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) …
Medidata said it will acquire SHYFT for $195 million in a deal designed to expand its reach in life sciences and clinical analytics. In a statement, the company said it already owned a 6 percent stake in SHYFT. Medidata combines CRM, research and third party data to help pharmaceutical, biotech and medical device companies commercialize and develop drug and product discoveries. SHYFT's analytics and data cloud weaves data sources together, provides visualizations and cleans and transforms data to provide insights. Life sciences and health care are ripe for everything from artificial intelligence to big data to digital transformation projects.
Report Scope: In this report, the market has been segmented based on type, deployment, organization size, end-user industries, and geography.The report covers the overview of the global market for machine learning and analyses the market trends, considering the base year of 2016 and estimates for 2017 to 2022. Revenue forecasts from 2017 to 2022 for segmentation based on deployment, organization size, end-user industries, and geography have been estimated with values derived from solutions and service providers' total revenues. The report also includes a section on the major players in the market.Further, it explains the major drivers, competitive landscape, and current trends in the machine learning market. The report concludes with an analysis of the machine learning vendor landscape and includes detailed profiles of the major players in the global machine learning market. Report Includes: - 45 data tables and 32 additional tables - An overview of the global market for machine learning - Analyses of global market trends, with data from 2016 and 2017, and projections of compound annual growth rates (CAGRs) through 2022 - Identification of segments with high growth potential and their future applications - Explanation of major drivers and regional dynamics of the market and current trends within the industry - Detailed profiles of major vendors in the market, including Amazon.com Inc., Alphabet Inc., Baidu Inc., Intel Corp. and Hewlett Packard Enterprise Company Summary Machine learning is one of the fastest growing areas of computer science, with a wide range of applications.Machine learning is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.
"Every day we see a new news report on how AI is changing the future of every part of society," said Robin Bordoli, CEO of CrowdFlower. "Despite some of the concerns around job loss, we believe in the power of AI to create positive change at all levels of society. The CrowdFlower "AI for Everyone" Challenge aims to do just that by putting the power of AI into the hands of those looking to make a difference. We expect to see applications addressing global societal challenges in the areas of healthcare, food and nutrition, and climate change. We have no doubt the passion and talent exists to solve the big problems we face, and we want to play our small part in providing the resources to those who can effect change."
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.
Artificial intelligence is everywhere: your smartphone, on streaming platforms such as Spotify and Netflix and even in some smart home appliances. But can the technology, which has seemingly caught the attention of most VCs across the world, be used in the realm of healthcare to drive efficiency and optimise patient outcomes? We take a look at some of the UK's most promising companies using AI to transform the healthcare space. No list of this kind would be complete without a mention of DeepMind, a British artificial intelligence company founded in 2010 and acquired by tech giant Google for a reported £400m four years later. DeepMind Health is leveraging machine learning technology – a form of AI – to boost the medical research field.
IBM Machine Learning leverages parts of the Watson supercomputer to be used with the IBM z System Mainframe. The tech giant's initiative aims to train and deploy analytics models in the private cloud. 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. The tech giant has called its new cognitive platform IBM Machine Learning. The upcoming machine learning platform will be launched first on the z System mainframe.
Microsoft (NASDAQ:MSFT) has delivered a rapid transformation under CEO Satya Nadella. After his first few weeks as CEO, Nadella described a Mobile First, Cloud First vision on which strategic and organizational decisions would be evaluated. He has stuck to that vision ever since and the results are dramatic. No longer is "mobile" defined by a device as was the case previously. Mobile now means mobile or computing on whatever platform a consumer chooses, wherever she wants. Cloud doesn't really mean just cloud.
Health Catalyst has used healthcare.ai to build predictive models that drive its clients' outcomes improvement efforts and span across the company's product lines. Models include but are not limited to a predictive model for central line associated blood stream infection (CLABSI), readmission models for COPD and other chronic conditions, schedule optimization, and financial predictions such as patient propensity to pay. "Machine learning and artificial intelligence are going to transform healthcare. We are seeing amazing results and yet we are barely getting started. 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.
Their machine-learning platform predicted a trio of reagents that was able to generate a never-before-seen cancer-like phenotype in tadpoles. 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 researchers had previously shown that pigment cells (melanocytes) in developing frogs could be converted to a cancer-like, metastatic form by disrupting their normal bioelectric and serotonergic signaling and had used AI to reverse-engineer a model that explained this complex process. However, during these extensive experiments, the biologists observed something remarkable: All the melanocytes in a single frog larva either converted to the cancer-like form or remained completely normal. Conversion of only some of the pigment cells in a single tadpole was never seen; how, the researchers asked, could such an all-or-none coordination of cells across the tadpole body be explained and controlled?
Artificial intelligence (AI) can be understood as a science, engineering and deployment of machines, which perform tasks with intelligence as similar to humans. Since its inception 60 years ago, AI has observed significant growth in recent years. Initially, AI was considered as topic for academicians, though in recent years with development of various technologies, AI has turned into reality and is influencing many lives and businesses. Additionally, evolution of various other supplementary technologies such as cloud computing, machine learning and cognitive computing are collectively paving the growth of the market for AI. Many IT giants and start-ups are investing heavily in development of AI software solutions and hardware products.