HomeChipsetsIntel acquires Movidius to accelerate machine vision strategy

Intel acquires Movidius to accelerate machine vision strategy

Intel announced its intention to acquire machine vision specialist Movidius, to further strengthen its position within computer vision, deep learning.

In a move to strengthen its position in the growing computer vision market, Intel announced its intention to acquire machine vision specialist Movidius. Machine vision uses cameras to let machines visually process and understand their surroundings, enabling functions such as navigation and mapping, collision avoidance or object recognition.

The machine vision technology developed by Movidius, which is used today by the likes of DJI, FLIR, Google and Lenovo, is set to optimize and enhance Intel’s RealSense depth-sensing camera technology. It will provide Intel with low-power, high-performance system on a chip (SoC) platforms for accelerating computer vision applications. Specifically, Intel is looking to deploy Movidius’s technology within augmented, virtual and merged reality (AR/VR/MR), drones, robotics and digital security cameras.

“To amplify this paradigm shift, we completed several acquisitions in machine learning, deep learning and cognitive computing to build a suite of capabilities that open an entirely new world of possibilities: from recognizing objects, to understanding scenes; from authentication to tracking and navigating. This said, as devices become smarter and more distributed, we recognize that specific System on a Chip (SoC) attributes will be paramount to giving human-like sight to the 50 billion connected devices that are projected by 2020,” said Josh Walden, senior vice president and general manager of Intel’s New Technology Group. By acquiring Movidius, Intel also acquires algorithms developed for deep learning, depth processing, navigation and mapping, and natural interactions.

“Our leading VPU (Vision Processing Unit) platform for on-device vision processing combined with Intel’s industry leading depth sensing solution is a winning combination for autonomous machines that can see in 3D, understand their surroundings and navigate accordingly,” said Remi El-Ouazzane, CEO of Movidius.

The transaction is subject to customary approval conditions.

Automotive, virtual reality to drive growth in the computer vision market

The computer vision market is gaining momentum, driven by automotive and consumer applications such as virtual reality. In fact, the automotive sector is expected to surpass robotics and machine vision as the largest segment in 2016, according to Tractica. The analyst firm forecasts the computer vision hardware and software market will grow at a compound annual growth rate (CAGR) of 32.9 percent between 2015 and 2022, reaching revenues of $48.6 billion by 2022. This compares with revenues of $6.6 billion in 2015. Hardware will account for three-quarters of the revenue opportunity during the forecast period.

Enabling computers to see will bring semi-autonomous machines to the market. Building upon this, the folllowing step will be about bringing intelligence to these machines with computer vision, making truly autonomous machines a reality.

IIoT News Recap: Volvo starts testing driverless truck in Boliden mine; LoRaWan IoT network goes live in Australia; Softbank completes acquisition of ARM; Today’s forecast: Cellular M2M connections

machine vision

Autonomous driving: Volvo starts testing driverless truck in Boliden mine

As part of its ongoing global initiative to develop automation in mines, mining company Boliden has now started to test Volvo’s driverless trucks in its mine in Kristineberg. “We have a technology that allows our employees to stay at a safe distance, which provides a better working environment,” said Peter Burman, responsible for Boliden’s mine automation program. Besides Volvo, Boliden’s automation partners include Ericsson, Atlas Copco and ABB.

LPWAN: LoRaWan IoT network goes live in Australia

Sydney’s LoRaWan-based Internet of Things (IoT) network went live on Monday 5 September, activated by Australia’s Federal Minister for Communications and the Arts, senator the Hon Mitch Fifield, at the IoT “State-of-the-Nation”workshop and networking event. Based on LoRaWan and using the Industrial and Scientific Spectrum at 915MHz, the IoT network is the result of a partnership between KPMG, Meshed, IoTAA and International Towers Barangaroo. It will soon be connected to The Things Network. Anyone within a 3-5 kilometers’ radius will be able to connect IoT devices for free. Up to 1,000 devices will be supported by the gateway.

According to the IoTAA, IoT could contribute AUD$120 billion to the country’s economy by 2025. “This represents an uplift of up to 2 per cent in Australia’s GDP across a range of environments including factories, retail outlets smart cities and homes, motor vehicles, other transport modes and even human health and fitness – IoT is a pervasive disruptor,” said John Stanton, Communications Alliance CEO and Chair of the IoTAA Executive Council.

M&A: Softbank completes acquisition of ARM

It is now a done deal: Softbank Group’s acquisition of ARM was completed as of 5 September 2016. The acquisition means Softbank purchased all of ARM’s issued and to be issued for cash, for a total amount of £ 24.0 billion (approximately $31.0 billion). ARM will thereby be delisted from the London Stock Exchange as of 6 September 2016.

Today’s forecast: LTE to dominate cellular M2M connections by 2021

Ovum has looked into the various technologies –2G, 3G, 4G – ­ used for cellular machine-to-machine (M2M) connections and found that LTE will be the dominant technology in the long term, accounting for 212 million of the total 733 global cellular M2M connections by 2021. The number of 2G connections will be roughly the same, while 3G will account for 172 million connections. By 2021, total global cellular M2M service revenues will reach $67 billion, growing at a compound annual growth rate (CAGR) of 13.3 percent between 2016 and 2021. “Machine-type connections need to stay alive for many years and are not transitioned to new air interfaces as a matter of course. Doing so breaks the economics of deploying fully autonomous nodes. Instead, M2M contracts typically reach the end-of-life stage before any migration occurs. Consequently, 2G, specifically GSM, will persist for far longer in M2M,” said Jamie Moss, principal analyst in IoT, at Ovum.

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