One of the major factors that will have a positive impact on the growth of this market includes the rising usage of deep learning technology among various industries such as automotive, advertisement, medical and others. Moreover, increasing acceptance of cloud based technology, high usage of deep learning in big data analytics, high R&D expansions for enhanced processing hardware for deep learning and rising applicability in healthcare and autonomous vehicles are fueling the market growth. Moreover, the market has tremendous growth opportunity such as utilization of deep learning technology in smartphones and medical image analysis. Depending on application, data mining segment is anticipated to grow at a highest CAGR during the forecast period attributed to growing utilization of deep learning in cybersecurity and database systems and data analytics.
The concept behind NLP is simple: if and when machines can understand and communicate with humans in natural (human) language, it democratizes data science, enabling humans to access, analyze, and leverage data more intelligently and become more efficient as they offload redundant, data-heavy tasks to machines. The market intelligence firm anticipates that NLP software deployments will drive significant additional sales of hardware and professional services, bringing the total NLP software, hardware, and services market opportunity to $22.3 billion by the end of the forecast period. Tractica's report, "Natural Language Processing", examines 42 NLP use cases, identifying those applications best suited for commercial use. In addition, the report details the market trends and technology issues surrounding natural language processing and presents 10-year forecasts for NLP hardware, software, and services during the period from 2016 through 2025.
DUBLIN--(BUSINESS WIRE)--The "Global Artificial Intelligence in Healthcare Market Insights, Opportunity Analysis, Market Shares and Forecast, 2017 - 2023" report has been added to Research and Markets' offering. The rising demand for real time monitoring system and increasing usage of big data in healthcare industry are responsible for the growth of the global Artificial Intelligence in healthcare market. However, ambiguous regulatory guidelines for medical software and reluctance among medical practitioners to adopt Artificial Intelligence based technologies are the factors that restrain the growth of the global Artificial Intelligence in healthcare market. Also, high usage of personal care products among consumers is driving growth of the Artificial Intelligence in healthcare market in North America.
DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence in Healthcare Market by Offering - Global Opportunity Analysis and Industry Forecast, 2017-2023" report has been added to Research and Markets' offering. The market growth is driven by rise in adoption rate of AI systems and delete technological advancements in the AI field. In addition, the ability of these systems to improve patient outcomes, increase in adoption of precision medicine, and increase in need for coordination between healthcare workforce & patients are expected to fuel the market growth. Increase in usage & application of AI systems is expected to improve patient outcomes and maintain electronic health records (EHR) & patient records to boost the market growth.
Robotic process automation (RPA) is a family of technologies designed to replicate human actions in order to complete a task or series of tasks. According to a new report from Tractica, the market for RPA is developing rapidly, and the market intelligence firm forecasts that worldwide revenue in the sector will increase from $151 million in 2016 to more than $5.1 billion by 2025. The key industry sectors that are embracing RPA implementations include financial services & banking, utilities & telecommunications, retail & commercial, and healthcare & insurance. Tractica's report, "Robotic Process Automation", provides an in-depth analysis of the robotic process automation market, including traditional approaches as well as newer cognitive RPA approaches that utilize AI capabilities.
The new research, Chatbots: Retail, eCommerce, Banking & Healthcare 2017-2022, forecasts that chatbots will be responsible for cost savings of over $8 billion per annum by 2022, up from $20 million this year. Juniper expects dramatic cost savings to be made in the healthcare and banking sectors, as enquiry resolution times are reduced and cost savings boosted. Research author Lauren Foye explained: "We believe that healthcare and banking providers using bots can expect average time savings of just over 4 minutes per enquiry, equating to average cost savings in the range of $0.50-$0.70 per interaction. In the banking sector, Juniper expects this to reach over 90% in 2022.
Tractica forecasts that deep learning software revenue will grow from $655 million in 2016 to $34.9 million worldwide by 2025. Tractica's report, "Deep Learning", examines the practical application of deep learning within consumer, enterprise, and government markets. The report provides strategic analysis and market forecasts for 112 deep learning use cases within 28 industry sectors, including an assessment of benefits and implementation considerations along with a quantification of the market opportunity for each use case. Market forecasts include deep learning software, hardware, and services revenue, segmented by world region, for the period from 2016 through 2025.
AI, which is defined as an information system that is inspired by a biological system, is an umbrella term that includes multiple technologies, such as machine learning, deep learning, computer vision, natural language processing (NLP), machine reasoning, and strong AI. Tractica's report, "Artificial Intelligence Market Forecasts", provides a quantitative assessment of the market opportunity for AI across the consumer, enterprise, and government sectors. The report includes market sizing, segmentation, and forecasts for 154 specific AI use cases and the 29 industries in which they will play a role. The market forecasts span the period from 2016 through 2025 and include segmentation by the six fundamental AI technologies: machine learning, deep learning, computer vision, NLP, machine reasoning, and strong AI.
In its fourth quarter earnings release, the Santa Clara, Calif.-based company reported revenue of $2.17 billion, up 55% year over year, on earnings per share of $1.13, up 117% a year ago. "Deep learning on Nvidia GPUs [graphics processing units], a breakthrough approach to AI, is helping to tackle challenges such as self-driving cars, early cancer detection and weather prediction," said Nvidia cofounder and CEO Jen-Hsun Huang in a statement. The company's data center business appears safe for now. And its increasing faster over time: Last quarter, reported in November, Nvidia's data center business showed 193% growth in year-over-year revenue.
"Deep learning on Nvidia GPUs [graphics processing units], a breakthrough approach to AI, is helping to tackle challenges such as self-driving cars, early cancer detection and weather prediction," said Nvidia cofounder and CEO Jen-Hsun Huang in a statement. The company's data center business appears safe for now. And its increasing faster over time: Last quarter, reported in November, Nvidia's data center business showed 193% growth in year-over-year revenue. Huang pointed out that the company's data center business relies on other areas outside of deep learning applications, including high-performance computing and running graphics-heavy software from the cloud.