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Top Artificial Intelligence Solution Companies In Europe

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In today's digital era, artificial intelligence (AI) is at the core of every automatic or self-sustaining system available in the marketplace. Be it the robotics workforce used in the manufacturing industry and logistics or the tools employed in the fields like healthcare, agriculture and automobile, AI is ubiquitous. All industry leaders across verticals are focused heavily on AI and advance solutions involving Deep Learning and Neural Networks. BPU Holdings is a global company, headquartered in Korea that pioneers in the development of Artificial Emotional Intelligence (AEI). The mission of the company is to generate the most advanced, secure usable, and innovative Artificial Emotional Intelligence technology in the world.


Europe's data revolution

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The growth potential of the data economy is mind-blowing. In Europe alone, the figures and forecasts are eye-catching, to say the least. The European Commission expects the value of the data economy to rise to €829 billion by 2025, up from €301 billion in 2018. Focusing on the headline economic figures alone overlooks the enormous potential to use data to create lasting social change and improve the personal and professional lives of millions of European citizens. The term digital economy is a catch-all for a wide range of digital transformation activities.


Top Artificial Intelligence Solution Companies

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BPU Holdings is a global company, headquartered in Korea that pioneers in the development of Artificial Emotional Intelligence (AEI). The mission of the company is to generate the most advanced, secure usable, and innovative Artificial Emotional Intelligence technology in the world. BPU has developed the first Artificial Emotional Intelligent (AEI) platform -- AEI Framework, which emulates how people think and feel. BPU improves the human condition by offering rigorous tools to improve emotional intelligence. Tracking and handling emotions enable the management of professional and interpersonal relationships, empathetically and judiciously.


How to make the most of AI? Open up and share data

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In this episode of the McKinsey on AI podcast miniseries, McKinsey's David DeLallo and Jeni Tennison, CEO of the Open Data Institute (ODI), discuss the promise and pitfalls of open data. They explore ways that applications of open data can benefit society and consider efforts to preserve data security and privacy, promote data discovery, and ensure the quality of open data. David DeLallo: Data--it's the lifeblood of the AI techniques used most often today. Most organizations have plenty of data within their veritable walls to fuel AI applications that improve areas from operations to product offerings. But it's the sharing of data across organizations that could unlock huge benefits for society.


Data Marketplace: sharing platform for data analytics, data mining, IoT, ML

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We are convinced that in the age of Artificial Intelligence and Industry 4.0, provi ding the most open possible access to data for all users serves as the basis for innova tion and progress. This starts with you as an interested private indivi dual and leads to your business enter prise, which wants to monetise its own data or use external data for new insights. Use open data to open up new perspec tives and lift your data project to the next level. In the sense of free access to data as a democratic basis for innova tions, we see open data as a core aspect of our offering. This is why we already combine almost 2 million open data records from over 8000 unique provi ders.


The case for open data for AI in the fight against COVID-19

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Death rate may be a poor metric. If it's very high for 80 years old people, this is a group where death can occur any time due to the next cold or flu for example. A better metric is life span reduction. In an 80-year old with health issues, life span reduction might just be a few weeks. Also, I assume many people already caught it and recovered without being aware of ever catching it, and they are unaccounted for in the statistics if they didn't go to the doctor and were not properly tested.


The case for open data for AI in the fight against COVID-19

#artificialintelligence

Death rate may be a poor metric. If it's very high for 80 years old people, this is a group where death can occur any time due to the next cold or flu for example. A better metric is life span reduction. In an 80-year old with health issues, life span reduction might just be a few weeks. Also, I assume many people already caught it and recovered without being aware of ever catching it, and they are unaccounted for in the statistics if they didn't go to the doctor and were not properly tested.


Get started with the Data Asset eXchange

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The IBM Data Asset eXchange (DAX) is an online hub for developers and data scientists to find free and open data sets under open data licenses. A particular focus of the exchange is data sets under the Community Data License Agreement (CDLA). For developers, DAX offers a trusted source for open data sets for artificial intelligence (AI). These data sets are ready to use in enterprise AI applications and are supplemented with relevant notebooks and tutorials. Also, DAX offers unique access to various IBM and IBM Research data sets and offers various integrations with IBM Cloud and AI services.


r/MachineLearning - [N] Call for papers: QOD 2020 Workshop

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The 3rd Workshop on Quality of Open Data will be held in conjunction with BIS conference on June 8-10, 2020 in Colorado Springs, United States. The goal of QOD 2020 workshop is to bring together different communities working on quality in Wikipedia, DBpedia, Wikidata, OpenStreetMap, Wikimapia and other open knowledge bases and data sources. The workshop calls for sharing research experience and knowledge related to quality assessment in open data. We invite papers that provide methodologies and techniques, which can help to verify and enrich various community based services in different languages. Papers approved for presentation at QOD 2020 will be published as a volume in Springer's Lecture Notes in Business Information Processing (LNBIP) series.


Microsoft's President on Privacy, Artificial Intelligence, and Human Rights

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Before a rapt, standing-room-only audience of more than 300 students, faculty, and other members of the Law School community, Microsoft President and Chief Legal Officer Brad Smith '84 returned to campus on October 1 to discuss his new book, Tools and Weapons: The Promise and the Peril of the Digital Age (cowritten with Carol Ann Browne). The event with Gillian Lester, Dean and the Lucy G. Moses Professor of Law of Columbia Law School, and Professor Tim Wu, a leading authority on antitrust law who advocates for breaking up Big Tech companies, was the season's first installment of the Dean's Distinguished Speaker Series. "Brad may be the only tech executive who would willingly share the stage with Professor Wu, given Tim's strong and well-articulated position on the perils associated with the bigness of today's technology companies," said Dean Lester in her introduction. The conversation touched on a number of pressing concerns, including cybersecurity, government regulation, ethics, and human rights. Smith's book addresses the untold ramifications of digital technology's ubiquity in our personal lives, our societies, and our economies.