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MG-LLaVA: An Advanced Multi-Modal Model Adept at Processing Visual Inputs of Multiple Granularities, Including Object-Level Features, Original-Resolution Images, and High-Resolution Data

Multi-modal Large Language Models (MLLMs) have various applications in visual tasks. MLLMs rely on the visual features extracted from an image to understand its content. When a low-resolution image containing fewer pixels is provided as input, it translates less information to these models to work with. Due to this limitation, these models often need to…

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A Simple Open-loop Model-Free Baseline for Reinforcement Learning Locomotion Tasks without Using Complex Models or Computational Resources

The field of deep reinforcement learning (DRL) is expanding the capabilities of robotic control. However, there has been a growing trend of increasing algorithm complexity. As a result, the latest algorithms need many implementation details to perform well on different levels, causing issues with reproducibility. Moreover, even state-of-the-art DRL models have simple problems, like the…

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Forget Statistical Tests: A/B Testing Is All About Simulations | by Samuele Mazzanti | Jul, 2024

How simulations outperform traditional stats in that they are easier to understand, more flexible, and economically meaningful [Image by Author]Controlled experiments such as A/B tests are used heavily by companies. However, many people are repelled by A/B testing due to the presence of intimidating statistical jargon including terms such as “confidence”, “power”, “p-value”, “t-test”, “effect…

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NanoNets AI Solution Transfers Delivery Information to Jamix

Integration between NanoNets and JAMIX Kitchen Intelligence System allows you to streamline your order-delivery process when the supplier provides delivery documents as printouts. The NanoNets AI solution scans printed delivery documents, converts the information into digital format and transfers the data to the JAMIX System.  JAMIX Kitchen Intelligence System is a comprehensive kitchen management software…

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7 Ways Machine Learning Transforms Customer Relationship Management

Customer relationship management (CRM) is vital for businesses. It helps you manage and analyze client interactions throughout their lifecycle. Leveraging these systems improves consumer satisfaction, boosts retention and drives sales growth. Recently, machine learning (ML) integration has revolutionized CRM because it brings a new level of sophistication to customer engagement. ML algorithms analyze vast…

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CMU Researchers Propose In-Context Abstraction Learning (ICAL): An AI Method that Builds a Memory of Multimodal Experience Insights from Sub-Optimal Demonstrations and Human Feedback

Humans are versatile; they can quickly apply what they’ve learned from little examples to larger contexts by combining new and old information. Not only can they foresee possible setbacks and determine what is important for success, but they swiftly learn to adjust to different situations by practicing and receiving feedback on what works. This process…

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