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RAG Infographics
AI/MLMay 15, 2025

Understanding Retrieval-Augmented Generation (RAG)

Retrieval-Augmented Generation (RAG) is an advanced AI architecture that combines two key components, a retriever to fetch relevant information from an external knowledge source and a generator (a large language model) to create human-like responses using that information.

Arun Raj

Manufacturing floor at Tesla
AIFebruary 19, 2025

5 Real Use Cases of AI in Manufacturing

The integration of AI in manufacturing can enhance operational efficiency, reduce costs, and drive innovation - with predictive analysis, supply chain optimization and much more. Read 5 such use cases of AI in the manufacturing industry.

Jesso Clarence

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Efficient Data Processing with Practical Parallelism in AI Workflows
AI/MLApril 28, 2025

Efficient Data Processing with Practical Parallelism in AI Workflows

In the era of Generative AI, the quality and scale of data processing have become more critical than ever. While sophisticated language models and ML algorithms steal the spotlight, the behind-the-scenes work of data preparation remains the unsung hero of successful AI implementations.

Ragul Kachiappan

The Dawn of Believable AI Voices: A Deep Dive into Sesame's Conversational Speech Model
AIMarch 20, 2025

The Dawn of Believable AI Voices: A Deep Dive into Sesame's Conversational Speech Model

The Dawn of Believable AI Voices explores Sesame's advanced conversational speech model, highlighting its breakthrough in generating natural, expressive AI voices that enhance human-computer interactions.

Jesso Clarence

Cost of developing Ai solutions
AIFebruary 11, 2025

The Cost of AI: Development Cost, ROI, and Optimization Strategies

AI solutions involve leveraging pre-trained LLMs, fine-tuning models for specific applications, and optimizing AI deployments for cost and efficiency. Hers's a structured approach to cost estimation, pricing models, and return on investment (ROI) calculations

Jesso Clarence