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Grounding AI: Towards Intelligent, Stable Language Models

Artificial Intelligence, Conversational AI, Large Language Models, LLM, Shaip Blogs

Introduction to Grounding in Artificial Intelligence In the fast-changing landscape of artificial intelligence, Large Language Models (LLMs) have become powerful tools that generate human-like text. However, these outputs are not always accurate or contextually appropriate. That’s where grounding AI comes in—anchoring models to real-world data to improve factuality and relevance. Ungrounded models might sound coherent […]

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Large Language Models In Healthcare: Breakthroughs & Challenges

Artificial Intelligence, Large Language Models, LLM, Shaip Blogs

Why do we – as a human civilization – need to nurture scientific competencies and foster R&D-driven innovation? Can’t conventional techniques and approaches be followed for eternity? Well, the very purpose of science and technology is to uplift humans, elevate lifestyles, and ultimately make the world a better place. Specifically, in the realm of healthcare,

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What are the Top Multimodal AI Applications and Use Cases?

Artificial Intelligence, Generative AI, Large Language Models, LLM, Shaip Blogs

Multimodal AI brings together knowledge from varying resources like text, pictures, audio, and video, thus being able to provide richer and more thorough insights into a given scene. In this sense, the approach is distinct from older models which focus only on one type of data. Mixing different streams of data provides multimodal AI with

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What is RAFT? RAG + Fine-Tuning

Artificial Intelligence, Generative AI, Large Language Models, LLM, Shaip Blogs

In simple terms, retrieval-augmented fine-tuning, or RAFT, is an advanced AI technique in which retrieval-augmented generation is joined with fine-tuning to enhance generative responses from a large language model for specific applications in that particular domain. It allows the large language models to provide more accurate, contextually relevant, and robust results, especially for targeted sectors

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What are Large Multimodal Models (LMMs)?

Artificial Intelligence, Large Language Models, LLM, Shaip Blogs

Large Multimodal Models (LMMs) are a revolution in artificial intelligence (AI). Unlike traditional AI models that operate within a single data environment such as text, images, or audio, LMMs are capable of creating and processing multiple modalities simultaneously. Hence the generation of outputs with context-aware multimedia information. The purpose of this article is to unravel

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Optimizing RAG with Better Data and Prompts

Artificial Intelligence, Large Language Models, LLM, Shaip Blogs

RAG (Retrieval-Augmented Generation) is a recent way to enhance LLMs in a highly effective way, combining generative power and real-time data retrieval. RAG allows a given AI-driven system to produce contextual outputs that are accurate, relevant, and enriched by data, thereby giving them an edge over pure LLMs. RAG optimization is a holistic approach that

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RAG vs. Fine-Tuning: Which One Suits Your LLM?

Artificial Intelligence, Large Language Models, LLM, RAG, Shaip Blogs

Large Language Models (LLMs) such as GPT-4 and Llama 3 have affected the AI landscape and performed wonders ranging from customer service to content generation. However, adapting these models for specific needs usually means choosing between two powerful techniques: Retrieval-Augmented Generation (RAG) and fine-tuning. While both these approaches enhance LLMs, they are articulate towards different

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What Are Multimodal Large Language Models? Applications, Challenges, and How They Work

Artificial Intelligence, Healthcare AI, Large Language Models, LLM, Shaip Blogs

Imagine you have an x-ray report and you need to understand what injuries you have. One option is you can visit a doctor which ideally you should but for some reason, if you can’t, you can use Multimodal Large Language Models (MLLMs) which will process your x-ray scan and tell you precisely what injuries you

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