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) …
Finalists will be selected by members of CrowdFlower's Scientific Advisory Board: Barney Pell, founder at Moon Express; Pete Warden, Staff Research Engineer at Google; Monica Rogati, independent data science advisor; Adrian Weller, Senior Research Fellow at the University of Cambridge and Lukas Biewald, founder at CrowdFlower. About CrowdFlower CrowdFlower is the essential human-in-the-loop AI platform for data science teams. The CrowdFlower software platform supports a wide range of use cases including self-driving cars, intelligent personal assistants, medical image labeling, content categorization, customer support ticket classification, social data insight, CRM data enrichment, product categorization, and search relevance. Headquartered in San Francisco and backed by Canvas Venture Fund, Trinity Ventures, and Microsoft Ventures, CrowdFlower serves data science teams at Fortune 500 and fast-growing data-driven organizations across a wide variety of industries.
The global machine learning as a service (MLaaS) market is poised to grow from $1.07 billion in 2016 to $19.86 billion in 2025, at a CAGR of more than 38%, according to a new report from Transparency Market Research. Demand for MLaaS has been highest in the healthcare and life sciences industry, due primarily to the need to integrate structured and unstructured data in these areas, especially data generated by electronic health records. Other industries that will benefit from this technology moving forward include manufacturing, retail, telecom, finance, energy and utilities, education, and the government, as MLaaS can improve the decision-making capabilities of devices used in those areas, the report stated. Enterprises' move to the cloud is another important factor behind the expected growth of the MLaaS market, the report noted--as more companies shift toward cloud computing, it is easier for them to take advantage of machine learning. SEE: 5 steps to turn your company's data into profit MLaaS solutions are typically deployed in both the public and private cloud, though private cloud accounts for most of the revenue generated in the global MLaaS market, the report noted.
DeepMind Health is leveraging machine learning technology – a form of AI – to boost the medical research field. Ali Parsa, Babylon's founder, told Tech City News that his app could potentially reduce expenditure by the NHS and improve system efficiency – cutting down the amount of time NHS call workers spend on the phone with patients calling its 111 line to discuss medical issues. Founded by Australian Neil Daly, the startup hopes to combat skin melanoma by allowing patients to track matters of concern via an AI-powered smartphone image recognition app. Antidote Match helps patients easily identify the trials that match to them; Connect Network streams the latest study information to patients on the platform; and Antidote Bridge enables users to add details about their studies.
According to Tech Republic, IBM plans to bring soon some of the core machine learning technology from IBM Watson to the private cloud and mainframes, as the company announced on Wednesday, Feb. 15. IBM described IBM Machine Learning in a press release as a platform that will facilitate creating, training and deploying high volume of analytic models in the private cloud. IBM Machine Learning is leveraging core Watson technologies in order to accelerate the adoption of machine learning, according to the statement of Rob Thomas, general manager for IBM Analytics, published in the press release. According to the release, IBM Machine Learning can help create and train operational analytic models by using any popular machine learning framework, any language and any transactional data type.
Other requirements included location awareness and data warehousing and data visualization. This build-out is well underway creating growth in dozens of companies providing chipsets such as Nvidia (NASDAQ:NVDA), RFID led by Impinj (NASDAQ:PI), data base technology as with Splunk (NASDAQ:SPLK), outsourced warehousing including REITs such as Data Reality (NYSE:DLR), optical components providers as in Oclaro (NASDAQ:OCLR), visualization technology such as Tableau and telecoms moving to LTE. Internet of Industrial Things "IoIT" (aka Industrial Internet), Internet of people, internet of connections, connected (home, car, health, factory, city, anything). The next phase requires several essential technologies and where Microsoft is primarily focusing their efforts along with Apple, Amazon, Facebook (NASDAQ:FB), Google (NASDAQ:GOOG) and IBM (NYSE:IBM).
We are applying it to the reduction of patient harm events, care management, hospital acquired infections, revenue cycle management, patient risk stratification, and more," said Dale Sanders, Executive Vice President of Health Catalyst. "We believe that machine learning is too helpful and important to be handled solely by full-time data scientists," said Sanders. Health Catalyst is a mission-driven data warehousing, analytics and outcomes-improvement company that helps healthcare organizations of all sizes perform the clinical, financial, and operational reporting and analysis needed for population health and accountable care. Our proven analytics platform helps improve quality, add efficiency and lower costs in support of more than 70 million patients for organizations ranging from the largest US health system to forward-thinking, small physician practices.
The research, reported in Scientific Reports on January 27, shows how artificial intelligence (AI) can help human researchers in fields such as oncology and regenerative medicine control complex biological systems to reach new and previously unachievable outcomes. The computer model predicted the percentage of tadpoles that would retain completely normal melanocytes within 1 percent of the in vivo results while aggregating the percentage of tadpoles that showed partial or total conversion in vivo. Work was supported by National Science Foundation grant EF-1124651, the Allen Discovery Center program through The Paul G. Allen Frontiers Group, and The G. Harold and Leila Y. Mathers Charitable Foundation. Lobo, D., Lobikin, M., Levin, M. Discovering novel phenotypes with automatically inferred dynamic models: a partial melanocyte conversion in Xenopus.
Some the prominent players in AI market in the recent times are Intel Corporation (U.S.), Google Inc. (U.S.), Microsoft Corporation (U.S.), Amazon.com, Computer vision technology has become a part of high definition video games, while deep learning; which is a subset of machine learning is now implemented in speech recognition, drug discovery, health monitoring and various others applications. However, the scarcity of low cost and energy efficient hardware, and the lack of skilled workforce for development of AI algorithms and tools is curbing the growth of the AI market. On the other hand, IBM acquired Truven Health Analytics (U.S.) in April 2016, with this IBM intent to derive insights from Truvens health data using Watson Healths cognitive capabilities. Alongside this, leading graphics processing unit (GPU) providers, NVIDIA Corporation launched the industrys first deep learning system,?NVIDIA DGX- 1, in April 2016.
This clearance enables Arterys to make use of its unique clinical annotation platform, which collects ground-truth data every time a user views a study on Arterys.com. About Arterys, Inc. Arterys, a pioneer in cloud-based medical imaging analytics software, is committed to accelerate the transformation of data driven medicine. The company's medical imaging analytics platform leverages the power of cloud computation and deep learning to support automated post-processing, diagnostic and therapeutic decisions. Starting with cardiac MRI, Arterys now plans to leverage its platform to create other imaging applications to make medical imaging services a whole more automated, quantitative, and useful.
Watson Health alone has 7,000 employees, and last year the company launched Watson Financial Services using cloud and cognitive computing. To serve individual industries with better data sets, IBM acquired Truven Health Analytics for $2.6 billion and Promontory Financial Group for undisclosed financial terms last year. Strategic imperatives – cloud, Watson AI, analytics, security and mobile technologies – drew in $9.5 billion for the quarter, up 11% year-over-year. For the full year 2016, strategic imperatives generated $32.8 billion in sales, up 13%, representing 41% of IBM revenues.