8th Global Summit on Artificial Intelligence and Neural Networks

Ambient intelligence (AmI) is a new term in the technology, it is the ability of a system to understand its surrounding environment, be aware of the user (and different people/objects) within that environment and most significantly, interpret and respond to their needs, unprompted. AmI is power driven by developments in AI and refers to the method of gathering and analyzing a wide spectrum of data signals generated in sensible environments. The global ambient intelligence market is segmented on the basis of regions into North America, Europe, Asia Pacific, Latin America and the Middle East, and Africa. North America market accounted for the largest share in the market, in 2016. This growth is attributed to increasing demand for smart buildings in the region. According to Coherent Market Insights’ analysis, the smart building market is expected to increase at a CAGR of about 18% by 2025. Rising focus on safety and security coupled with increasing concerns related to energy

According to a study, a form of artificial intelligence will analyze heart ultrasound tests than more quickly and higher than board-certified echocardiographers. Analysts at the California University trained a computer and tested them against proficient human technicians to assess the foremost common echocardiogram views. The researchers used real-world echo pictures for the advanced machine learning and resulted in finding that the computers precisely assessed ECG videos 91.6 percent to 97.8 percent of the time, compared to 70.3 percent to 83.6 percent once humans reviewed them. As results steered, this approach will be utilized in helping echocardiographers in rising their potency, accuracy, and workflow. It can also offer a foundation for higher analysis of echocardiographic data. In an echo, various video clips, still pictures and heart recordings are measured from over a dozen completely different angles, or views, many of which can have solely delicate variations. Inte

For the past five years, a team of research scientist at MIT’s Laboratory for Information and Decision Systems has been trying to create automation tools that enable the subject matter experts to use ML. The team first divided the process into a discrete set of steps. For example, the first step involved searching for buried patterns with predictive power, known as “feature selection engineering.” Second is called "model selection," in which the best modeling technique is chosen from the many available options. These steps are automated; releasing open-source tools to help domain experts efficiently complete them. Then these automated tools are grouped together, turning raw data into a trustworthy, conveyable model over the chain of seven steps. This chain of automation makes it possible for subject matter experts even those without data science experience to use machine learning to solve business problems. Through machine learning for automated data science tools

·      Client engagement and lead generation: The use of online Chatbots for healthcare on a medical practice’s website has drastically increased its client engagement levels while costing a mere fraction of the conventional method. People are already online, searching their symptoms on Google. Clinics and hospitals can attract these people to their websites and start a conversation with them via chat. Their chatbot scripts can include symptom checking questionnaires, which patients can use to understand their symptoms better. The medical chatbot can then offer these patients access to treatment at the clinic or hospital, by instantly scheduling appointments through the chat window itself. Because this interaction does not depend on business hours or working days and can happen right through the patient’s computer or smartphone, it can quickly lead to a full calendar of appointments for the clinic in question.  ·     Information on Medications and Drugs: The monetary ad

Artificial intelligence refers to machines with abilities that mimic cognitive capabilities related to the human thoughts—most significantly gaining knowledge and problem-solving. It plays a good sized function in the field of content marketing, supporting to streamline processes at a time of immense content overload and is supporting marketers decipher the ever-changing world of content marketing by examining user data and assisting marketers to make an experience of user objective. Now marketers can automatically generate content for simple stories such as sports reports and stock updates and can probably read content written by an algorithm without noticing it. Support Vector Machines ( Chatbots ) are computer applications that use artificial intelligence to mimic conversation with users. For illustration Fb Messenger uses chatbots to perform quasi-conversations with users, answering queries and issues in actual time. AI enables social networks including Twitter, Facebook,