If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Artificial intelligence (AI) doesn't just have technological applications. Simulation of human intelligence processes has demonstrated that it can help farmers, artisans and fisherman to substantially eliminate the gap between the price they get for their produce and the market price, said Amitabh Kant, speaking at the AI Startup Conclave organised by leadingindia.ai "AI can help double their income with the same efforts and tools they are using today," said Kant, who was addressing scholars from prestigious institutions and other startup invitees. Leadingindia.ai, is an initiative being supported by NVIDIA, Amazon, edX, Newton-Bhabha Fund, Royal Academy of Engineering, UK, Brunel University and University College, London. Special teams from the government of Andhra Pradesh, Maharashtra and Gujarat attended the event.
According to the DJI's report, around 65 people have been rescued by drones in the last year. The report, "More Lives Saved: A Year Of Drone Rescues Around The World," features the innovative drone technology, and the rapid adoption by first responders to increase the pace of drone use in critical public safety missions. Reports have also stated that drones have dropped buoys to struggling swimmers in Australia and Brazil, and found helpless people in fields, rivers, and mountains. Approximately, 22 out of 65 "were at great risk of death, such as stranded in a body of water or exposed to hazardous weather." "Drones allow rescuers a way to find missing people, deliver supplies like food and life vests, and cut search and response times from hours to minutes," says Brendan Schulman, DJI's Vice-President of policy and legal affairs.
At some point in the future, while riding along in a car, a kid may ask their parent about a distant time in the past when people used steering wheels and pedals to control an automobile. Of course, the full realization of the "auto" part of the word -- in the form of fully autonomous automobiles -- is a long way off, but there are nonetheless companies trying to build that future today. However, changing the face of transportation is a costly business, one that typically requires corporate backing or a lot of venture funding to realize such an ambitious goal. A recent funding round, some $128 million raised in a Series A round by Shenzhen-based Roadstar.ai, In short, not as many as you'd think.
The chip manufacturer Infineon is setting up a new development center at its Dresden site. It will focus on new products and solutions in the field of automobile and power electronics and artificial intelligence. Its core tasks will include modeling complex systems, developing highly integrated products, and chip design. The launch is planned for 2018. "Microelectronics accounts for about 90% of all innovations in cars", explains chairman of the board Dr. Reinhard Ploss .
This article is brought to you thanks to the strategic cooperation of The European Sting with the World Economic Forum. Author: Rhodri Davies, Head of Policy, Charities Aid Foundation Artificial intelligence has become a hot political and cultural topic. UK prime minister Theresa May made it the centerpiece of her appearance at this year's Davos Summit.
Reprinted with permission from Quanta Magazine's Abstractions blog. When he talks about where his fields of neuroscience and neuropsychology have taken a wrong turn, David Poeppel of New York University doesn't mince words. "There's an orgy of data but very little understanding," he said to a packed room at the American Association for the Advancement of Science annual meeting in February. He decried the "epistemological sterility" of experiments that do piecework measurements of the brain's wiring in the laboratory but are divorced from any guiding theories about behaviors and psychological phenomena in the natural world. It's delusional, he said, to think that simply adding up those pieces will eventually yield a meaningful picture of complex thought.
Artificial Neural Networks (ANN) are replacing traditional Machine Learning models to evolve precise and accurate models. Convolutional Neural Networks (CNN) brings the power of deep learning to computer vision. Some of the recent advancements in computer vision such as Single Shot Multibox Detector (SSD) and Generative Adversarial Networks (GAN) are revolutionizing image processing. For example, using some of these techniques, images and videos that are shot in low light and low resolution can be enhanced to HD quality. The ongoing research in computer vision will become the base for image processing in healthcare, defense, transportation and other domains.
Github compiled a list of the top open datasets for machine learning and it seems as though every data scientist has a favorite. We pulled a few from their list but you can see more in the first article, below. You can also find a recap of the SharePoint Conference and reactions to the SharePoint Server 2019. Many of our readers were also interested in how AI can benefit the employee experience. It's so easy, "toucan" do it too!
One of the main concerns with AI technologies today is the fear that they will propagate the various biases we already have in society. A recent Stanford study turned things around, however, and highlighted how AI can also turn the mirror onto society and shed light on the biases that exist within it. The study utilized word embeddings to map relationships and associations between words and, through that measure, the changes in gender and ethnic stereotypes over the last century in the United States. The algorithms were fed text from a huge canon of books, newspapers, and other texts, while comparing these with official census demographic data and societal changes, such as the women's movement. The researchers used embedding to single out specific occupations and adjectives that tended to be biased toward women or ethnic groups each decade from 1900 to the present day.