Information and communication technologies have contributed to the social and cognitive stimulation of children with autism spectrum disorder (ASD). This seems to be partly because children with ASD are more comfortable with predictive and repetitive behaviours [1], which can be implemented through algorithms. In particular, artificial intelligence algorithms are used in various fields, from language or gesture recognition to image classification [2]. These functions are convenient for a system to interact with a human being. Furthermore, robots seem to prove useful with autistic children because of simpler face expressions than those of human beings [3]. Robots can perform gesture imitation learning [4]. For a gesture to be recognized, the human body must first be correctly represented. Joint angles and joint positions can be used to represent human motion in spaces more suitable than the Euclidian one.

As the world adjusts to new ways of working and staying connected, we remain committed to providing Azure AI solutions to help organizations invent with purpose. Building on our vision to empower all developers to use AI to achieve more, today we're excited to announce expanded capabilities within Azure Cognitive Services, including:. Companies in healthcare, insurance, sustainable farming, and other fields continue to choose Azure AI to build and deploy AI applications to transform their businesses. According to IDC1, by 2022, 75 percent of enterprises will deploy AI-based solutions to improve operational efficiencies and deliver enhanced customer experiences. To meet this growing demand, today's product updates expand on existing language, vision, and speech capabilities in Azure Cognitive Services to help developers build mission-critical AI apps that enable richer insights, save time and reduce costs, and improve customer engagement.

Artificial Intelligence can be a Solution to unending unemployment. In today's society, it has become a difficult task to secure employment especially for those with minimum or no industry experience. Opportunities in the emerging technology can never be exhausted, as a positive tool it can be used to encourage the youths to pursue digital entrepreneurship. Youths can now define, create and manage their own ventures – be it to maintain and service the technology itself through digital start-ups, online kiosks or even innovation of better industry solutions. According to statistics from the International Labour Organisation, "the majority of youths regularly suffer from under-employment and lack decent working conditions. Of the 38.1 per cent estimated total working poor in sub-Saharan Africa, young people account for 23.5 per cent. Young girls tend to be more disadvantaged than young men in access to work and experience worse working conditions than their male counterpart, and employment in the informal economy or informal employment is the norm."

SAFR from RealNetworks, Inc., the world's premier facial recognition and computer vision platform for live video, announced the addition of Walter Candelu as Area Vice President for the Middle East. Mr. Candelu brings experience and leadership to the new SAFR office in Dubai. He will drive its growing sales and business development initiatives across the Middle East Region. Mr. Candelu will be based in Dubai, UAE and will focus on expanding the SAFR reseller channel, partner network, and regional sales and marketing programs. Prior to joining SAFR, he held senior positions with leading security companies where he successfully drove the exponential growth of their technical capabilities and revenue.

A network of fictional journalists, analysts, and political consultants has been used to place opinion pieces favorable to certain Gulf states in a range of media outlets, an investigation from The Daily Beast has revealed. At least 19 fake personas were used to author op-eds published in dozens of mainly conservative publications, with AI-generated headshots of would-be authors used to trick targets into believing the writers were real people. It's not the first time AI has been used in this way, though it's unusual to see machine learning tech deployed for online misinformation in the wild. Last year, a report from The Associated Press found a fake profile on LinkedIn, part of a network of likely spies trying to make connections with professional targets, that also used an AI-generated headshot. AI-generated profile pictures created by sites like ThisPersonDoesNotExist.com have some unique advantages when it comes to building fake online personas.

Global AI/Machine Learning market Size, Insights and Forecast 2020 to 2026 Latest Innovations & Application Analysis with the key players -GOOGLE, IBM, BAIDU, SOUNDHOUND, ZEBRA MEDICAL VISION, PRISMA, IRIS AI, PINTEREST, TRADEMARKVISION, DESCARTES LABS and Amazon, including Production, Price, Revenue, Cost, Application, Growth Rate, Import, Export, Capacity, Market Share and Technological Developments.The research report on AI/Machine Learning market provides a granular analysis of this business space and also assesses its various segmentations. Major aspects such as existing market size ad position in terms of volume and revenue estimations are detailed in the study.

