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) …
Self-driving cars are one of the high-risk artificial intelligence applications the European Union wants to regulate. The European Commission today unveiled its plan to strictly regulate artificial intelligence (AI), distinguishing itself from more freewheeling approaches to the technology in the United States and China. The commission will draft new laws--including a ban on "black box" AI systems that humans can't interpret--to govern high-risk uses of the technology, such as in medical devices and self-driving cars. Although the regulations would be broader and stricter than any previous EU rules, European Commission President Ursula von der Leyen said at a press conference today announcing the plan that the goal is to promote "trust, not fear." The plan also includes measures to update the European Union's 2018 AI strategy and pump billions into R&D over the next decade.
IDCC uniquely leverages optical character recognition, Utopia's advanced machine learning code, intelligent online web search, and document search. Beginning simply with only a photo of a manufacturer's nameplate, IDCC can produce complete and accurate material and asset information. Manufacturer and model data is organized in ISO-14224 standards and can be delivered via a variety of easy-to-integrate methods, including SAP Asset Intelligence Network . The cloud-based nature of IDCC enables cost-effective, rapid deployments by large and small organizations alike. IDCC can be deployed in pure cloud environments, such as SAP Intelligent Asset Management, or hybrid deployments using SAP Master Data Governance, enterprise asset management extension by Utopia.
With an imperative to empower the youngest minds of the country with the latest technologies, NITI Aayog, Atal Innovation Mission (AIM) in collaboration with the National Association of Software and Services Companies (NASSCOM) today launched an AI based Module rolled out for students in Indian schools. The AI-Base Module has been introduced with an objective for students to leverage the full potential of AIM's Atal Tinkering Lab (ATL) and further empowers them to innovate and create valuable solutions benefiting societies at large. The module contains activities, videos and experiments that enable students to work through and learn the various concepts of AI. Sharing his thoughts, CEO, NITI Aayog Amitabh Kant said that India can add 1.3% to its GDP on an annual basis through the use of machine learning and artificial intelligence. "Indians can find solutions to the challenges of a shared connected zero emission world, improving learning outcomes, disease like tuberculosis, cancer etc. If we are able to find solutions to these challenges for the 1.3 billion people of India, we can find solutions for the 7.5 billion people of the world too," he said.
Graphcore Ltd., the British semiconductor firm whose chips are used to run artificial intelligence programs, has raised $150 million, bringing its valuation to $1.95 billion. The company now has $300 million in cash, which it will use to invest in research and development and global expansion, Bristol, England-based Graphcore said in a statement on Tuesday. After it raised $200 million in 2018, Graphcore was approached by additional investors who wanted to put money into the company, Chief Executive Officer Nigel Toon said in an interview. While the company has no immediate plans for an initial public offering, several of its investors, such as Baillie Gifford, have experience investing in publicly traded technology companies and are the types of shareholders the company would try to target if it were to go public at some point in the future, Toon said. "Having this additional capital on hand allows us to accelerate our investment and allows us to be in a position to support the really large customers who we're building business with," Toon said.
HONG KONG/BEIJING – Autonomous driving firm Pony.ai said it raised $462 million in its latest funding round, led by an investment by Toyota Motor Corp. Toyota invested around $400 million (¥44.2 billion) in the round, Pony.ai said in a statement Wednesday, marking its biggest investment in an autonomous driving company with a Chinese background. The latest fund raising values the three-year-old firm, already backed by Sequoia Capital China and Beijing Kunlun Tech Co., at slightly more than $3 billion. The investment by Japan's largest automaker comes at a time when global carmakers, technology firms, start-ups and investors -- including Tesla, Alphabet Inc.'s Waymo and Uber -- are pouring capital into developing self-driving vehicles. Over the past two years, 323 deals related to autonomous cars raised a total of $14.6 billion worldwide, according to data provider PitchBook, even amid concerns about the technology given its high cost and complexity. The Silicon Valley-based startup Pony.ai -- co-founded by CEO James Peng, a former executive at China's Baidu, and chief technology officer Lou Tiancheng, a former Google and Baidu engineer -- is already testing autonomous vehicles in California, Beijing and Guangzhou.
The "The Business Use of Artificial Intelligence" training has been added to ResearchAndMarkets.com's offering. Your competitors are using AI to analyze sales, what do you do? Organizations today are applying artificial intelligence capabilities to a wide variety of uses especially in operations such as for process enablement. Each organization is focusing on performance improvements using AI. This explosion of interest in AI poses a challenge to managers to effectively make sense of and use AI effectively.
Artificial Intelligence applications are expanding into nearly every area of industry including government services, transportation, healthcare, cybersecurity, autonomous systems, finance and more. Forbes includes artificial intelligence as one of the "Hottest Career Paths of 2020 and Beyond." In order to meet the increasing demand for AI professionals, the University of North Texas, a Tier One research university, is offering the only Master of Science degree in artificial intelligence in Texas and one of only a few programs nationwide. The new degree offers students the choice of three concentrations: machine learning, autonomous systems and biomedical engineering. Students will be able to take classes that allow them to explore specific interests in AI and leave the program with marketable skills.
The challenge is that the math behind it is somewhat complicated, and that it has to be run, over and over, across vast quantities of data to suss out the statistical weights and biases of a particular system. The work will get done; it might just take a long time. Data scientists and machine learning researchers have long used graphics processing units (GPUs) because of their highly parallelized architecture and relatively abundant on-chip memory available. But as industry and research groups alike seek more efficiency and need to accommodate ever-larger quantities of information, more specialized computing hardware is required for the task. Headquartered in Bristol, U.K., Graphcore is in the business of producing silicon purpose-built for munching through machine-learning math at high rates of speed and using less electricity than GPUs.
According to a new market intelligence report by BIS Research titled'Global Artificial Intelligence (AI) in Energy Market – Analysis and Forecast, 2019-2024', the artificial intelligence in energy market is expected to reach $7.78 billion by 2024. The market is projected to witness a CAGR of 22.49% from 2019 to 2024. This growth is anticipated to be driven by the demand for increasing operational efficiency, rising concern for energy efficiency, growing market penetration of decentralized power generation, and rising concern for battery storage systems. Browse more than 60 Data Tables and 150 Figures spread through 259 Pages and in-depth ToC on "Global Artificial Intelligence (AI) in Energy Market". Artificial intelligence utilizes advanced algorithms and stacks of data accumulated from the source to provide systems and machines with the ability to perceive, think, calculate, and analyze information like a human brain.