MLPerf: An Industry Standard Performance Benchmark Suite for Machine LearningMLPerf
The rapid growth in the use of DNNs has spurred the development of numerous specialized processor architectures and software frameworks. System and application developers need reliable performance metrics to help them select processors and frameworks. Processor and framework developers need reliable performance metrics so that they can improve their products. This talk from Carole Jean Wu, Research Scientist at Facebook AI Research and an Associate Professor at Arizona State University, presents MLPerf, an industry-standard performance benchmark suite, and the design philosophies behind the benchmark suite and associated benchmarking methodologies.

Deploying AI Software to Embedded Devices Using Open StandardsCodeplay Software
AI software developers need to deploy diverse classes of algorithms in embedded devices, including deep learning, machine vision and sensor fusion. Adapting these algorithms to run efficiently on embedded devices typically involves using accelerator processors, such as GPUs or neural network accelerators. Quickly deploying high-performance AI algorithms to different processors requires open standards. There are a variety of open standards available to help: SYCL, OpenCL, SPIR-V, OpenMP, OpenVX and ONNX. This talk from Andrew Richards, Co-founder and CEO of Codeplay Software, presents proven workflows that combine these standards to enable AI software developed on a PC to run efficiently on a variety of embedded devices using accelerated programming models.


Opportunities for Vision in HealthcareWoodside Capital
With advances in computer vision, AI/ML and data analytics, the pace of technological change continues to accelerate. Nowhere has the confluence of those technologies been more impactful than in Digital Health. Healthcare is an almost $4 trillion industry and continues to grow every year. But by some estimates about 25% of the overall healthcare spend ($1T!) is wasted. This presentation from Vini Jolly, Executive Director at Woodside Capital, not only examines the investment trends in digital health, but also dives into the specific verticals and domains where startups are leveraging computer vision and AI to disrupt healthcare by addressing efficiency, efficacy and hopefully affordability.

A Computer Vision-Based Personal Trainer That Runs On Your PhoneTwentyBN
In this presentation, Roland Memisevic, CEO, Chief Scientist and Founder of Twenty BN, describes his company’s journey towards building an AI-powered personal trainer that runs on your phone. The trainer takes the form of an on-screen avatar that watches and listens to you using the phone’s camera and microphone. This allows it to provide feedback on your form and to continuously adapt your training plan as a function of your effort, form and progress. Memisevic describes the challenges behind creating the real-time on-device AI system that powers the avatar’s behaviors and the data generation efforts that went into training it.


How Battery-powered Intelligent Vision is Bringing AI to the IoT – Eta Compute Webinar: October 5, 2021, 9:00 am PT

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BlinkAI Technologies Night Video (Best Edge AI Software or Algorithm)BlinkAI Technologies
BlinkAI Technologies’ Night Video is the 2021 Edge AI and Vision Product of the Year Award Winner in the Edge AI Software and Algorithms category. Night Video is the world’s first AI-based night video solution for smartphones. BlinkAI’s deep learning software elevates the low-light performance of smartphone native camera hardware to bring unprecedented detail and vibrancy to smartphone nighttime videos. BlinkAI’s proprietary solution is able to instantly enhance each short-exposure, high-noise video frame, using a unique spatiotemporal neural network that is exceptionally power efficient, only consuming 250 mW when deployed on neural network hardware accelerators. By enabling any camera to see at 5-10X lower illumination than previously possible, BlinkAI Night Video also dramatically improves downstream computer vision tasks such as object detection in low-light conditions. And beyond the smartphone market, BlinkAI is also actively collaborating with leading companies in the automotive, robotics, and surveillance industries interested in applying Night Video to their computer vision tasks.

Please see here for more information on BlinkAI Technologies and Night Video. The Edge AI and Vision Product of the Year Awards celebrate the innovation of the industry’s leading companies that are developing and enabling the next generation of edge AI and computer vision products. Winning a Product of the Year award recognizes a company’s leadership in edge AI and computer vision as evaluated by independent industry experts.


Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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