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) …
Overview: More than 50% of enterprise IT organizations are experimenting with Artificial Intelligence (AI) in various forms such as Machine Learning, Deep Learning, Computer Vision, Image Recognition, Voice Recognition, Artificial Neural Networks, and more. AI is not a single technology but a convergence of various technologies, statistical models, algorithms, and approaches. Machine Learning is a sub-field of computer science that evolved from the study of pattern recognition and computational learning theory in AI. Every large corporation collects and maintains a huge amount of human-oriented data associated with its customers including their preferences, purchases, habits, and other personal information. As the Internet of Things (IoT) progresses, there will an increasingly large amount of unstructured machine data.
UserReplay announced today the addition of a machine learning feature to its existing solution in order to better assist companies with gaining insight into their customers' online experiences and resolve issues in real time. UserReplay machine learning uncovers hard-to-discover revenue opportunities hidden in the powerful data set captured by UserReplay. UserReplay's machine learning algorithm uncovered the issue and the high-fidelity replay showed the retailer how to fix the problem. About UserReplay UserReplay's customer experience analytics solution enables businesses to discover the truth about their customers' digital experience.
"Hindsait's main goal has been to develop a robust, AI platform that specifically addresses the needs of healthcare organizations," said Frost & Sullivan Research Analyst Harpreet Singh Buttar. "This platform assists in reducing unnecessary health services, eliminating errors and biases in care delivery and improving overall quality of care." Hindsait's system has proven to be highly adaptable and scalable, based on unique use case requirements. Their capabilities range from natural language processing (NLP) and machine learning to cognitive computing and predictive analytics that directly helps providers and payers resolve healthcare delivery issues. Hindsait boasts a wide range of services, right from analyzing unstructured data, such as clinical notes, patient charts, and prescriptions, to real-time optimization of diagnostic and treatment plans.
Norwalk, Conn.--June 8, 2016-- TMC announced today the conference program for the Smart Machine Conference, held at Caesars Palace in Las Vegas, NV from July 11 – 14, 2016. The Smart Machines conference is dedicated to exploring the business advantages of technologies like AI, Autonomous Robots, Chat bots, Neural Networks, Deep Learning, Cloud, Big Data, Virtual Reality Assistants and so much more. The conference program includes keynotes, case studies, networking opportunities and a robust exhibit floor. "The smart machine revolution is here and disrupting society as a whole whether it's fraud detection powered by machine learning, customer service chat bots or a champion chess playing computer," said TMC's CEO, Rich Tehrani, the conference's Executive Producer. "At the Smart Machine Conference attendees will learn the competitive advantages of these technologies and what the industry's future holds."
Sure continues to pioneer Episodic Insurance in the insurance market by providing consumers with simple options based on the context and information gathered through his or her mobile device with permission. The company's proprietary Robo-Broker uses real-time data to offer customized insurance options through a simple, mobile chat interaction in the Sure app and other chat platforms like Facebook Messenger, Telegram, and Whatsapp. By providing simple, mobile insurance products that fits their needs, Sure aims to fix the limitations of today's inefficient insurance-buying model. Sure has raised 2.6m from investors including: ff Venture Capital, Montage Ventures, and Fosun Kinzon Capital (Fosun Group).
Let's skip to the chase: Self-driving cars are going to be The Next Big Thing (tm). Here's how you can make big money from this revolution, no matter which carmaker or technology platform comes out on top. Since Alphabet started leading this futuristic idea out into the mainstream, the car industry itself has turned in that direction. Name a carmaker, and I bet the company has developed at least the embryo of a self-driving platform. You can already find traces of this upcoming revolution inside current cars, powering automatic parallel-parking systems or highway-speed autopilots.
After an up-and-down start to the year, Chinese search giant Baidu issued earnings last week that outperformed on a host of key indicators. As we've come to expect from Baidu, revenue growth remained brisk, increasing at a healthy 31% year-over-year pace to total 2.5 billion. In keeping with its recent quarters, increased spending crimped Baidu's operating profits, which grew only 2.6% compared with the first quarter of 2015. Either way, Baidu's earnings exceeded expectations on the top and bottom line. What's more, Baidu's guidance for second-quarter sales proved better than analysts anticipated, sending the company's shares up in after-hours trading the day of the announcement.
After an up-and-down start to the year, Chinese search giant Baidu (NASDAQ:BIDU) issued earnings last week that outperformed on a host of key indicators. As we've come to expect from Baidu, revenue growth remained brisk, increasing at a healthy 31% year-over-year pace to total 2.5 billion. In keeping with its recent quarters, increased spending crimped Baidu's operating profits, which grew only 2.6% compared with the first quarter of 2015. Either way, Baidu's earnings exceeded expectations on the top and bottom line. What's more, Baidu's guidance for second-quarter sales proved better than analysts anticipated, sending the company's shares up in after-hours trading the day of the announcement.
That is why the White House Office of Science and Technology Policy is excited to announce that we will be co-hosting four public workshops over the coming months on topics in AI to spur public dialogue on artificial intelligence and machine learning and identify challenges and opportunities related to this emerging technology. A new National Science and Technology Council (NSTC) Subcommittee on Machine Learning and Artificial Intelligence will meet for the first time next week. Broadly, between now and the end of the Administration, the NSTC group will work to increase the use of AI and machine learning to improve the delivery of government services. Applications in AI to areas of government that are not traditionally technology-focused are especially significant; there is tremendous potential in AI-driven improvements to programs and delivery of services that help make everyday life better for Americans in areas related to urban systems and smart cities, mental and physical health, social welfare, criminal justice, the environment, and much more.
Cognizant recently announced a partnership to develop Blockchain solutions for secure record-keeping of documents for Japan's Mizuho Financial Group Inc. Could you share more details on what the partnership means for the company? As part of the deal with Mizuho Financial Group announced earlier this year, we will bring together our extensive financial services, consulting and digital technology expertise to design and develop a Blockchain solution for secure record-keeping of documents among Mizuho's group firms. Effectively addressing the dual mandate for clients requires partners that can combine strategy, technology and business consulting in one integrated model. Our strategy in Japan is to not just grow our business organically with MNCs (multinational companies) and local Japanese customers, but also to work closely with local partners to deepen understanding of Japanese market requirements and sharpen onsite service delivery and Japanese language capabilities.