Artificial Intelligence

By Joy Mustafi, Principal Applied Scientist, Microsoft AI and Chairman, MUST Research Club

Joy Mustafi, Principal Applied Scientist, Microsoft AI and Chairman, MUST Research Club

Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving". In the 1940s and 50s, a group of scientists from a variety of fields (mathematics, psychology, engineering, economics and political science) began to discuss the possibility of creating an artificial brain. The field of artificial intelligence research was founded as an academic discipline in 1956. In the last 60 years as machines become increasingly capable, mental facilities once thought to require intelligence are removed from the definition. AI research is divided into subfields that focus on specific problems or on specific approaches or on the use of a particular tool or towards satisfying particular applications. The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. General intelligence is among the field's long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience and
artificial psychology.

Cognitive computing makes a new class of problems computable. To respond to the fluid nature of users understanding of their problems, the cognitive computing system offers a synthesis not just of information sources but of influences, contexts, and insights. These systems differ from current computing applications in that they move beyond tabulating and calculating based on pre-configured rules and programs. They can infer and even reason based on broad objectives. In this sense, cognitive computing is a new type of computing with the goal of more accurate models of how the human brain or mind senses, reasons, and responds to stimulus. It is a field of study which studies how to create computers and computer software that are capable of intelligent behavior. This field is interdisciplinary, in which a number of sciences and professions converge, including computer science, electronics, mathematics, statistics, psychology, linguistics, philosophy, neuroscience and biology. They must learn as information changes, and as goals and requirements evolve. They must resolve ambiguity and tolerate unpredictability. They must be engineered to feed on dynamic data in real time. They must interact easily with users so that those users can define their needs comfortably. They must interact with other processors, devices, services, as well as with people. They must aid in defining a problem by asking questions or finding additional source input if a problem statement is ambiguous or incomplete. They must remember previous interactions in a process and return information that is suitable for the specific application at that point in time. They must understand, identify, and extract contextual elements such as meaning, syntax, time, location, appropriate domain, regulation, user profile, process, task and goal. They may draw on multiple sources of information, including both structured and unstructured digital information, as well as sensory inputs (visual, gestural, auditory, or sensor-provided).

For an example - students often ever face difficulties while solving complex mathematical word problems – whether arithmetic, combinatorics or mechanics. In project CogniMaths, there are two factors that contribute to the difficulty of a word problem. First, to harness the power of natural language processing to tackle this problem and extract information from the text. The second factor is realizing which is the correct formulae to apply to obtain the desired answer. The research solution can be integrated as an interactive learning tool for students and educators around the world to help them achieve more. The solution is a computer-based question-answer system can understand an arithmetic or algebraic math problem stated in natural language and provide an answer or solution in real-time. The core idea consists of the following key steps: Get the input problem statement and question to be answered; Determine whether the original sentences are well-formed from a mathematical perspective; If required, convert the input sentences to a sequence of sentences which are well-formed from a mathematical perspective; Convert the well-formed sentences into mathematical equations; Solve the set of equations using applicable logic or mathematical methods to get a mathematical result; Correlate the mathematical result to the original question to be answered; Narrate the mathematical result in natural language, as an answer to the original question.

The overall research goal of artificial intelligence is to create technology that allows computers and machines to function in an intelligent manner. The general problem of simulating (or creating) intelligence has been broken down into sub-problems.

At Microsoft, researchers in artificial intelligence are harnessing the explosion of digital data and computational power with advanced algorithms to enable collaborative and natural interactions between people and machines that extend the human ability to sense, learn and understand. The research infuses computers, materials and systems with the ability to reason, communicate and perform with humanlike skill and agility.Microsoft’s deep investments in the field are advancing the state of the art in machine intelligence and perception, enabling computers that understand what they see, communicate in natural language, answer complex questions and interact with their environment. In addition, the company’s researchers are thought leaders on the ethics and societal impacts of intelligent technologies. The research, tools and services that result from this investment are woven into existing and new products and, at the same time, made open and accessible to the broader community in a bid to accelerate innovation, democratize AI and solve the world’s most pressing challenges.

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