The tremendous applications of human activity recognition are surging its span from health monitoring systems to virtual reality applications. Thus, the automatic recognition of daily life activities has become significant for numerous applications. In recent years, many datasets have been proposed to train the machine learning models for efficient monitoring and recognition of human daily living activities. However, the performance of machine learning models in activity recognition is crucially affected when there are incomplete activities in a dataset, i.e., having missing samples in dataset captures. Therefore, in this work, we propose a methodology for extrapolating the missing samples of a dataset to better recognize the human daily living activities. The proposed method efficiently pre-processes the data captures and utilizes the k-Nearest Neighbors (KNN) imputation technique to extrapolate the missing samples in dataset captures. The proposed methodology elegantly extrapolated a similar pattern of activities as they were in the real dataset.

In this work, we focus on an analogical reasoning task that contains rich compositional structures, Raven's Progressive Matrices (RPM). To discover compositional structures of the data, we propose the Scattering Compositional Learner (SCL), an architecture that composes neural networks in a sequence. Our SCL achieves state-of-the-art performance on two RPM datasets, with a 48.7% relative improvement on Balanced-RAVEN and 26.4% on PGM over the previous state-of-the-art. We additionally show that our model discovers compositional representations of objects' attributes (e.g., shape color, size), and their relationships (e.g., progression, union). We also find that the compositional representation makes the SCL significantly more robust to test-time domain shifts and greatly improves zero-shot generalization to previously unseen analogies.

This paper explores the important role of critical science, and in particular of post-colonial and decolonial theories, in understanding and shaping the ongoing advances in artificial intelligence. Artificial Intelligence (AI) is viewed as amongst the technological advances that will reshape modern societies and their relations. Whilst the design and deployment of systems that continually adapt holds the promise of far-reaching positive change, they simultaneously pose significant risks, especially to already vulnerable peoples. Values and power are central to this discussion. Decolonial theories use historical hindsight to explain patterns of power that shape our intellectual, political, economic, and social world. By embedding a decolonial critical approach within its technical practice, AI communities can develop foresight and tactics that can better align research and technology development with established ethical principles, centring vulnerable peoples who continue to bear the brunt of negative impacts of innovation and scientific progress. We highlight problematic applications that are instances of coloniality, and using a decolonial lens, submit three tactics that can form a decolonial field of artificial intelligence: creating a critical technical practice of AI, seeking reverse tutelage and reverse pedagogies, and the renewal of affective and political communities. The years ahead will usher in a wave of new scientific breakthroughs and technologies driven by AI research, making it incumbent upon AI communities to strengthen the social contract through ethical foresight and the multiplicity of intellectual perspectives available to us; ultimately supporting future technologies that enable greater well-being, with the goal of beneficence and justice for all.

The COVID-19 pandemic due to the SARS-CoV-2 coronavirus has directly impacted the public health and economy worldwide. To overcome this problem, countries have adopted different policies and non-pharmaceutical interventions for controlling the spread of the virus. This paper proposes the COVID-ABS, a new SEIR (Susceptible-Exposed-Infected-Recovered) agent-based model that aims to simulate the pandemic dynamics using a society of agents emulating people, business and government. Seven different scenarios of social distancing interventions were analyzed, with varying epidemiological and economic effects: (1) do nothing, (2) lockdown, (3) conditional lockdown, (4) vertical isolation, (5) partial isolation, (6) use of face masks, and (7) use of face masks together with 50% of adhesion to social isolation. In the impossibility of implementing scenarios with lockdown, which present the lowest number of deaths and highest impact on the economy, scenarios combining the use of face masks and partial isolation can be the more realistic for implementation in terms of social cooperation. The COVID-ABS model was implemented in Python programming language, with source code publicly available. The model can be easily extended to other societies by changing the input parameters, as well as allowing the creation of a multitude of other scenarios. Therefore, it is a useful tool to assist politicians and health authorities to plan their actions against the COVID-19 epidemic.