Technical Meeting: Cloud Platform Considerations for Automotive Product Development

#Cloud #Tensorflow #automotive #products #development #standards #IOT #Amazon #Glue #Alex #FaceBook #OSquery #machine #learning #EC2 #MongoDB #Atlas #serverless #computing #functional #to #compute #engines
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Cloud Platform Considerations for Future Automotive Product Development


Vehicle Development platforms for new automotive products will change substantially over the next few years.  Traditional platforms are highly limited in areas of incorporating machine learning, AI development, IOT integration, V-I public cloud integration, AI-based security systems to protect the product development ecosystem, etc.  Most existing automotive platforms are best-of-breed, integrated stacks that are designed from traditional IT products and services.  Much of the productivity and efficiency improvements that have been implemented by major cloud providers are not realized in these vehicle development platforms.

During the hour, considerations and recommendations will be presented that build upon configurable platform elements that manage different platform capabilities - IOT/sensors, machine learning, computing methods (traditional CPU, graphic processor cards, FPGAs, and ASICs), key technology standards, and a profile of skills that will be necessary to develop and operate these next generation platforms.  These platforms will also incorporate new software capabilities emerging in the cloud that can dramatically improve automotive product quality, speed and productivity requirements. Examples include Amazon Glue (collection of Python scripts that automatically crawls IOT data sources and apply data organization and transforms before storing), Amazon Alexa (voice recognition & control) adapted to automotive, Google’s TensorFlow (software and hardware to improve machine learning/AI), Amazon EC2 P2 Chips to create/train deep neural networks for on-demand infrastructure,  functional to functional compute engines (e.g., serverless computing), Amazon MongoDB Atlas (distribute replicas across multiple availability zones (e.g., 3, 5, 7), and Facebook’s OSquery (provide real time, reliable visibility into systems running throughout your network to quickly identify and investigate anomalies). Challenges related to creating/managing these platforms will also be presented. Finally, considerations that identify which platform elements should be available in the vehicle, in the cloud, and in-both will be presented.



  Date and Time

  Location

  Hosts

  Registration



  • Date: 15 Feb 2017
  • Time: 06:00 PM to 07:30 PM
  • All times are (GMT-05:00) US/Michigan
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  • EC 116, Engineering Center
  • Oakland University
  • Rochester, Michigan
  • United States 48309-4479
  • Building: Engineering Center
  • Room Number: EC 116
  • Click here for Map

  • Contact Event Host
  • Co-sponsored by Subramaniam Ganesan
  • Starts 28 January 2017 12:00 AM
  • Ends 15 February 2017 03:12 PM
  • All times are (GMT-05:00) US/Michigan
  • No Admission Charge


  Speakers

Bill Bone Bill Bone of CloudSAFE

Topic:

Cloud Platform Considerations for Automotive Product Development

Vehicle Development platforms for new automotive products will change substantially over the next few years.  Traditional platforms are highly limited in areas of incorporating machine learning, AI development, IOT integration, V-I public cloud integration, AI-based security systems to protect the product development ecosystem, etc.  Most existing automotive platforms are best-of-breed, integrated stacks that are designed from traditional IT products and services.  Much of the productivity and efficiency improvements that have been implemented by major cloud providers are not realized in these vehicle development platforms.


During the hour, considerations and recommendations will be presented that build upon configurable platform elements that manage different platform capabilities - IOT/sensors, machine learning, computing methods (traditional CPU, graphic processor cards, FPGAs, and ASICs), key technology standards, and a profile of skills that will be necessary to develop and operate these next generation platforms.  These platforms will also incorporate new software capabilities emerging in the cloud that can dramatically improve automotive product quality, speed and productivity requirements. Examples include Amazon Glue (collection of Python scripts that automatically crawls IOT data sources and apply data organization and transforms before storing), Amazon Alexa (voice recognition & control) adapted to automotive, Google’s TensorFlow (software and hardware to improve machine learning/AI), Amazon EC2 P2 Chips to create/train deep neural networks for on-demand infrastructure,  functional to functional compute engines (e.g., serverless computing), Amazon MongoDB Atlas (distribute replicas across multiple availability zones (e.g., 3, 5, 7), and Facebook’s OSquery (provide real time, reliable visibility into systems running throughout your network to quickly identify and investigate anomalies). Challenges related to creating/managing these platforms will also be presented. Finally, considerations that identify which platform elements should be available in the vehicle, in the cloud, and in-both will be presented.


 

Biography:

Bill is currently VP, Product Development, of CloudSAFE in Southfield, MI.  In this position, he leads the product management functions for product launches including technical marketing, customer innovation, portfolio management, and NPDI process.  Previously, Bill was CTO, Automotive, for Aras Corp.  In this positon, he was responsible for driving innovation through Aras’s customer, partner, and vendor initiatives to create world-class product management solutions for the automotive engineering and manufacturing industry.  In addition, he led Aras’ Community for Automotive Innovation Center focusing on open-community initiatives for complex configurable vehicle product options/variants and vehicle virtual validation solutions. Prior to this position, Bill was Director, Global Infrastructure Strategy for GM.  Bill previously worked for HP/EDS as an HP Fellow and Chief Technologist for the Manufacturing, Engineering, and Life Sciences industries. He is active in ACM, IEEE, SNIA, and SME professional organizations.

Email:

Bill Bone of CloudSAFE

Topic:

Cloud Platform Considerations for Automotive Product Development

Biography:

Email:






Agenda

6:00 PM - Welcome and Introductions, Chapter business update

6:15 PM - Technical Talk

7:15 PM - Q & A

7:30 PM - Wrap Up

7:30 to close - Networking 

 



A Joint Oakland University/IEEE Computer Society SEM Chapter Presentation