Word embeddings have emerged as a popular approach to unsupervised learning of word relationships in machine learning and natural language processing. In this article, we benchmark two of the most popular algorithms, GloVe and word2vec, to assess their suitability for capturing medical relationships in large sources of biomedical data. Leaning on recent theoretical insights, we provide a unified view of these algorithms and demonstrate how different sources of data can be combined to construct the largest ever set of embeddings for 108,477 medical concepts using an insurance claims database of 60 million members, 20 million clinical notes, and 1.7 million full text biomedical journal articles. We evaluate our approach, called cui2vec, on a set of clinically relevant benchmarks and in many instances demonstrate state of the art performance relative to previous results. Finally, we provide a downloadable set of pre-trained embeddings for other researchers to use, as well as an online tool for interactive exploration of the cui2vec embeddings.

According to a recent report revealed by the BBC, AI could benefit NHS healthcare officials. The report found that the amount of nurses that left the NHS last year has increased by 20% since 2013. With more than 33,000 nurses resigning from the NHS last year, this is a crisis for hospitals. The NHS is working towards resolving the issue, with artificial intelligence (AI) playing a critical role, according to the report. While NHS officials have made no mention of using AI or digital technologies as part of its recruitment and retention efforts, the UK government has indicated it has high aspirations for AI, issuing a recent report with recommendations on how the UK can become a global AI innovator. Meanwhile, we have seen healthcare officials across the UK growing increasingly interested in AI's potential benefits, including the use of cognitive agents.

A base spokeswoman didn't immediately comment. The Air Force has said following previous protests that it respects assembly and free speech rights, but is committed to critical national security missions.

The rise of machine intelligence, variously referred to as AI and deep learning, and the accompanying angst over its future applications are prompting calls for a national strategy for simultaneously advancing and harnessing the technology. A report released earlier this month by the Center for Strategic and International Studies and underwritten by Booz Allen Hamilton makes the case for a comprehensive U.S. framework for maintaining leadership while ensuring "responsible development" of machine intelligence. CSIS also stresses the "hard power" implications of robotics and other forms of automation, particularly as the Defense Department and the Chinese People's Liberation Army recognize that "the next generation of military technologies will be driven" by machine intelligence. One of the report's authors said the U.S. roadmap is needed because the most recent AI R&D strategy has been overtaken by events, including a growing list of national strategies unveiled over the last year. Most notably, China released an AI development strategy in August 2017.

The entrance to SenseTime headquarters in Beijing shows who among the company's employees is inside the office and who is not (faded and tinted blue). The entrance to SenseTime headquarters in Beijing shows who among the company's employees is inside the office and who is not (faded and tinted blue). Dozens of cameras meet visitors to the Beijing headquarters of SenseTime, China's largest artificial intelligence company. One of them determines whether the door will open for you; another tracks your movements. The one that marketing assistant Katherine Xue is gazing into, in the company's showroom, broadcasts an image of my face with white lines emanating from my eyes, nose and corners of my mouth.

New Delhi: Tech honchos in Silicon Valley are deeply worried at China's rapid progress in harnessing Artificial Intelligence (AI) technology that has shown encouraging results in changing the way we work and live. Measured by start-up financing deals and dollars from venture capitalists, the United States' AI start-up ecosystem currently dominates -- followed by China, says a recent Accenture analysis titled "Rewire for Growth". When it comes to India, the number of AI start-ups has increased since 2011 at a compounded annual growth rate of 86 per cent. But the size of funding till date is substantially smaller in India than in the US and China, reflecting the limited success of India's AI start-ups in achieving scale so far, the report noted. "According to our analysis, AI has the potential to add $957 billion, or 15 per cent of current gross value added, to India's economy in 2035," said Accenture.

CAMBRIDGE – In the future, if not already, the Silicon Valleys of artificial intelligence (AI) will be in China. Alibaba, China's e-commerce giant, is based in Hangzhou. And Tencent, a multinational conglomerate that is investing heavily in AI, is in Shenzhen. Tencent already has a market capitalization higher than General Electric, and Baidu is larger than General Motors. China has a chance to lead in AI because it has managed to adopt new technologies very quickly.

Opaque and potentially biased mathematical models are remaking our lives--and neither the companies responsible for developing them nor the government is interested in addressing the problem. This week a group of researchers, together with the American Civil Liberties Union, launched an effort to identify and highlight algorithmic bias. The AI Now initiative was announced at an event held at MIT to discuss what many experts see as a growing challenge. Algorithmic bias is shaping up to be a major societal issue at a critical moment in the evolution of machine learning and AI. If the bias lurking inside the algorithms that make ever-more-important decisions goes unrecognized and unchecked, it could have serious negative consequences, especially for poorer communities and minorities. The eventual outcry might also stymie the progress of an incredibly useful technology (see "Inspecting Algorithms for Bias").

French President Emmanuel Macron has committed to investing $1.8 billion in artificial intelligence over the next four years. The spending plan will target the healthcare sector and is accompanied by a commitment to open up French data. Macron discussed the strategy following the release of a report (PDF) from a fellow French politician that sketched out an AI strategy for France and Europe. The report called for France to make health a cornerstone of its AI policy. Macron echoed the position in an interview with WiRED, in which he said healthcare is the field that drove home the potential of AI to him.

France has announced a new national AI strategy, including government funding worth nearly €1.5 billion ($1.85 billion). But the country's president, Emmanuel Macron, is worried about the damage this technology could do if not properly guided. In an interview with Wired, he said there was even a risk AI could "jeopardize democracy." Macron is worried about unaccountable "black box" algorithms being introduced into society and making decisions formerly entrusted to humans. He gave the example of an algorithm used to sort students into universities and said that if its workings were not easy to understand, it could destroy trust and encourage people to "reject" innovation.