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Tag: Multimodal

  • Generative AI on AWS: Building Context-Aware Multimodal Reasoning – VERY GOOD

    Generative AI on AWS: Building Context-Aware Multimodal Reasoning – VERY GOOD



    Generative AI on AWS: Building Context-Aware Multimodal Reasoning – VERY GOOD

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    Generative AI on AWS: Building Context-Aware Multimodal Reasoning

    In recent years, generative AI has been making waves in the tech world, enabling machines to understand and generate human-like content such as images, text, and even music. With the power of AWS, developers can now take their generative AI projects to the next level by building context-aware multimodal reasoning systems.

    By combining different modalities such as text, images, and audio, developers can create AI systems that can not only generate content but also understand and reason about the context in which it is presented. This opens up a world of possibilities for applications in fields like natural language processing, computer vision, and more.

    With AWS’s powerful cloud infrastructure and tools like Amazon SageMaker, developers can easily train and deploy complex generative AI models at scale. By leveraging AWS’s comprehensive suite of machine learning services, developers can focus on building innovative AI applications without worrying about the underlying infrastructure.

    So, if you’re looking to take your generative AI projects to the next level, consider harnessing the power of AWS to build context-aware multimodal reasoning systems. The possibilities are endless, and the results can be truly transformative.
    #Generative #AWS #Building #ContextAware #Multimodal #Reasoning #GOOD

  • Mastering PyTorch: Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond

    Mastering PyTorch: Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond


    Price: $51.99 – $39.51
    (as of Dec 15,2024 22:54:45 UTC – Details)


    From the brand

    Packt's Brand Story

    Packt's Brand Story

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    Packt is a leading publisher of technical learning content with the ability to publish books on emerging tech faster than any other.

    Our mission is to increase the shared value of deep tech knowledge by helping tech pros put software to work.

    We help the most interesting minds and ground-breaking creators on the planet distill and share the working knowledge of their peers.

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    Publisher ‏ : ‎ Packt Publishing; 2nd ed. edition (May 31, 2024)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 558 pages
    ISBN-10 ‏ : ‎ 1801074305
    ISBN-13 ‏ : ‎ 978-1801074308
    Item Weight ‏ : ‎ 2.11 pounds
    Dimensions ‏ : ‎ 1.14 x 7.5 x 9.25 inches


    Are you ready to take your deep learning skills to the next level? In our latest post, we’ll be diving into the world of PyTorch and exploring how you can create and deploy a wide range of deep learning models, from Convolutional Neural Networks (CNNs) to multimodal models, Large Language Models (LLMs), and beyond.

    PyTorch is a powerful open-source deep learning framework that has become increasingly popular among researchers and practitioners in the field. With its flexible and intuitive design, PyTorch makes it easy to build and train complex neural networks for a wide range of applications.

    In this post, we’ll walk you through the process of building and deploying deep learning models in PyTorch. We’ll cover everything from the basics of setting up your environment and defining your model architecture, to training and fine-tuning your model on real-world datasets. We’ll also explore how you can leverage PyTorch’s built-in tools and libraries to optimize your models for performance and scalability.

    Whether you’re a seasoned deep learning practitioner looking to expand your skills or a newcomer eager to dive into the world of deep learning, this post is for you. Join us as we explore the exciting world of PyTorch and learn how you can create and deploy cutting-edge deep learning models for a wide range of applications.
    #Mastering #PyTorch #Create #deploy #deep #learning #models #CNNs #multimodal #models #LLMs

  • Generative AI on AWS: Building Context-Aware Multimodal Reasoning Applications

    Generative AI on AWS: Building Context-Aware Multimodal Reasoning Applications


    Price: $79.99 – $55.99
    (as of Dec 15,2024 05:00:40 UTC – Details)


    From the brand

    oreillyoreilly

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    Sharing the knowledge of experts

    O’Reilly’s mission is to change the world by sharing the knowledge of innovators. For over 40 years, we’ve inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.

    Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.

    Publisher ‏ : ‎ O’Reilly Media; 1st edition (December 19, 2023)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 309 pages
    ISBN-10 ‏ : ‎ 1098159225
    ISBN-13 ‏ : ‎ 978-1098159221
    Item Weight ‏ : ‎ 1.1 pounds
    Dimensions ‏ : ‎ 7 x 0.65 x 9.19 inches

    Customers say

    Customers find the book easy to understand with clear explanations of high-level concepts. The examples and code snippets help practitioners get started with generative AI on AWS. They describe the content quality as excellent, a great resource, and high-quality.

    AI-generated from the text of customer reviews


    Generative AI on AWS: Building Context-Aware Multimodal Reasoning Applications

    In recent years, generative artificial intelligence (AI) has emerged as a powerful tool for creating realistic and complex content, such as images, text, and audio. By training deep learning models on vast amounts of data, these AI systems can generate new content that is indistinguishable from human-created content.

    One exciting application of generative AI is in the realm of building context-aware multimodal reasoning applications. These applications have the ability to understand and reason about multiple types of data, such as images, text, and speech, in order to generate meaningful responses or actions.

    On Amazon Web Services (AWS), developers can leverage a variety of AI services, such as Amazon Rekognition for image analysis, Amazon Comprehend for natural language processing, and Amazon Polly for text-to-speech capabilities, to build context-aware multimodal reasoning applications.

    By combining these services with generative AI techniques, developers can create innovative applications that can understand and respond to user input in a more human-like manner. For example, a virtual assistant could analyze an image, read a text description, and generate a spoken response, all while taking into account the context of the conversation.

    Overall, generative AI on AWS opens up a world of possibilities for creating intelligent and context-aware applications that can understand and interact with users in a more natural and intuitive way. With the power of AWS AI services and generative AI techniques, developers can push the boundaries of what is possible in the world of AI-powered applications.
    #Generative #AWS #Building #ContextAware #Multimodal #Reasoning #Applications

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