Prabhat Korshub Blogs

  Introduction to GenAI in Finance & Accounting Artificial Intelligence has been making waves across industries, but 2025 marks a defining year for Generative AI (GenAI) in the world of finance and accounting. Imagine a digital co-worker who can prepare your balance sheets, detect anomalies, predict future revenue, and even write your audit reports—all in seconds. That’s GenAI. Finance teams are leveraging GenAI not just for automation but for strategic intelligence , reshaping how organizations manage money, mitigate risk, and plan for the future. The Evolution of AI in Finance Gone are the days when AI was just a glorified calculator. Earlier systems could automate data entry or reconcile bank statements—but now, GenAI understands context, writes narratives, and even generates complex financial models. In 2025 , this evolution has reached a point where AI can interpret financial data, draft reports, and provide real-time insights without human intervention. How GenA...

  Introduction Artificial Intelligence (AI) and Machine Learning (ML) have transformed the way we live, work, and interact with technology. By 2025, AI & ML will be ubiquitous , powering everything from autonomous vehicles to personalized healthcare and smart finance systems. Python has emerged as the go-to programming language for AI and ML due to its simplicity, flexibility, and vast ecosystem of libraries and frameworks. Whether you are a beginner or an experienced developer, learning Python for AI & ML opens the door to endless opportunities. What is Artificial Intelligence (AI)? Artificial Intelligence refers to the simulation of human intelligence in machines. AI systems can perceive, reason, learn, and make decisions similar to humans. Over the years, AI has evolved from rule-based systems to deep learning and generative AI , making it more powerful and versatile. Applications of AI in daily life include: Virtual assistants like Siri and Alexa Recommend...

  Introduction Leadership and management have always been about inspiring people, making smart decisions, and driving organizations forward. But in today’s digital era, leaders face challenges far more complex than ever before—fast-paced markets, global uncertainty, and massive amounts of data that can’t be processed manually. This is where Generative AI steps in, not as a replacement for leaders, but as a powerful partner to empower them. Imagine having a co-pilot who never sleeps, crunches endless data in seconds, and even helps you understand your team better. That’s what generative AI brings to leadership—a masterclass in transforming managers into forward-thinking leaders. Understanding Generative AI What is Generative AI? Generative AI is an advanced branch of artificial intelligence that doesn’t just analyze—it creates. It can generate ideas, write strategies, design workflows, and even simulate possible future outcomes. Key Capabilities of Generative AI in Business ...

  🚀 Introduction Let’s be real— AI is not just the future anymore. It’s the present. Whether you're a student, a freelancer, an entrepreneur , or someone just curious about the tech world, AI tools can supercharge your workflow, creativity, and income. In 2025, knowing how to use AI is like knowing how to use a computer in the '90s—it’s no longer optional if you want to stay ahead. From writing and designing to coding and automating tasks, there’s an AI tool for pretty much everything. So let’s dive into 20+ powerful AI tools you should absolutely start learning today. 💬 Conversational AI Tools ChatGPT The king of conversational AI. You can use it to write articles, generate code, brainstorm ideas, or even tutor you in math. Pro tip : Use GPT-4 for the best performance and explore tools like Memory and Custom Instructions. Custom GPTs Custom GPTs let you build your own version of ChatGPT with specific skills and personality. Think of it like creating your own AI as...

  Introduction Welcome to the ultimate 2025 Masterclass on Data Science using Python—your complete A to Z guide for entering and thriving in the world of Machine Learning. Whether you're just starting out or looking to sharpen your skills, this guide is crafted to take you from zero to job-ready hero in the exciting domain of data science. Python remains the leading language for data scientists—and with good reason. It’s readable, flexible, and packed with robust libraries that can turn raw data into powerful insights. Getting Started with Data Science Who Is This Course For? This course is for: Students aiming for a data-driven career Professionals switching into data science Analysts who want to level up with ML Tools You Need Python (3.10+) Jupyter Notebooks (via Anaconda) GitHub for version control Google Colab (optional for cloud use) Setting Up Your Environment Download and install Anaconda. Launch Jupyter Notebook. Test libraries l...

  Full AI Course 2025: ChatGPT, Gemini, Midjourney, Firefly Introduction Welcome to the Future of AI Learning 2025 isn’t just another year. It’s the year AI goes mainstream. From intelligent chatbots to generative art, artificial intelligence is no longer a futuristic dream — it’s in your browser, your design tools, your search engine, and even your daily workflows. And guess what? You can master it all. Why 2025 Is the Best Time to Learn AI AI tools have become insanely user-friendly. You no longer need a PhD in computer science to build intelligent applications. With platforms like ChatGPT, Gemini, Midjourney, and Firefly leading the way, learning AI has become as simple as using a Google search or designing a poster in Canva. Understanding Artificial Intelligence Today What Is AI, Really? AI stands for Artificial Intelligence , the ability of machines to mimic human intelligence. Whether it's understanding language, recognizing images, or making decisions — AI is behind many of...

  Aragonese Cartoonists: Boycott AI Art Until Laws Protect Artists The platforms that use Artificial Intelligence to model and design images need three parts to generate them, which are divided into people, computing and data. They spend huge sums of money on the first two; but the third, the accumulated data resource, they want to get for free. These hundreds of thousands of stored data that they use to generate their designs have been stolen and hoarded as their own from the different web domains and social networks of the creatives, the most vulnerable and precarious part of the equation. As long as we do not have regional, state and European laws and directives that protect the violated copyright of designers, the AAAC calls on public institutions and entities – city councils, universities, libraries, State Government, regional governments and other local entities – not to use them for their publications and posters. Using them represents an improper use of our work, which is ...