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Researchers from Carnegie Mellon University suggest a technique called In-Context Abstraction Learning (ICAL) – a method where AI builds a memory bank of insights from multimodal experiences, drawing from imperfect demonstrations and human feedback.

AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 29, 202456Views0Likes0Comments
Researchers from Carnegie Mellon University and Google's DeepMind have developed a novel approach for training visual-language models (VLMs) called In-Context Abstraction Learning (ICAL). Unlike traditional methods, ICAL guides VLMs to build multimodal abstractions in new domains, allowing machines to better understand and learn from their experiences. This is achieved by focusing on four cognitive abstractions,…

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Researchers from New York University have released Cambrian-1: Improving Multimodal AI with Vision-Based Large Language Models for Better Performance and Adaptation in Actual World Scenarios.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 27, 202461Views0Likes0Comments
Multimodal large language models (MLLMs), which integrate sensory inputs like vision and language, play a key role in AI applications, such as autonomous vehicles, healthcare and interactive AI assistants. However, efficient integration and processing of visual data with textual details remain a stumbling block. The traditionally used visual representations, that rely on benchmarks such as…

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Researchers from New York University Present Cambrian-1: Progressing Multimodal AI with a Focus on Large Language Models for Improved Real-World Functionality and Incorporation.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 27, 202468Views0Likes0Comments
Multimodal large language models (MLLMs), which integrate sensory inputs like vision and language to create comprehensive systems, have become an important focus in AI research. Their applications include areas such as autonomous vehicles, healthcare, and AI assistants, which require an understanding and processing of data from various sources. However, integrating and processing visual data effectively…

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The Innovative Replacement for Traditional Convolutional Neural Networks (CNNs): Convolutional Kolmogorov-Arnold Networks (Convolutional KANs)

AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 25, 202473Views0Likes0Comments
Computer vision, a significant branch of artificial intelligence, focuses on allowing machines to understand and interpret visual data. This field includes image recognition, object detection, and scene understanding, and researchers are continually working to improve the accuracy and efficiency of neural networks that handle these tasks. Convolutional Neural Networks (CNNs) are an advanced architecture that…

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Cephalo: A Collection of Open-Source Extensive Language Models for Multimodal Vision (V-LLMs), Specifically Designed with the Perspective of Bio-Inspired Design.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 24, 202472Views0Likes0Comments
Materials science is a field of study that focuses on understanding the properties and performance of various materials, with an emphasis on innovation and the creation of new material for a range of applications. Particular challenges in this field involve integrating large amounts of visual and textual data from scientific literature to enhance material analysis…

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Cephalo: An Array of Open-Source, Multimodal Vision, Extensive Linguistic Models (V-LLMs) Particularly for Bio-Inspired Design Applications

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 24, 202475Views0Likes0Comments
Materials science focuses on the study of materials to develop new technologies and improve existing ones. Most researchers in this realm use scientific principles such as physics, chemistry, and understanding of engineering. One major challenge in materials science is collating visual and textual data for analysis to improve material inventions. Traditional methods rarely combine both…

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MaPO: Introducing the Memory Efficient Maestro – A Novel Benchmark for Synchronizing Generative Models with Multiple Preferences

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 23, 202481Views0Likes0Comments
Machine learning has made significant strides, especially in the field of generative models such as diffusion models. These models are tailored to handle complex, high-dimensional data like images and audio which have versatile uses in various sectors such as art creation and medical imaging. Nevertheless, perfect alignment with human preferences remains a challenge, which can…

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Removing Vector Quantization: Implementing Diffusion-Based AI Models for Autoregressive Image Production

AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 22, 202491Views0Likes0Comments
Autoregressive image generation models have traditionally been built using vector-quantized representations. However, these models have exhibited drawbacks, particularly related to their limited flexibility and computational intensity that often result in suboptimal image reconstruction. The vector quantization process involves the conversion of continuous image data into discrete tokens, which can also give rise to loss of…

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Microsoft Unveils Florence-2: A New Vision Foundation Model with an Integrated, Prompt-based Structure for a Range of Computer Vision and Vision-Language Responsibilities.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 22, 202479Views0Likes0Comments
Microsoft research team has made significant strides in introducing Florence-2, a sophisticated computer vision model. The adoption of pretrained and adaptable systems in artificial general intelligence (AGI) is increasingly becoming popular. These systems, characterized by their task-agnostic capabilities, are used in diverse applications. Natural language processing (NLP), with its ability to learn new tasks and…

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MINT-1T: A Free-to-use Trillion Token Multimodal Interweaved Collection and a Crucial Element for Educating Extensive Multimodal Models LMMs

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 20, 202468Views0Likes0Comments
Open-source pre-training datasets play a critical role in investigating data engineering and fostering transparent and accessible modeling. Recently, there has been a move from frontier labs towards the creation of large multimodal models (LMMs) requiring sizable datasets composed of both visual and textual data. The rate at which these models advance often exceeds the availability…

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Researchers at New York University suggest the use of Inter- & Intra-Modality Modeling (I2M2) for multiple mode learning, emphasizing on both cross-modality and within-modality dependencies.

AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 19, 202464Views0Likes0Comments
Researchers from New York University, Genentech, and CIFAR are pioneering a new approach to multi-modal learning in an attempt to improve its efficacy. Multi-modal learning involves using data from various sources to inform a target label, placing boundaries between the sources to allow for differentiation. This type of learning is commonly used in fields like…

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