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Meet Gemini: A Google’s Groundbreaking Multimodal AI Model Redefining the Future of Artificial Intelligence

Google’s latest venture into artificial intelligence, Gemini, represents a significant leap forward in AI technology. Unveiled as an AI model of remarkable capability, Gemini is a testament to Google’s ongoing commitment to AI-first strategies, a journey that has spanned nearly eight years. This development is not just a milestone for Google but also the wider […]
The post Meet Gemini: A Google’s Groundbreaking Multimodal AI Model Redefining the Future of Artificial Intelligence appeared first on MarkTechPost.

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Mitigate hallucinations through Retrieval Augmented Generation using Pinecone vector database & Llama-2 from Amazon SageMaker JumpStart

Despite the seemingly unstoppable adoption of LLMs across industries, they are one component of a broader technology ecosystem that is powering the new AI wave. Many conversational AI use cases require LLMs like Llama 2, Flan T5, and Bloom to respond to user queries. These models rely on parametric knowledge to answer questions. The model […]

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Researchers from Microsoft Research and Georgia Tech Unveil Statistical Boundaries of Hallucinations in Language Models

A key issue that has recently surfaced in Language Models is the high rate at which Language Models (LMs) provide erroneous information, including references to nonexistent article titles. The Merriam-Webster dictionary defines a hallucination as “a plausible but false or misleading response generated by an artificial intelligence algorithm.” In one instance, attorneys who submitted legal […]
The post Researchers from Microsoft Research and Georgia Tech Unveil Statistical Boundaries of Hallucinations in Language Models appeared first on MarkTechPost.

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Techniques for automatic summarization of documents using language models

Summarization is the technique of condensing sizable information into a compact and meaningful form, and stands as a cornerstone of efficient communication in our information-rich age. In a world full of data, summarizing long texts into brief summaries saves time and helps make informed decisions. Summarization condenses content, saving time and improving clarity by presenting […]

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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

Conversational AI has come a long way in recent years thanks to the rapid developments in generative AI, especially the performance improvements of large language models (LLMs) introduced by training techniques such as instruction fine-tuning and reinforcement learning from human feedback. When prompted correctly, these models can carry coherent conversations without any task-specific training data. […]

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Meet Ego-Exo4D: A Foundational Dataset and Benchmark Suite to Support Research on Video Learning and Multimodal Perception

Today, AI finds its application in almost every field imaginable. It has definitely transformed our lives, streamlining processes and enhancing efficiency in ways we couldn’t have imagined before. Its capabilities could be improved even further by advancements in understanding human skills, which could facilitate numerous applications such as virtual coaching, robotics, and even social networking. […]
The post Meet Ego-Exo4D: A Foundational Dataset and Benchmark Suite to Support Research on Video Learning and Multimodal Perception appeared first on MarkTechPost.

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A Guide on 12 Tuning Strategies for Production-Ready RAG Applications

How to improve the performance of your Retrieval-Augmented Generation (RAG) pipeline with these “hyperparameters” and tuning strategiesTuning Strategies for Retrieval-Augmented Generation ApplicationsData Science is an experimental science. It starts with the “No Free Lunch Theorem,” which states that there is no one-size-fits-all algorithm that works best for every problem.

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