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    Edge AI accelerates with Micron

    AI at the edge of everything

    They say the edge is the end, a boundary, a border, a limit. But what if the edge is where AI experience begins? Learn how Micron's technology doesn't just store data on your devices; but accelerates the transformation of data into actionable intelligence.

    Experience AI on the edge
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    We accelerate the transformation of data into intelligence​

    AI is everywhere

    AI is expanding from the cloud to where data lives on edge devices. Micron enables AI in the cloud, on the edge and at every step along the way.

    More, faster, better

    AI needs more memory and storage that is faster and more efficient in the cloud, in data centers and on edge devices.

    Your trusted advisor for edge AI

    Our partners trust us to tackle their AI data challenges with industry-leading memory and storage solutions that accelerate the AI revolution.

    5 things you need to know about edge AI

    The AI industry is evolving fast. It can be hard to keep up on what’s new and what is next. Read this article to find out what you need to know about AI from the cloud to edge devices, how memory and storage are key to the success of AI and how Micron is pushing the edge of innovation.

    Read the article
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    The opportunity and growth of edge AI

    Memory and storage products for AI applications

    Micron’s portfolio of power-efficient memory and storage solutions enables edge AI, from cars and phones to PCs and beyond.

    Lean in and look over the edge

    Find more information about how Micron supports edge markets & industries.

    Frequently asked questions

    AI begins with data, and data starts on the edge. Much of the data used for data center AI training is captured on edge devices. AI will leverage both cloud and edge computing through a distributed AI model to provide more efficient and scalable solutions. Traditionally, AI processing has been centralized in large data centers, but the demand for real-time applications has led to the rise of distributed AI. This approach enables on-device decision-making by processing data locally on edge devices while utilizing the cloud for large-scale computations and model training.  It also ensures that AI capabilities are accessible and effective in diverse environments. Micron's advanced memory and storage solutions, such as high-bandwidth memory (HBM) and LPDDR5X, are crucial in supporting this hybrid approach, ensuring efficient, scalable and responsive AI operations across diverse environments.

    Memory is crucial for AI because it enables rapid access to vast amounts of data. essential for training complex models and making real-time decisions. Without data there is no AI. To unlock AI’s full potential, data must be stored, moved and processed with incredible speed and efficiency — cloud to edge. Micron’s high-performance memory solutions ensure AI systems can handle large datasets and perform computations quickly, leading to more accurate outcomes.

    Storage is essential for AI as it provides the infrastructure to manage the world’s data efficiently. Micron’s high-performance storage solutions ensure rapid data access and the capacity to hold the world’s data, enabling AI systems to handle large datasets swiftly and make intelligent decisions. Having rapid access to data accelerates AI innovation across various AI applications.

    The market for AI on edge devices is experiencing substantial growth. Gartner estimates that in 2025, about 75% of enterprise-generated data will be created and processed outside traditional centralized data centers or clouds, compared to about 10% in 2018. This remarkable shift reflects the increasing adoption of edge AI in automotive, mobile phones, and AI PCs, driven by the need for real-time data processing and improved efficiency. In 2024, the edge AI market was valued at approximately US$ 12.5 billion and is projected to grow at a compound annual growth rate (CAGR) of 24.8% from 2025 to 2034, reaching US$ 109.4 billion by 2034. This growth is fueled by advancements in neural network technology, the proliferation of AI-enabled devices and the demand for efficient and secure data processing.

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