Vishweshwar Joshi

Artificial Intelligence (AI) has many branches that address different challenges in mimicking human cognition and solving complex problems. Two essential subfields that stand out for their focus on guiding intelligent agents toward goal achievement are search and planning. These domains are critical in determining the sequence of actions or steps an AI system must take to achieve specific goals. From navigating a maze to making business decisions, these methods provide the fundamental framework that defines how an AI agent interacts with its environment.

AI 101: The Fundamentals of Search and Planning for Smarter Systems - Startupsgurukul Artificial Intelligence (AI) has many branches that address different challenges in mimicking human cognition and solving complex problems. Two essential

Artificial Intelligence (AI) fundamentally revolves around the concept of building intelligent agents—systems that can perceive their environment and take actions to achieve specific goals. At the core of this concept is the rational agent, which makes decisions based on available information (or percepts) and chooses actions that maximize the likelihood of achieving its goals.

AI Agents Explained: How Rational Agents Think, Plan, and Act - Startupsgurukul Artificial Intelligence (AI) fundamentally revolves around the concept of building intelligent agents—systems that can perceive their environment and take

Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of technological advancements, driving innovations across various sectors. At the core of these innovations are algorithms—structured sets of instructions that guide machines in making decisions, solving problems, and learning from data. While the user interface is what most people see and interact with, the real magic happens behind the scenes, powered by sophisticated algorithms. This blog post will delve into the intricacies of algorithms in AI/ML, from their creation to how they are patented, and why they are so special.

The Heart of AI: Understanding and Developing Powerful Algorithms - Startupsgurukul Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of technological advancements, driving innovations across various sectors. At the

Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized how machines interact with the world, making it possible for them to “see” and “hear” in ways that were once the exclusive domain of human beings. Optical Character Recognition (OCR) and voice assistants like Alexa and Siri are prime examples of how these technologies mimic human cognition to process and interpret visual and auditory information. In this post, we’ll explore the mechanisms behind OCR and voice assistants, their parallels with human cognition, and how these AI technologies are inspired by the workings of the human brain.

The Neural Blueprint of AI: How Human Cognition Shapes OCR and Voice Technology - Startupsgurukul Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized how machines interact with the world, making it possible for them to "see" and

The notion of an “agent” in artificial intelligence (AI) is a foundational concept used to describe entities that perceive their environment and act upon it. However, as highlighted in the provided text, it’s crucial to understand that the idea of an agent is primarily a tool for analyzing systems, rather than an absolute categorization that rigidly divides the world into agents and non-agents. This perspective is essential for both theoretical exploration and practical application in AI and engineering.

The Science of AI Agents: Bridging the Gap Between Simple Systems and Complex Decision-Making - Startupsgurukul The notion of an "agent" in artificial intelligence (AI) is a foundational concept used to describe entities that perceive their environment and act upon it.