NEWS IN BRIEF: AI/ML FRESH UPDATES

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Maximizing Results with Small Samples

Learn how to design precise experiments using optimization in Python with a step-by-step guide. Optimization-based approach improves statistical inference, reducing experimental costs in disciplines like oncology.

Building Real-World RAGs: Lessons from GenAIIC

AWS GenAIIC helps customers with generative AI, focusing on Retrieval-Augmented Generation (RAG) for chatbots. RAG architecture involves retrieval, augmentation, and generation, with a key emphasis on optimizing the retriever for efficient document ingestion.

Revolutionizing Indian Manufacturing with NVIDIA AI and Omniverse

Indian manufacturers and service providers are leveraging NVIDIA Omniverse for factory planning and automation. Ola Electric and Reliance Industries are utilizing Omniverse for faster time to market and solar panel factory planning, showcasing the power of AI in India's manufacturing industry.

Maximize Call Analytics with Amazon Q in QuickSight

Amazon Web Services offers AI solutions like Post Call Analytics to enhance customer service by providing actionable insights from call recordings. Amazon Q in QuickSight enables users to easily analyze post-call data and generate visualizations for data-driven decisions.

Optimizing ML Models: The Power of Chaining

ML metamorphosis, a process chaining different models together, can significantly improve model quality beyond traditional training methods. Knowledge distillation transfers knowledge from a large model to a smaller, more efficient one, resulting in faster and lighter models with improved performance.

Supercharge Your LLMs on RTX with LM Studio

Large language models (LLMs) are transforming productivity with tasks like drafting documents and answering questions. NVIDIA RTX GPUs enable local running of LLMs, optimizing AI acceleration and performance with GPU offloading and LM Studio.

Revolutionizing ML: Relational Deep Learning

Engage in Relational Deep Learning (RDL) by directly training on your relational database, transforming tables into a graph for efficient ML tasks. RDL eliminates feature engineering steps by learning from raw relational data, enhancing model performance and granularity.

The Power of Agentic AI

AI chatbots use generative AI for responses. Agentic AI autonomously solves complex problems, improving productivity across industries.