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5 Skills to Work Better with AI

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  AI is everywhere, and it’s here to stay. From virtual assistants to powerful decision-making tools, AI is shaping the way we work and interact with technology. But simply using AI isn’t enough—you need to understand how to make the most of it. Many people, even in everyday interactions with AI-powered tools like ChatGPT, Gemini, or DeepSeek, struggle to get the results they expect. This isn’t because AI is flawed, but because working effectively with it requires a certain set of skills. Knowing how to phrase your queries, provide the right context, and interpret AI’s responses can make all the difference. Whether you use AI for work, creativity, or problem-solving, keeping these five key skills in mind will help you unlock its true potential. 1. Know Where to Use AI AI isn’t a one-size-fits-all solution. While it excels at processing vast amounts of data and analyzing lengthy documents, it’s not always necessary—or even useful—in every situation. It’s not a magic wand, and unders...
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When Machines Take the Lead: The Case for Rules India, as the world’s largest digitally connected democracy, is moving forward at an incredible pace—but with growth comes its own set of challenges. Take the case of Sunil Bharti Mittal, Chairman of Bharti Enterprises. He recently shared a startling experience reported by The Economic Times . A scammer used AI to clone his voice and called one of his executives in Dubai, trying to authorize a large money transfer. The voice was so convincing that even Mittal himself was left stunned when he heard the recording. Stories like this show just how urgently we need laws to protect us from the darker side of AI and other digital technologies, so they can truly serve us for the better. Why the need for a legislation AI is already part of our everyday lives, often working quietly behind the scenes without us even noticing. While this powerful technology brings incredible opportunities, it also comes with risks we can’t afford to ignore. From bia...

Can language models reason?

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  Illustration by Rajashree Rajadhyax Large language models are an impressive technology that excels at providing answers based on vast knowledge of the world. However, they often struggle with reasoning and logic-based questions. To overcome this limitation, the Chain-of-Thought (CoT) method was introduced. This technique emulates how humans solve problems by reasoning step-by-step. Just as we break down complex problems into smaller, manageable parts for analysis and logical resolution, CoT guides language models to adopt a similar approach. By mimicking this natural, structured problem-solving process, CoT enhances the models’ ability to handle logic-driven tasks with greater accuracy and reliability. This approach, however, requires more time and computational effort because it involves processing more tokens . Tokens are the building blocks of text, like words or parts of words, that the model uses to understand and generate responses. Since the Chain-of-Thought method involv...

AI implementation myths

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  Visionary leaders recognize the importance of adopting cutting-edge technologies to enhance their business operations. This is a bold move, especially in the early stages when few businesses have embraced it. Generative AI is currently at such a juncture. Although AI has experienced several setbacks over the years, recent advancements in foundational models like large language models (LLMs) have reignited interest and investment in the field. Generative AI never fails to impress those who see it in action. At Cere Labs, my company, we have developed a Gen AI framework, and whenever I demonstrate it, the feedback is unanimously positive, with many stating it is "useful." However, despite this enthusiasm, there is hesitation when it comes to integrating this technology into business practices. Addressing certain misconceptions and concerns could help leaders more easily adopt Generative AI to enhance their operations. With my 8 years of experience assisting businesses in inco...