of renewed vaccine freedoms, this year's collection is a testament to change (temporary and lasting), a consideration of loss (will travel ever be like it was?), and a celebration of questions (that still need answering). The hammock may be away until next year, but the memories remain. I spent the summer writing and revising the final section of a longish novel I started in 2019. It seems now as though I've been from 1946 to 2021 on my hands and knees. Various lockdowns have been a liberation from obligations and the luggage carousel, and I've never known such sweet and total focus for months on end. We have the luxury of living in the country--no shortage of big skies and moody walks. All our few breaks were in the UK--Scotland, the Lake District, the West country. Even in our remote part of the Lakes, I had to keep on writing--as in photo. The best novel I read this summer was Sandro Veronesi's The Hummingbird. Best non-fiction was Peter Godfrey Smith's Metazoa: Animal Life and the Birth of the Mind. I gave time also to some wonderful novellas--perfect fictional form for you too-busy scientists. IAN MCEWAN is a novelist whose works have earned him worldwide critical acclaim. He is the recipient of the Man Booker Prize for Amsterdam (1998), the National Book Critics' Circle Fiction Award, and the Los Angeles Times Prize for Fiction for Atonement (2003). His most recent novel is Machines Like Me. In 2019, Časlav Brukner and myself were walking on a beach on Lamma Island, near Hong Kong, marvelling together at the astonishing strangeness of quantum phenomena. This summer, the conversation with Časlav has continued on another island, and quite an island: Lesbos, the northern Greek island near the Turkish coast. Lesbos is the place where lyrical poetry was born. Here lived Sappho and Alcaeus.

Telegram was almost banned in Brazil because it missed some emails from the local authorities. In his newsletter, Newton explains why this is the latest in a series of troubling decisions from a platform with over 500 million users. "When you're providing critical communications infrastructure to tens of millions of people, though, you have more responsibility," he writes. Artificial intelligence is being used for all sorts of things in medicine, one of which is predicting if a patient is at risk for conditions like diabetes or cardiovascular issues. However, it can be difficult for us as members of the public to understand how these algorithms work.

The domain of Artificial Intelligence (AI) ethics is not new, with discussions going back at least 40 years. Teaching the principles and requirements of ethical AI to students is considered an essential part of this domain, with an increasing number of technical AI courses taught at several higher-education institutions around the globe including content related to ethics. By using Latent Dirichlet Allocation (LDA), a generative probabilistic topic model, this study uncovers topics in teaching ethics in AI courses and their trends related to where the courses are taught, by whom, and at what level of cognitive complexity and specificity according to Bloom’s taxonomy. In this exploratory study based on unsupervised machine learning, we analyzed a total of 166 courses: 116 from North American universities, 11 from Asia, 36 from Europe, and 10 from other regions. Based on this analysis, we were able to synthesize a model of teaching approaches, which we call BAG (Build, Assess, and Govern), that combines specific cognitive levels, course content topics, and disciplines affiliated with the department(s) in charge of the course. We critically assess the implications of this teaching paradigm and provide suggestions about how to move away from these practices. We challenge teaching practitioners and program coordinators to reflect on their usual procedures so that they may expand their methodology beyond the confines of stereotypical thought and traditional biases regarding what disciplines should teach and how. This article appears in the AI & Society track.

The National Center For Artificial Intelligence (Cenia) was established in 2021 as a core component of the Chile National Policy for AI. Cenia is the main institution dedicated to AI in Chile, with a mission to be at the forefront of scientific and technological innovation in this field. As a main leading guide, Cenia promotes sustainable and ethical progress, in harmony with the environment and human development.

The Kullback-Leibler divergence or relative entropy is an information-theoretic measure between statistical models that play an important role in measuring a distance between random variables. In the study of complex systems, random fields are mathematical structures that models the interaction between these variables by means of an inverse temperature parameter, responsible for controlling the spatial dependence structure along the field. In this paper, we derive closed-form expressions for the Kullback-Leibler divergence between two pairwise isotropic Gaussian-Markov random fields in both univariate and multivariate cases. The proposed equation allows the development of novel similarity measures in image processing and machine learning applications, such as image denoising and unsupervised metric learning.

Artificial intelligence (AI) is a cutting-edge computer science technology. It shares similarities with human intelligence in terms of language comprehension, reasoning, learning, problem solving. In the development and revision of technology, market manufacturers face enormous intellectual challenges during the forecast period. Furthermore, the expansion of the automotive industry is expected to drive the Automotive Artificial Intelligence Market during the forecast period. The automotive industry has recognized the potential of artificial intelligence and is one of the major industries that employs AI to augment and mimic human action which is the major factor driving the growth of Automotive Artificial Intelligence Market during the forecast period.

The Department of Innovation & Technology (InnoTech) under Druk Holding & Investments (DHI), the commercial arm of the Royal Government of Bhutan, has partnered with Omdena, a global collaborative platform that makes AI for good accessible to all. This partnership is a step further in DHI InnoTech's mission to strategize technology and innovation pathways to enhance access and diffusion of emerging technologies, and build local capacity in the fields of science and technology. Omdena will assist InnoTech in hosting a global 2-week hackathon wherein InnoTech will identify key themes and issues that can be resolved using innovative AI/ML applications. Omdena will work with 50 AI engineers over an additional 8-week challenge to develop the idea or POC selected from the hackathon into a fully deployable algorithm. The pilot InnoTech-Omdena event will serve as a showcase for local institutions and the general public who are interested in AI/ML.