Natural language processing (NLP) and large language models (LLMs) have been revolutionized with the introduction of transformer models. These refer to a type of neural network architecture that excels at tasks involving sequences. While we have talked about the details of a typical transformer architecture, in this blog we will explore the different types of the models. Transformers ensure the efficiency of LLMs in processing information. Their role is critical to ensure improved accuracy, faster training on data, and wider applicability. Hence, it is important to understand the different mod ..read more

Knowledge graphs and LLMs are the building blocks of the most recent advancements happening in the world of artificial intelligence (AI). Combining knowledge graphs (KGs) and LLMs produces a system that has access to a vast network of factual information and can understand complex language. The system has the potential to use this accessibility to answer questions, generate textual outputs, and engage with other NLP tasks. This blog aims to explore the potential of integrating knowledge graphs and LLMs, navigating through the promise of revolutionizing AI. Before we understand the impact and m ..read more

If I were to ask you, can Generative AI in education outperform students in competitive assessments like that of Harvard’s or Stanford’s, what would your answer be? Maybe? Let me tell you, the answer is yes. That’s the exciting world of generative AI, shaking things up everywhere across the globe, be it logical assessments, medical exams, or a thought-provoking essay at the Ivy Leagues.  Chatbot vs Medical Student Performance on Clinical Reasoning Examinations Now, before you imagine robots taking over classrooms, hold on! Generative AI isn’t here to replace humans, it’s more of a super-p ..read more

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Large Language Models are growing smarter, transforming how we interact with technology. Yet, they stumble over a significant quality i.e. . Often, they provide unreliable information or guess answers to questions they don’t understand—guesses that can be completely wrong. This issue is a major concern for enterprises looking to leverage LLMs. How do we tackle this problem? Retrieval Augmented Generation ( ) offers a viable solution, enabling LLMs to access up-to-date, relevant information, and significantly improving their responses. Tune in to our podcast and dive deep into RAG, fine-tuning ..read more

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