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DeepStack: Boosting Multimodal Structures using Layered Visual Token Assimilation for Exceptional High-Resolution Outcomes

AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 12, 202427Views0Likes0Comments
Researchers from Fudan University and Microsoft have developed a novel architecture for language and vision models (LMMs), called "DeepStack." The DeepStack model takes a different approach to processing visual data, thereby improving overall computational efficiency and performance. Traditional LMMs typically integrate visual and textual data by converting images into visual tokens, which are then processed…

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“Teach-MusicGen: A Unique AI Method for Converting Text into Music while Enhancing Both Melodic and Literary Controls”

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Sound, Staff, Tech News, Technology, UncategorizedJune 12, 202437Views0Likes0Comments
Instruct-MusicGen, a new method for text-to-music editing, has been introduced by researchers from C4DM, Queen Mary University of London, Sony AI, and Music X Lab, MBZUAI. This new approach aims to optimize existing models that require significant resources and fail to deliver precise results. Instruct-MusicGen utilizes pre-trained models and innovative training techniques to accomplish high-quality…

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Researchers utilize extensive language models to assist robots with navigation.

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Data, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, Robotics, Robots, School of Engineering, UncategorizedJune 12, 202433Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a language-based navigational strategy for AI robots. The method uses textual descriptions instead of visual information, effectively simplifying the process of robotic navigation. Visual data traditionally requires significant computational capacity and detailed hand-crafted machine-learning models to function effectively. The researchers' approach involves converting a…

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Improving the Safety and Dependability of AI via Short-Circuiting Methods

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 12, 202433Views0Likes0Comments
AI system vulnerabilities, particularly in large language models (LLMs) and multimodal models, can be manipulated to produce harmful outputs, raising questions about their safety and reliability. Existing defenses, such as refusal training and adversarial training, often fall short against sophisticated adversarial attacks and may degrade model performance. Addressing these limitations, a research team from Black…

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Improving Efficiency of Large-scale Parallel Training with C4, Developed by Alibaba.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 12, 202439Views0Likes0Comments
Large Language Models (LLMs) such as GPT-3 and Llama face significant inefficiencies during large-scale training due to hardware failures and network congestion. These issues can lead to a substantial waste of GPU resources and extended training durations. Existing methods to address these challenges, which involve basic fault tolerance and traffic management strategies, are often inefficient…

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A novel approach to computer vision accelerates the screening process of electronic components.

3-D printing, Algorithms, Artificial Intelligence, Automation, Computer vision, Imaging, Machine learning, Materials science and engineering, Mechanical engineering, Renewable energy, Research, School of Engineering, Solar, Sustainability, UncategorizedJune 12, 202436Views0Likes0Comments
Solar cells, transistors, LEDs, and batteries with boosted performance require better electronic materials which are often discovered from novel compositions. Scientists have turned to AI tools to identify potential materials from millions of chemical formulations, with engineers developing machines that can print hundreds of samples at a time, based on compositions identified by AI algorithms.…

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