Intel And The Swiss Startup Daedalean Have Collaborated To Provide A Reference Design For An AI Application That Passes Regulatory Tests, Enabling Companies To Integrate Certified Machine-Learned Computers Into Cockpits More Quickly.
The Two Companies Have Published A White Paper Outlining Their Reference Architecture And Providing Guidance On How To Ensure That ML-Based Systems Meet Computational And Certification Requirements While Adhering To Size, Weight, And Power (SWaP) Constraints.
Technical Product Marketing Manager At Intel Corporation Debra Aubrey Stated, “The Aviation Industry Still Requires A Reference Architecture As The Initial Step Towards A Future With Multidirectional Embedded Computational Equipment. Regulators Must Examine A Reference Architecture To Certify That It Will Produce Predictable And Safe Flight Behaviour.”
The White Paper Investigates The Difficulties Of Applying Software Assurance To Machine-Learned Devices, The Visual Awareness System They Employ, And The Current And Future Role Of Embedded Computing In The Industry. It Is The First Document To Ever Present A Working Example Of A Machine-Learned System And Provide Guidance On Overcoming Application Challenges.
Dr. Niels Haandbaek, Director Of Engineering At Daedalean, Stated, “The Approach Described In The Document Is Driving The Need For High-Performance Embedded Computing In The Aviation Industry. This Foundational Real-World Example Has The Potential To Foster A New Generation Of Airworthy Machine-Learning Applications.”
Intel And Daedalean Have Collaborated To Bring AI’s Capabilities To Avionics. When Incorporating Machine-Learned Applications Into Cockpits, Their White Paper Outlining The Reference Architecture For Certifiable Embedded Electronics Can Aid Businesses In Reducing Time-To-Market. This Document Provides Actionable Recommendations And Findings That Can Stimulate Industry Interest In High-Performance Embedded Computing.
Intel Corporation And Daedalean, A Swiss Startup Specialising In The Development Of Machine-Learning Solutions For The Aviation Industry, Have Announced The Release Of A White Paper That Presents A Reference Design For A Certifiable, Or Regulatory-Compliant, AI Application. The Document Explains How To Ensure That ML-Based Systems Can Meet Computational And Certification Requirements While Adhering To Size, Weight, And Power (SWaP) Constraints.
Technical Product Marketing Manager At Intel Corporation Debra Aubrey Stated, “Regulators Must Review A Reference Architecture In Order To Certify That It Will Produce Predictable, Safe Flight Behaviour.” This White Paper Discusses The Difficulties Of Applying Software Assurance To Machine-Learned Devices, The Visual Awareness System Employed, And The Current And Future Role Of Embedded Computing In The Industry. It Is The First Document Of Its Kind To Present A Working Example Of A Machine-Learned System And Offer Guidance On Overcoming Application Challenges.
Dr. Niels Haandbaek, Director Of Engineering At Daedalean, Stated, “The Approach Described In The Document Is Driving The Need For High-Performance Embedded Computing In The Aviation Industry. This Foundational Real-World Example Has The Potential To Foster A New Generation Of Airworthy Machine-Learning Applications.”
This White Paper Will Facilitate The Incorporation Of AI Into Avionics By Decreasing The Time-To-Market For Integrating Machine-Learned Computers Into Aircraft Cockpits. It Provides Recommendations And Findings That Can Drive The Industry’s Pursuit Of High-Performance Embedded Computing. Intel And Daedalean Hope That Their Reference Architecture Will Serve As A Starting Point For Other Firms Seeking To Develop Certifiable Machine-Learned Electronics And Applications For Use In Aviation.
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