Probability theory plays a foundational role in artificial intelligence (AI) by helping systems reason, make predictions, and handle uncertainty. In AI, especially in real-world scenarios, outcomes are rarely deterministic. Agents must often make decisions with incomplete or noisy information, requiring a framework to measure, update, and infer probabilities dynamically. One of the most important tools ...
In the field of artificial intelligence and machine learning, learning algorithms are essential for developing systems that can adapt, predict, and improve over time. Among the foundational learning techniques is inductive learning, which focuses on drawing general conclusions from specific examples. It mimics the way humans learn from experience—by observing patterns and extrapolating rules. Inductive ...
Artificial Intelligence (AI) is reshaping the retail industry by driving smarter operations, hyper-personalized experiences, and data-informed decision-making. In an era where customer expectations are rapidly evolving, retailers face intense competition and growing pressure to deliver seamless, personalized, and responsive shopping journeys—both online and in-store. Shoppers today demand real-time service, tailored recommendations, and frictionless checkout. To ...
Uncertainty in Artificial Intelligence (AI) refers to the lack of complete certainty in decision-making due to incomplete, ambiguous, or noisy data. AI models handle uncertainty by using probabilistic methods, fuzzy logic, and Bayesian inference. Proper uncertainty representation enables AI systems to make informed predictions and improve reliability in real-world applications. What is Uncertainty in Artificial ...
The Traveling Salesman Problem (TSP) is a well-known combinatorial optimization problem in computer science and artificial intelligence (AI). It involves finding the shortest possible route that allows a salesman to visit N cities exactly once and return to the starting point. The challenge lies in the exponential increase in possible routes as the number of ...
Inference in artificial intelligence (AI) refers to the logical process of deriving conclusions from a given set of premises or facts. It plays a crucial role in automated reasoning, knowledge representation, and decision-making systems, allowing AI to mimic human-like reasoning. Inference mechanisms are widely used in expert systems, natural language processing, and automated theorem proving, ...
The Dempster-Shafer Theory (DST) is a mathematical framework for handling uncertainty and incomplete information in decision-making. Unlike traditional probability theory, which requires prior probabilities, DST allows for degrees of belief based on available evidence. This makes it highly useful in artificial intelligence, expert systems, and data fusion applications. What is Dempster Shafer Theory? The Dempster-Shafer ...
Artificial Intelligence (AI) is transforming the transportation industry, making mobility safer, smarter, and more efficient. AI-powered solutions are enhancing traffic management, predictive maintenance, autonomous driving, and logistics optimization, creating a more sustainable and connected transport ecosystem. One of the key roles of AI in transportation is improving efficiency by analyzing vast amounts of data from ...
Strong AI, also known as Artificial General Intelligence (AGI), refers to an advanced form of artificial intelligence that can think, reason, and learn at a human level or beyond. Unlike current AI models, which are designed for specific tasks, Strong AI aims to possess general intelligence, allowing it to adapt to unfamiliar situations, make independent ...
Artificial Intelligence (AI) algorithms are the core mechanisms that enable machines to process information, learn patterns, and make decisions without human intervention. These algorithms form the foundation of AI systems, allowing computers to recognize speech, classify images, analyze data, and predict outcomes with accuracy and efficiency. AI algorithms play a crucial role in automation, problem-solving, ...
Team Applied AI
Abhimanyu Saxena
