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Apple AI Research Introduces MM1.5: A New Family of Highly Performant Generalist Multimodal Large Language Models (MLLMs)

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Multimodal large language models (MLLMs) represent a cutting-edge area in artificial intelligence, combining diverse data modalities like text, images, and even video to build a unified understanding across domains. is poised to address key challenges in multimodal AI. The post Apple AI Research Introduces MM1.5:

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This AI Research Introduces TinyGPT-V: A Parameter-Efficient MLLMs (Multimodal Large Language Models) Tailored for a Range of Real-World Vision-Language Applications

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The development of multimodal large language models (MLLMs) represents a significant leap forward. These advanced systems, which integrate language and visual processing, have broad applications, from image captioning to visible question answering. If you like our work, you will love our newsletter.

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This AI Paper Introduces DyCoke: Dynamic Token Compression for Efficient and High-Performance Video Large Language Models

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Video large language models (VLLMs) have emerged as transformative tools for analyzing video content. These models excel in multimodal reasoning, integrating visual and textual data to interpret and respond to complex video scenarios. Don’t Forget to join our 55k+ ML SubReddit.

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Google DeepMind Researchers Propose Optimization by PROmpting (OPRO): Large Language Models as Optimizers

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With the constant advancements in the field of Artificial Intelligence, its subfields, including Natural Language Processing, Natural Language Generation, Natural Language Understanding, and Computer Vision, are getting significantly popular. If you like our work, you will love our newsletter.

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Can a Language Model Revolutionize Radiology? Meet Radiology-Llama2: A Large Language Model Specialized For Radiology Through a Process Known as Instruction Tuning

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Large language models (LLMs) built on transformers, including ChatGPT and GPT-4, have demonstrated amazing natural language processing abilities. The creation of transformer-based NLP models has sparked advancements in designing and using transformer-based models in computer vision and other modalities.

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Microsoft AI Releases LLMLingua: A Unique Quick Compression Technique that Compresses Prompts for Accelerated Inference of Large Language Models (LLMs)

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Large Language Models (LLMs), due to their strong generalization and reasoning powers, have significantly uplifted the Artificial Intelligence (AI) community. If you like our work, you will love our newsletter.

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Researchers from Microsoft and Georgia Tech Introduce VCoder: Versatile Vision Encoders for Multimodal Large Language Models

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In the evolving landscape of artificial intelligence and machine learning, the integration of visual perception with language processing has become a frontier of innovation. This integration is epitomized in the development of Multimodal Large Language Models (MLLMs), which have shown remarkable prowess in a range of vision-language tasks.