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) …
Getting started in AI development is difficult and many companies are struggling with how to operationalize their developments. Taking a concept from development into production is a major hurdle for many organizations. I will guide you through the process and show you how to get started in AI, help you navigate through the maze of buzz words and concepts to take you from an idea into production.
Summary: Booze Allen just launched a one-stop shop for all manner of pretested DNN models. This makes buying just like picking accounting, CRM, or HRIS software. Equally as important, it's a genius example of platform strategy to lock in customers and lock out competitors. The common vision of developing and deploying a deep learning model is half-a-dozen (at least) data scientists and engineers slogging away over maybe three to six months before having that MVP to first test in production. Go down to the software store, grab a COTS (commercial off the shelf) DNN for any image or text problem you may have, add a little transfer learning, and slam, bang, thank you ma'am you're in production.
In the early 1980s, presentations about Infosys began with the founders' pointing out India and Bengaluru on a world map. Today, globally listed companies such as Dr Reddy's, Tata Motors, and Reliance Industries have made that redundant. The country is also the third-largest startup nation. A number of its business-to-consumer (B2C) ventures, from e-commerce major Flipkart to ride-sharing platform Ola, are known across the world. Now, a new wave of business-to-business (B2B) startups in niche segments is silently creating a significant impact globally.
AI has moved into the art world. Two paintings up for auction in New York highlight a growing interest in artificial intelligence-created works – a technique that could transform how art is made and viewed but is also stirring up passionate debate. Last year, the art world was stunned when an AI painting sold for US$432,500, and auctioneers are keen to further test demand for computer-generated works. "Art is a true reflection of what our society, what our environment responds to," said Max Moore of Sotheby's. Sotheby's will put two paintings by the French art collective Obvious up for sale this week, including "Le Baron De Belamy."
This is the fourth in a series of articles I am writing about Māori ethics with AI, Data sovereignty and Robotics. Article 3: Māori Ethical considerations with Artificial Intelligence Systems; Article 2: Māori ethics associated with AI systems architecture and Article 1: Māori cultural considerations with Artificial Intelligence and Robotics. The next planned articles are"Indigenising the Internet" and "Tikanga and Facial Recognition". At the conclusion of this article, are the English, Māori and a Translation into English of the Māori version of te Treaty of Waitangi. There is an international debate about whether we regulate Artificial Intelligence (AI) or assume that AI systems developments will be the better of the wider community.
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IMAGE: Peter Foltz, a research professor at the University of Colorado Boulder Institute of Cognitive Science, has developed an app that rates mental help based on speech cues. Thanks to advances in artificial intelligence, computers can now assist doctors in diagnosing disease and help monitor patient vital signs from hundreds of miles away. Now, CU Boulder researchers are working to apply machine learning to psychiatry, with a speech-based mobile app that can categorize a patient's mental health status as well as or better than a human can. "We are not in any way trying to replace clinicians," says Peter Foltz, a research professor at the Institute of Cognitive Science and co-author of a new paper in Schizophrenia Bulletin that lays out the promise and potential pitfalls of AI in psychiatry. "But we do believe we can create tools that will allow them to better monitor their patients."
A surge of new healthcare products from wearable consumer health trackers to diagnostic algorithms promising to improve medical outcomes and costs with artificial intelligence (AI) is prompting physicians and hospital executives to ask a fundamental question: "Are these technologies solving the right problems?" Two ongoing developments add scale and urgency to this important question. The first is a virtual gold rush of technology vendors looking to stake a claim in the healthcare IT market, which is projected to top $390 billion by 2024 according to research firm MarketsandMarkets. The second is what the World Medical Association is calling a "pandemic of physician burnout," caused by a staggering workload of electronic paperwork to document patient care and which is required for insurance coverage, financial reimbursement, and medicolegal liability protection. More than half of clinicians report feeling burned out from the hamster wheel of documentation and reporting tasks that often require spending two hours at a computer for every hour spent in patient care.