Intel Movidius Vision Processing Units (VPUs) Alternatives

Accelerates AI compute tasks, offloading from CPU and GPU, while enabling high-performance, low-power computer vision and deep learning inference for various applications.
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Hailo

If you're looking for an alternative to Intel Movidius Vision Processing Units (VPUs), Hailo is a good option. The Israeli company's AI processors are geared for edge devices, where they can handle high-resolution video and other data processing and analysis. The Hailo-15 family in particular is suited for deep learning tasks, with low latency and high accuracy, and is a good candidate for computer vision tasks.

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Coral

Another contender is Coral, a local AI platform that lets developers run AI tasks quickly, privately and efficiently on the device. Coral's products support frameworks like TensorFlow Lite and are balanced between power consumption and performance, making it a good fit for smart cities, manufacturing and health care, where data privacy and low latency are important.

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Numenta

If you need high-performance AI compute but also need scalable infrastructure, Numenta offers a system to run large AI models on CPUs. Its NuPIC system can optimize performance in real time, accommodate multiple customers, and scale easily, which makes it a good fit for gaming and document retrieval. It's also a relatively cheap option for businesses that want to tap into AI without the expense of GPUs.

More Alternatives to Intel Movidius Vision Processing Units (VPUs)

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Run:ai

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Groq

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Lambda

Provision scalable NVIDIA GPU instances and clusters on-demand or reserved, with pre-configured ML environments and transparent pricing.

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Salad

Run AI/ML production models at scale with low-cost, scalable GPU instances, starting at $0.02 per hour, with on-demand elasticity and global edge network.

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AIxBlock

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AMD

Accelerates data center AI, AI PCs, and edge devices with high-performance and adaptive computing solutions, unlocking business insights and scientific research.

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Edge Impulse

Develop, optimize, and deploy AI models directly on edge devices, leveraging high-quality datasets and hardware-agnostic tools for efficient performance.

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ZETIC.ai

Brings AI capabilities directly to devices, eliminating cloud server costs and ensuring top performance, energy efficiency, and enhanced data security.

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Eyeson One View

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ThirdAI

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UbiOps

Deploy AI models and functions in 15 minutes, not weeks, with automated version control, security, and scalability in a private environment.

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Twelve Labs

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NVIDIA

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VideoProc

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Daily

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LastMile AI

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Google AI

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Clarifai

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Cisco AI Solutions

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NVIDIA AI Platform

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Cerebras

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