• Home
  • About Us
  • Contact Us
  • Privacy Policy
  • Special Offers
Business Intelligence Info
  • Business Intelligence
    • BI News and Info
    • Big Data
    • Mobile and Cloud
    • Self-Service BI
  • CRM
    • CRM News and Info
    • InfusionSoft
    • Microsoft Dynamics CRM
    • NetSuite
    • OnContact
    • Salesforce
    • Workbooks
  • Data Mining
    • Pentaho
    • Sisense
    • Tableau
    • TIBCO Spotfire
  • Data Warehousing
    • DWH News and Info
    • IBM DB2
    • Microsoft SQL Server
    • Oracle
    • Teradata
  • Predictive Analytics
    • FICO
    • KNIME
    • Mathematica
    • Matlab
    • Minitab
    • RapidMiner
    • Revolution
    • SAP
    • SAS/SPSS
  • Humor

Hailo partners with Foxconn to build edge device for AI inference

May 13, 2020   Big Data
 Hailo partners with Foxconn to build edge device for AI inference

AI startup Hailo today announced that it’s teaming up with Foxconn and system-on-chip provider Socionext to launch BOXiedge, an edge computing processing solution for video analytics. If the companies’ claims bear out, BOXiedge could deliver “market-leading” energy efficiency for AI inference, benefiting applications like industrial internet of things, smart cities, and smart medical.

BOXiedge is the successor to a mini server Foxconn teamed up with Network Optix to launch in January, which confusingly shares the same name. Unlike the previous server, this new BOXiedge can perform image classification, detection, pose estimation, and other tasks on footage from up to 20 cameras simultaneously thanks to SocioNext’s SynQuacer SC2AA chip and Hailo’s Hailo-8 processor, which features an architecture that consumes less power than rival chips while incorporating memory, software control, and a heat-dissipating design.

Under the hood of the Hailo-8, resources including memory, control, and compute blocks are distributed throughout the whole of the chip, and Hailo’s software — which supports Google’s TensorFlow machine learning framework and ONNX (an open format built to represent machine learning models) — analyzes the requirements of each AI algorithm and allocates the appropriate modules.

Hailo-8 is capable of 26 tera-operations per second (TOPs), which works out to 2.8 TOPs per watt. In a recent benchmark test conducted by Hailo, the Hailo-8 outperformed hardware like Nvidia’s Xavier AGX on several AI semantic segmentation and object detection benchmarks, including ResNet-50. At an image resolution of 224 x 224 pixels per inch, it processed 672 frames per second compared with the Xavier AGX’s 656 frames and sucked down only 1.67 watts (equating to 2.8 TOPs per watt) versus the Nvidia chip’s 32 watts (0.14 TOPs per watt).

VB Transform 2020 Online – July 15-17: Join leading AI executives at the AI event of the year. Register today and save 30% off digital access passes.

The edge AI hardware market is anticipated to be worth $ 1.15 billion by 2023, and Hailo — which raised $ 60 million in March — is hoping to beat rivals to the punch. Startups AIStorm, Esperanto Technologies, Quadric, Graphcore, Xnor, and Flex Logix are developing chips customized for AI workloads. Mobileye, the Tel Aviv company Intel acquired for $ 15.3 billion in March 2017, offers a computer vision processing solution for autonomous vehicles in its EyeQ product line. Baidu in July unveiled Kunlun, a chip for edge computing on devices and in the cloud via datacenters. And Chinese retail giant Alibaba launched an AI inference chip for autonomous driving, smart cities, and logistics verticals in the second half of 2019.

Foxconn is one of Hailo’s first publicly disclosed customers after NEC and ABB Technology. Previously, the startup said it’s working to build Hailo-8 into products from OEMs and tier-1 automotive companies in fields such as advanced driver-assistance systems (ADAS) and industries like robotics, smart cities, and smart homes.

Let’s block ads! (Why?)

Big Data – VentureBeat

Build, Device, edge, Foxconn, Hailo, inference, Partners
  • Recent Posts

    • Experimenting to Win with Data
    • twice-impeached POTUS* boasts: “I may even decide to beat [Democrats] for a third time”
    • Understanding Key Facets of Your Master Data; Facet #2: Relationships
    • Quality Match raises $6 million to build better AI datasets
    • Teradata Joins Open Manufacturing Platform
  • Categories

  • Archives

    • March 2021
    • February 2021
    • January 2021
    • December 2020
    • November 2020
    • October 2020
    • September 2020
    • August 2020
    • July 2020
    • June 2020
    • May 2020
    • April 2020
    • March 2020
    • February 2020
    • January 2020
    • December 2019
    • November 2019
    • October 2019
    • September 2019
    • August 2019
    • July 2019
    • June 2019
    • May 2019
    • April 2019
    • March 2019
    • February 2019
    • January 2019
    • December 2018
    • November 2018
    • October 2018
    • September 2018
    • August 2018
    • July 2018
    • June 2018
    • May 2018
    • April 2018
    • March 2018
    • February 2018
    • January 2018
    • December 2017
    • November 2017
    • October 2017
    • September 2017
    • August 2017
    • July 2017
    • June 2017
    • May 2017
    • April 2017
    • March 2017
    • February 2017
    • January 2017
    • December 2016
    • November 2016
    • October 2016
    • September 2016
    • August 2016
    • July 2016
    • June 2016
    • May 2016
    • April 2016
    • March 2016
    • February 2016
    • January 2016
    • December 2015
    • November 2015
    • October 2015
    • September 2015
    • August 2015
    • July 2015
    • June 2015
    • May 2015
    • April 2015
    • March 2015
    • February 2015
    • January 2015
    • December 2014
    • November 2014
© 2021 Business Intelligence Info
Power BI Training | G Com Solutions Limited