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Researchers Build AI That Builds AI

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A hypernetwork aims to find the best deep neural network architecture to solve a given task. Boris Knyazev of the University of Guelph in Ontario and his colleagues have designed and trained a "hypernetwork" that could speed up the training of neural networks. Given a new, untrained deep neural network designed for some task, the hypernetwork predicts the parameters for the new network in fractions of a second, and in theory could make training unnecessary. The work may also have deeper theoretical implications. The name outlines the approach.


Senior Machine Learning Engineer (Matching)

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Beat is the fastest growing ride hailing app in Latin America and a part of the international FreeNow Group, the multi-service mobility joint venture backed by BMW Group and Daimler AG. One city at a time, we are on a mission to develop seamless mobility for a safe and sustainable urban life. We are proud to say we have launched Beat Tesla / Loonshot, the first and largest private all-electric vehicle service in Latin America. As an organization, we are committed to our drivers with ethical practices and a safe working environment. To our customers, we differentiate ourselves from other ride-hailing apps with our super user-friendly app and excellent customer service.


Artificial Intelligence Can Help Leaders Drive Global Economy Forward In 2022

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Significant hurdles leaders face this year include managing talent, formulating strategies, operational plans, and organizing employee tasks in ways that ensure everyone accesses growth opportunities. These challenges emphasize the importance of good strategy, and are essential for organizational survival. Vijay Pereira, Professor and head of department of people and organizations, at NEOMA Business School in France, believes artificial intelligence (AI) can help leaders undertake these challenges. For example, his recent work concludes that evolutionary computation and data mining can explore large databases or social media to locate potential talented individuals for recruitment purposes. In addition, machine learning helps reanalyze and recognize patterns from data collected from existing decision support systems to help organizations improve their strategic planning processes.


Knowledge, society and artificial intelligence in the media

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All human actions are based on anticipated futures. We cannot know the future because it does not exist yet, but we can use our current knowledge to imagine the future and make them happen. The better we understand the present and the history that has created it, the better we can understand the possibilities of the future. To appreciate the opportunities and challenges that artificial intelligence (AI) creates, we need both a good understanding of what AI is today and what the future may bring when AI is widely used in society. AI can enable new ways of learning, teaching, and education, and it may also change society in ways that pose new challenges for educational institutions.


US Machine Learning in Finance Market 2022- New study Report 2026 – Daily Research Sheets

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The Global Machine Learning in Finance Market report provides information about the Global industry, including valuable facts and figures. This research study explores the Global Market in detail such as industry chain structures, raw material suppliers, with manufacturing The Machine Learning in Finance Sales market examines the primary segments of the scale of the market. This intelligent study provides historical data from 2015 alongside a forecast from 2022 to 2026. Results of the recent scientific undertakings towards the development of new Machine Learning in Finance products have been studied. Nevertheless, the factors affecting the leading industry players to adopt synthetic sourcing of the market products have also been studied in this statistical surveying report.


How banks and fintech are using artificial intelligence to deliver loans - The Goa Sportlight

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Financial technology services are increasingly large and diverse, not only representing a change for users, but also for banks that have had to adapt as new developments allow greater knowledge of the market and customers. Faced with this situation, they have launched in Colombia a platform that will use advanced artificial intelligence functions to generate a credit score for each person and allow financial institutions to identify potential clients. The new system is developed by the fintech Yabx which specializes in enabling credit for unbanked sectors, so thanks to an alliance it will base its data on Telecom's Telecommunications system in association with Claro, therefore It will allow the identification of new clients not recognized by the criteria of traditional banking. The platform will use machine-learning algorithms (artificial intelligence machine learning) to provide a credit score and other products that can be offered to banks or other fintech companies that want to improve their abilities to acquire and qualify customers whose applications to banks traditional are rejected. Thanks to the association with Claro, one of the largest telecommunications networks in the country, the new system will be able to cover around 67% of Colombian adults, in addition, it will allow credit institutions to reduce their rejection rates by up to 40% by take into account factors that are not normally observed.


Can Algorithms be Racist?

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As artificial intelligence (A.I.) continues to rapidly integrate within everyday life, there are a few ethical dilemmas that have arisen synchronously and their impact on use cases have become the subject of much debate (Kilbertus et al., 2017; Hardt et al., 2016; Pazzanese, 2020). One such predicament that this paper hinges on has to do with inclusivity and marginalization (Bender et al., 2021). How are notions of participation affected by training data that reinforce hegemonic power in the formation of algorithmic models? Accordingly, this article will seek to spotlight ethical challenges within A.I. via a grounded interpretivist viewpoint gained by qualitatively investigating the literature in order to discuss bias amplifications. As outlined by Bender et al., (2021), there are several juristic and social dilemmas regarding the growth and utilization of language models.


How Do AI Represent the Urban?

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It's important to remember that these images aren't created from scratch. They're built from "training sets" of images that human researchers feed into the AI to help it learn and recognise patterns. If you're not familiar with how such AI apps work, this old article from 2015 does a pretty good job of explaining this. I suspect that while the process has become more sophisticated over the years, the basic principle of recursively feeding images back into neural nets until the AI "gets it" hasn't changed. Therefore, human biases do exist in the patterns chosen and images generated, which turns these images into AI interpretations of human biases.


The Impact of Tech in 2022

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Now is the time to upgrade our technologies, and in the year 2022, AI, ML, 5G, and Cloud Computing will be the most important technologies to emerge. The covid-19 pandemic will continue to have a wide-ranging influence on our life in 2022. As a result, the digitalization and virtualization of business and society will continue to increase. As we enter the new year, however, the demand for sustainability, ever-increasing data volumes, and faster computation and network speeds will reclaim their positions as the most essential drivers of digital transformation. IEEE has announced the conclusions of a new study of global technology executives from the United States, the United Kingdom, China, India, and Brazil titled "The Impact of Technology in 2022 and Beyond: an IEEE Global Study."


AI, ML, cloud, 5G to be most important technologies in 2022: Study

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The study revealed the findings of a global survey technology leaders from the US, UK, China, India, and Brazil, including 350 chief technology officers, chief information officers and IT directors. Because of the global pandemic, technology leaders surveyed said in 2021 they accelerated adoption of cloud computing (60%), AI and ML (51%), and 5G (46%), among others. Not surprisingly, 95% agreed, including 66% who strongly agreed, that AI will drive the majority of innovation across nearly every industry sector in the next one-five years. The technology leaders surveyed said 5G will benefit areas like telemedicine, including remote surgery and health record transmissions (24%), remote learning and education (20%), personal and professional day-to-day communications (15%), entertainment, sports and live events streaming (14%), manufacturing and assembly (13%), transportation and traffic control (7%), carbon footprint reduction and energy efficiency (5%), and farming and agriculture (2%). As for industry sectors most impacted by technology in 2022, technology leaders surveyed cited manufacturing (25%), financial services (19%), healthcare (16%) and energy (13%).