The first graduate-level AI university in the world has been announced in Abu Dhabi. The university will also engage policymakers and businesses around the world so that AI can be harnessed responsibly for positive transformation. Supervision of PhD students will happen in partnership with the Abu Dhabi-based Institute of Artificial Intelligence, and all admitted students will also be offered a full scholarship as well as monthly benefits including allowance, health insurance and accommodation. Internships will be provided in collaboration with local and global companies, and students will also be assisted in finding employment opportunities. His Excellency Dr Sultan Ahmed Al Jaber, UAE minister of state and chair of the MBZUAI board of trustees, said: "MBZUAI aligns with the vision of the UAE leadership that is based on sustainable development, progress and the overall wellbeing of humanity, and underpinned by capacity-building and active participation in finding practical solutions based on innovation and state-of-the-art technology. The MBZUAI is an open invitation from Abu Dhabi to the world to unleash AI's full potential."

Leading political figures and business professionals joined forces at PRS for Music's King's Cross headquarters to examine what Artificial Intelligence (AI) means for music creators today and how it may shape the future industry. Led by Emma McClarkin, former MEP and technology and international trade specialist, a panel including Lydia Gregory, classical singer and co-founder of creative services company, FeedForward AI, and Matthew Hawn, Chief Product Officer at Audio Network delved into the topic and discussed the creative limits of a machine, whether AI, specifically Artificial General Intelligence (AGI), is a disruptive force that unsettles the already complex world of music or does it create new opportunities for creators? Emma McClarkin said: "Technology is changing the world we live in, from the way we discover music to its creation, AI will bring innovation but also big questions for the industry. Just as the UK leads in music so we should in our understanding of AI and the impact it could have." AGI could have the capacity to understand or learn any intellectual task that a human being can.

Fintech startups and banks have always been at the forefront of tech adoption, and they've been curiously following the growth and development of AI for many years. And there's a good reason for it -- we, the consumers of their services, want to have access to cutting-edge technology while dealing with our finances, as well as making sure that the companies dealing with our savings be equipped with the best of what tech can offer. AI and ML have recently moved from the realm of futurism to the very crux of the conversation in the Fintech sector, and many aspiring businesses have started integrating it into their services. In this article, we wanted to touch on the ways various Fintech businesses and startups implement this technology in the services they provide their customers with and how it benefits their users. Let's dive right in, shall we?

The amazing capabilities of AI, ML, and Predictive Analytics will lead to the transformation of various insurance processes beyond recognition. FREMONT, CA: Technology is transforming various aspects of the insurance industry. Innovative digital tools are streamlining insurance processes. Data science is one of the many areas in insurance which is impacted by technological advancements to a great extent. Data science is fueled by artificial intelligence (AI) and predictive analytics capabilities and offers insurance companies with actionable, concrete insights into a wide range of insurance processes.

Google held its big annual hardware event Tuesday in New York to unveil the Pixel 4, Nest Mini, Pixelbook Go, Nest Wifi, and Pixel Buds. It was mostly predictable because details about virtually every piece of hardware the company revealed at the event were leaked months in advance, but if Google's biggest hardware event of the year had an overarching theme, it was the many applications of on-device machine learning. Most of the hardware Google introduced includes a dedicated chip for running AI, continuing an industry-wide trend to power services consumers will no doubt enjoy, but there can be privacy implications too. The new Nest Mini's on-device machine learning recognizes your most commonly used voice commands to quicken Google Assistant response time compared to the first-generation Home Mini. In Pixel Buds, due out next year, machine learning helps recognize ambient sound levels and increase or decrease sound the same way your smartphone dims or brightens when it's in sunlight or shade.

SAN DIEGO (KGTV) - Behind every mammogram Dr. Lisa Watanabe looks at is a woman waiting, and hoping, for good news. Dr. Watanbe is a radiologist, and the Chief Medical Officer for CureMetrix, an artificial intelligence (AI) technology company focused on early breast cancer detection. Their FDA-cleared software is able to learn, using millions of mammograms, to identify, mark, and score anomalies. "Cancers that were missed by a radiologist were detected by the machine, some of them weren't even small, sometimes they were just obscured by dense tissue," said Dr. Watanabe. She says the technology has found breast cancer up to five years earlier than it was found by the human radiologist.

Sberbank Rossii PAO (MCX:SBER) and Microsoft Research (MSR) announced a joint initiative to explore the use of Microsoft's artificial intelligence (AI) solutions in robotics. The project involves training robots to interact with real-world objects in the same way that humans do. Researchers at Sberbank will be working with their MSR counterparts in Redmond, Washington. The team will try to find effective ways to control manipulators that use the capabilities of an AI platform developed by Microsoft. The platform uses machine learning, including reinforcement learning, and simulation modeling in virtual reality to develop autonomous AI systems that can function in the real world.

Word embedding -- the mapping of words into numerical vector spaces -- has proved to be an incredibly important method for natural language processing (NLP) tasks in recent years, enabling various machine learning models that rely on vector representation as input to enjoy richer representations of text input. These representations preserve more semantic and syntactic information on words, leading to improved performance in almost every imaginable NLP task. Both the novel idea itself and its tremendous impact have led researchers to consider the problem of how to provide this boon of richer vector representations to larger units of texts -- from sentences to books. This effort has resulted in a slew of new methods to produce these mappings, with various innovative solutions to the problem and some notable breakthroughs. This post is meant to present the different ways practitioners have come up with to produce document embeddings. Note: I use the word document here to refer to any sequence of words, ranging from sentences and paragraphs through social media posts all way up to articles, books and more complexly structured text documents (e.g. In this post, I will touch upon not only approaches that are direct extensions of word embedding techniques (e.g., in the way doc2vec extends word2vec), but also other notable techniques that produce -- sometimes among other outputs -- a mapping of documents to vectors in ℝⁿ. I will also try to provide links and references to both the original papers and code implementations of the reviewed methods whenever possible. Note: This topic is somewhat related, but not equivalent, to the problem of learning structured text representations (e.g., Liu & Lapata, 2018). The ability to map documents to informative vector representations has a wide range of applications.

The Assam Company India Ltd on Friday said it is aiming to increase its output by nearly fivefold to 50 million kg within next five years with introduction of advanced technologies. The company acquired by Abu Dhabi-based BRS Ventures a year ago and currently has 15 tea gardens, is looking to utilise artificial intelligence, including smart drones, in the field of tea farming to achieve its target. "Our aim is to bring technology and innovation at the forefront of the tea industry. This will not only impact the lives of 26,000 farmers at our estates, but the entire workforce employed in the tea sector across the country," BRS Ventures Chairman B R Shetty said at a press conference here. The company is optimistic that focus on enhancing the lives of the farmers and upgrading the production facilities by optimizing efficiencies will see a remarkable change in the Indian tea industry in the days to come, he added.

As artificial intelligence enhanced solutions penetrate further into our daily lives, we are confronted with the limitations of computers and of humans and the co-ordination between them. The promise of AI runs far ahead of its current capabilities, and yet the challenges are ever more urgent to address. We are at the relative beginning of an era when machines learn to use the data about us and the world around us to do things more efficiently, effectively, and more precisely. At a time when the rate of technological change exceeds imagination of the future, what is key to learn about AI is how it intersects with everything else. The future of artificial intelligence is more human.