Category: training
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Nvidia Introduces VILA: Visual Language Intelligence and Edge AI 2.0
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in AI, Applications, Artificial Intelligence, Edge AI 2.0, Guide, images, Intermediate, IOT, language models, LLM, LLMs, Models, NVIDIA, training, VILA, visual modelIntroduction Visual Language Models (VLMs) are revolutionizing the way machines comprehend and interact with both images and text. These models skillfully combine techniques from image processing with the subtleties of language comprehension. This integration enhances the capabilities of artificial intelligence (AI). Nvidia and MIT have recently launched a VLM named VILA, enhancing the capabilities of…
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NVIDIA’s Visual Language Model VILA Enhances Multimodal AI Capabilities
The artificial intelligence (AI) landscape continues to evolve, demanding models capable of handling vast datasets and delivering precise insights. Fulfilling these needs, researchers at NVIDIA and MIT have recently introduced a Visual Language Model (VLM), VILA. This new AI model stands out for its exceptional ability to reason among multiple images. Moreover, it facilitates in-context…
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Paramanu-Ganita: A New Mathematical Model that Outperforms LLaMa, Falcon, and PaLM
Introduction Large language models (LLMs) have dramatically reshaped computational mathematics. These advanced AI systems, designed to process and mimic human-like text, are now pushing boundaries in mathematical fields. Their ability to understand and manipulate complex concepts has made them invaluable in research and development. Among these innovations stands Paramanu-Ganita, a creation of Gyan AI Research.…
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Finetuning Llama 3 with Odds Ratio Preference Optimization
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Introduction Large Language Models are often trained rather than built, requiring multiple steps to perform well. These steps, including Supervised Fine Tuning (SFT) and Preference Alignment, are crucial for learning new things and aligning with human responses. However, each step takes a significant amount of time and computing resources. One solution is the Odd Ratio…
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How Data Efficient GANs Generate Images of Cats and Dogs?
Introduction Generative adversarial networks are a popular framework for Image generation. In this article we’ll train Data-efficient GANs with Adaptive Discriminator Augmentation that addresses the challenge of limited training data. Adaptive Discriminator Augmentation dynamically adjusts data augmentation during GAN training, preventing discriminator overfitting and enhancing model generalization. By employing invertible augmentation techniques and probabilistic application,…
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Implementing Query2Model: Simplifying Machine Learning
Introduction Embark on an exciting journey into the world of effortless machine learning with “Query2Model”! This innovative blog introduces a user-friendly interface where complex tasks are simplified into plain language queries. Explore the fusion of natural language processing and advanced AI models, transforming intricate tasks into straightforward conversations. Join us as we delve into the…
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Microsoft Phi 3 Mini: The Tiny Model That Runs on Your Phone
Introduction In the field of artificial intelligence (AI), there’s always been a belief that bigger is better. But Microsoft has just shaken things up with their latest creation, Phi-3-mini. It’s a small AI model that’s turning heads by showing that size isn’t everything. Despite being much smaller than its counterparts, Phi-3-mini can hold its own…