She is a full-stack developer with 4+ years of experience, including 1 year in AI. Passionate about AI, computer vision, and NLP, she's driven by curiosity and loves exploring real-world solutions. In her free time, she enjoys movies and cricket.
Why does conversational context matter in chatbots? Learn how context-aware design helps bots respond more naturally, remember past interactions, and improve user experience across every exchangeâwithout sounding robotic or disconnected.
What happens when demand forecasts miss the mark? AI in demand forecasting enables retailers to tackle shifting trends, reduce costs, and manage inventory with greater precision. Discover how data-driven forecasting enables faster and smarter retail decisions.
Can code be written in plain English? Natural language programming bridges the gap between ideas and executionâno complex syntax required. Letâs break down how it works, where it fits, and why it matters.
What shapes a better AI response? Great answers often start with great prompts. Learn how generated knowledge prompting improves reasoning, clarity, and accuracyâplus techniques to guide models step by step with confidence.
Whatâs changing with generative AI in 2025? From autonomous agents to advanced reasoning, see how todayâs trends shape real business outcomesâand what you can do to stay ahead.
How much can AI remember? Gemini 1.5 Pro changes the story with a massive context window that helps process entire books, codebases, or videos, without losing the thread or skipping key details.
This article provides a clear look into the importance of prompt engineering in generative AI. It explains how prompt quality directly impacts AI outputs' relevance and accuracy. You'll find key strategies, real-world use cases, and best practices to craft effective prompts for better results across various industries.
This article examines the most impactful generative AI use cases across key industries like healthcare, finance, manufacturing, and media. It explores how businesses use AI to speed up operations, solve complex problems, and improve service delivery. Discover how this technology is transforming work as we know it.
This article provides a step-by-step guide to help beginners learn how to code AI systems from scratch. It breaks down complex concepts into simple steps, covering essential tools, math, and programming basics. Readers will also explore hands-on projects to build real-world AI skills with confidence.
This article provides a clear look at the real-world challenges of AI, including bias and privacy concerns. It offers practical strategies to manage these risks, like using clean data and promoting transparency. Youâll also learn how ethical practices can help make AI adoption safer and more effective.
This article provides a clear overview of how ethical AI frameworks guide responsible AI development. It highlights key principles, global standards, and real-world implementation steps. Youâll learn how these frameworks ensure fairness, reduce harm, and build trust in AI systems.
This article provides an overview of how machines learn from data without being told exactly what to look for. It explores how deep belief networks (DBNs) handle unlabeled data and uncover complex features using layers of Restricted Boltzmann Machines. Youâll learn how DBNs are trained, where they work best, and how they differ from other deep learning models.
