How to Use ChatGPT for Business: Real-World Applications
Artificial intelligence has quickly moved from hype to utility, and nowhere is this clearer than in how businesses are adopting conversational AI. ChatGPT is becoming a genuine driver of business outcomes. The real question for leaders today isn’t whether to use it, but how to make it work for your business model.
Prompt Engineering: From Templates to Enterprise Grade Infrastructure
The conversation around prompt engineering has evolved quickly. What started as a handful of clever templates for coaxing better answers out of AI systems is now moving toward something far more serious: enterprise-grade infrastructure for managing, scaling, and governing prompts across business-critical use cases.
Reinforcement Learning: Teaching AI Through Trial and Error
Artificial Intelligence has progressed through various learning paradigms, including supervised learning, unsupervised learning, and, most recently, reinforcement learning. Among these, reinforcement learning (RL) is unique because it doesn’t rely solely on labeled data or static patterns.
Beginner Friendly Guide to Multimodal Prompting 101
Artificial intelligence isn’t just about text anymore. Models today can process images, audio, video, and text in a single workflow, opening doors to richer applications that go beyond simple Q&A. This shift is powered by multimodal prompting, a method where different types of inputs work together to generate better, more context-aware outputs.
Prompt Engineering in Real-World AI Software: Challenges, Learnings, and Use Cases
AI can perform miracles but only if you know how to ask. I’m Subodh, a Prompt Engineer at Nirvana Lab. I’ve wrestled with the fine art of crafting the perfect AI instruction. Sometimes, a single word changes everything other times, even the most polished prompts fail spectacularly.
AI vs ML vs Deep Learning: What’s the Difference?
Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are often used interchangeably, but they represent distinct concepts with unique applications. Understanding the difference between AI, ML, and deep learning is crucial for business leaders, tech enthusiasts, and decision-makers navigating the digital transformation orbit.
How to Build A Machine Learning Model (Step-by-Step Guide)
Machine learning (ML) is transforming industries by enabling data-driven decision-making, automation, and predictive analytics. Whether you’re a business leader, data scientist, or a beginner, understanding how to build a machine learning model is essential.
10 Best Prompt Engineering Techniques for Better AI Responses
In 2025, AI becomes increasingly integrated into business workflows, and the ability to extract high-quality responses from AI models has become a critical skill. Prompt engineering, the practice of crafting effective inputs to guide AI outputs, plays a pivotal role in maximizing the utility of AI tools like ChatGPT, Gemini, and Claude.