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) processing today is mostly done in a cloud-based data center. The majority of AI processing is dominated by training of deep learning models, which requires heavy compute capacity. In the last 6 years, the industry has experienced a 300,000X growth in compute requirements, with graphics processing units (GPUs) providing most of that horsepower. According to a new report from Tractica, however, as the diversity of AI applications grows, an increasing amount of AI processing will be handled within edge devices rather than in a centralized, cloud-based environment. Tractica forecasts that AI edge device shipments will increase from 161.4 million units in 2018 to 2.6 billion units worldwide annually by 2025.
Significant advances have been made during the past few years in the ability of artificial intelligence (AI) systems to recognize and analyze human emotion and sentiment, owing in large part to accelerated access to data (primarily social media feeds and digital video), cheaper compute power, and evolving deep learning capabilities combined with natural language processing (NLP) and computer vision. According to a new report from Tractica, these trends are beginning to drive growth in the market for sentiment and emotion analysis software. Tractica forecasts that worldwide revenue from sentiment and emotion analysis software will increase from $123 million in 2017 to $3.8 billion by 2025. The market intelligence firm anticipates that this growth will be driven by several key industries including retail, advertising, business services, healthcare, and gaming. According to Tractica's analysis, the top use case categories for sentiment and emotion analysis will be as follows: "A better understanding of human emotion will help AI technology create more empathetic customer and healthcare experiences, drive our cars, enhance teaching methods, and figure out ways to build better products that meet our needs," says principal analyst Mark Beccue.
Imagine this scenario: An executive's primary competitor has just hired a promising start-up, a software firm specializing in strong artificial intelligence that covers a broad range of applications, not just something specific such as translation or image recognition. Trying to learn more about this, she looks up the start-up founder's TEDx talk but finds it impenetrable. The firm's website boasts claims for the tool bordering on science fiction and has pictures of young men and women and their dogs in a WeWork space against a backdrop of whiteboards all covered in formulas. How solid is this technology? How does what the people with the dogs say they do intersect with what their technology seems to be for?
This article was written by Kwon Sok Oh, a Financial Analyst at I Know First. NVIDIA Corp. (NASDAQ: NVDA) is the leading designer and manufacturer of graphics processing units and related products and services. It's main operating segments are the GPU segments and the Tegra Processor segment. NVIDIA currently has 11,528 employees with $9.71 billion in revenue in 2017. It is headquartered in Santa Carla, CA.
According to the new research report "Artificial Intelligence in Supply Chain Market by Offering, Technology, Application (Fleet Management, Supply Chain Planning, Warehouse Management, Virtual Assistant, Freight Brokerage), End-User Industry, and Geography - Global Forecast to 2025", published by MarketsandMarkets, the market is expected to grow from USD 730.6 million in 2018 to USD 10,110.2 million by 2025, at a CAGR of 45.55% between 2018 and 2025. Major drivers for the market are the growth of big data, demand for greater visibility and transparency into supply chain data and processes, and adoption of AI for improving consumer services and their satisfaction. The major restraint for the market is the limited number of the artificial intelligent technology experts. Browse 64 market data Tables and 44 Figures spread through 176 Pages and in-depth TOC on "Artificial Intelligence in Supply Chain Market - Global Forecast to 2025" The software market is expected to grow at the highest CAGR for artificial intelligence in supply chain by 2025. The adoption of AI-based software solutions is increasing as it has beginning to apply machine learning capabilities that can automatically detect errors and make course corrections while processing real-time data streams.
Artificial intelligence (AI) technology is progressing at a rapid pace, as is the application of the technology to solve real-world problems. While the market for chipsets to address deep learning training and inference workloads is still a new one, the landscape is changing quickly – in the past year, more than 60 companies of all sizes have announced some sort of deep learning chipset or intellectual property (IP) design. A new report from Tractica finds that virtually every prominent name in the technology industry has acknowledged the need for hardware acceleration of AI algorithms and the semiconductor industry has responded by offering a wide variety of solutions. Tractica forecasts that the market for deep learning chipsets will increase from $1.6 billion in 2017 to $66.3 billion by 2025. System-on-a-chip (SoC) accelerators such as those found in mobile devices will lead the market in terms of sheer volumes by the end of the forecast period, followed by application-specific integrated circuits (ASICs) and graphics processing units (GPUs).
The Global Artificial Intelligence In Insurance Market Report includes a comprehensive analysis of the present market. The report starts with the basic Artificial Intelligence In Insurance Market overview and then goes into each and every detail. Houston, TX -- (SBWIRE) -- 05/26/2018 -- Artificial Intelligence In Insurance Market research report offers comprehensive insight into the key growth drivers, notable challenges, prominent trends, recent technological advancements, and the competitive landscape. The study presents a critical assessment of the scope of key applications and the innovations in products brought about by key players. It further takes a closer look at prevailing regulatory landscape in major regions and identifies promising avenues.
This has further foisted pressure on the traditional retailers to reimagine the strategies for creating and capturing value in order to explore the optimal usage of their assets. Public policy liberalization is also one of the key factors supporting the flow of knowledge, information and resources, further generating pressure on the brick n' mortar retailers to tackle with the lowered entry barriers to the online retailers in the market. Key trend which will predominantly effect the market in coming year is rising adoption of multi-channel or omni channel retailing. In forthcoming years, the retail industry is anticipated to witness higher growth in the trend of Omni channel retailing. Artificial intelligence will be having a key role as this technology would be bridging the gap between online and offline retailing in coming future.