computer science

Movidius

Movidius is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Movidius rather than just read about it. In short: Movidius Ltd. was a company based in San Mateo, California, that designed low-power processor chips for computer vision. The company was acquired by Intel in September 2016, who continues to sell the company's products under the Movidius line.

Key takeaways

Movidius belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Movidius to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Movidius from memory before moving on to harder problems.

Reference excerpt

Movidius Ltd. was a company based in San Mateo, California, that designed low-power processor chips for computer vision. The company was acquired by Intel in September 2016, who continues to sell the company's products under the Movidius line.

Company history

Movidius was co-founded in 2005 by Sean Mitchell, David Moloney, and Val Muresan in Dublin, Ireland. Between 2006 and 2016, it raised nearly $90 million in capital funding. In May 2013, the company appointed Remi El-Ouazzane as CEO. In January 2016, the company announced a partnership with Google. Movidius has been active in Google's Project Tango, and in September 2016 it was announced that Intel planned to acquire the company.

Products

Myriad 2 The company's Myriad 2 chip is a manycore vision processing unit that can function on power-constrained devices. The Fathom is a USB stick containing a Myriad 2 processor, allowing a vision accelerator to be added to devices using ARM processors including PCs, drones, robots, IoT devices and video surveillance for tasks such as identifying people or objects. It can run at between 80 and 150 GFLOPS on 1W of power.

Myriad X Intel's Myriad X VPU (vision processing unit) is the third generation VPU from Movidius. It uses a Neural Compute Engine, a dedicated hardware accelerator—for neural network deep-learning inferences.

Neural Compute Stick

The Intel Movidius Neural Compute Stick (NCS) is a compact device designed to facilitate the development of deep learning applications at the network edge. It utilizes the Intel Movidius Myriad 2 Vision Processing Unit (VPU), which is also found in various smart devices like security cameras, gesture-controlled drones, and industrial machine vision systems. The NCS supports frameworks such as TensorFlow and Caffe for developing neural network models. The second iteration, the Intel Neural Compute Stick 2 (NCS 2), was introduced on November 14, 2018, at the AI DevCon event in Beijing. This version is based on the Myriad X VPU, which significantly improves performance over the original, providing up to eight times the processing capability for AI inference tasks. The NCS 2 is designed to work seamlessly with the Intel Distribution of OpenVINO toolkit, which helps developers optimize and deploy their models efficiently. The NCS connects to a host machine via a USB interface, allowing developers to rapidly prototype and deploy deep neural network applications without the need for cloud connectivity. This makes it suitable for various real-time, low-power applications where efficient on-device processing is essential.

Uses Google Clips camera uses Myriad 2 VPU. The Intel RealSense Tracking Camera T265 uses the Myriad 2. In 2016, Mavic incorporated the Myriad 2 VPU in all its consumer drones. The Ryze Tello affordable programmable drone, licensing Mavic Software, uses the Myriad 2 VPU. ComBox Technology uses Myriad X in ComBox x64 PCIe Blad board for CNN inference in DC. TiltFive AR Glasses use a Movidius Myriad X to compute the reprojection to show the user

See also MPSoC Coprocessor Convolutional neural network

References

Illustrations

Logo of Intel Movidius since 2020

Worked examples

Example 1 — a first encounter with Movidius

Start with the simplest possible case. Write down what Movidius claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Movidius before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Movidius ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Movidius

In research: Movidius appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Movidius in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Movidius is common in secondary-school and first-year university syllabi. It links to neighbouring topics 2016 mergers and acquisitions, Companies based in San Mateo, California, Defunct computer companies of the United States, so understanding it makes those chapters shorter.
In everyday life: Look for Movidius outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Movidius in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Movidius means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Movidius out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Movidius in simple terms?

Why does Movidius matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Movidius?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Movidius.