This blog post was originally published at PerceptiLabs’ website. It is reprinted here with the permission of PerceptiLabs. One group of scientists leveraging ML is the Buchser lab at Washington University in Saint Louis School of Medicine in the Department of Genetics. There, Dr. Buchser and his team are working in functional genomics, High-Throughput Screening, […]
Case Study: Genetic Screening Using CNNs in PerceptiLabs Read More +
This blog post was originally published at AImotive’s website. It is reprinted here with the permission of AImotive. The aiSim team adapted the Hardware-In-the-Loop testing approach with a unique spin on the concept that allows for testing complete automated driving systems with live simulated sensor data without any prerecorded footage. In this post, we will
End-to-end HiL Testing with aiSim to Maximize Coverage Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. The most commonly diagnosed cancer in the US today is skin cancer. There are three main variants: melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). Though melanoma only accounts for roughly 1% of all skin
Building Real-time Dermatology Classification with NVIDIA Clara AGX Read More +
This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. Edge computing is emerging as the next transformational technology across industries—and its rapid growth is only increasing. In fact, Gartner suggests that by 2025, over 75% of data will be created and processed outside centralized data centers.
Intel Smart Edge: Unleashing Services at the Edge Read More +
This blog post was originally published by NXP Semiconductors. It is reprinted here with the permission of NXP Semiconductors. Edge intelligence is one of the most disruptive innovations since the advent of the Internet of Things (IoT). While the IoT gave rise to billions of smart, connected devices transmitting countless terabytes of sensor data for
This blog post was originally published at Syntiant’s website. It is reprinted here with the permission of Syntiant. One of my great professional privileges when founding Syntiant’s machine learning stack has been collaborating with a team of electrical engineers in the design, development, verification, and shipping of an ultra-power efficient tensor computation core for Syntiant
The Growing Syntiant Core Family Read More +
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Combining machine learning and classical algorithms through neural augmentation for combinatorial optimization Machine learning (ML) is transforming industries, improving products, and enhancing everyday life for consumers. You should think of ML as a horizontal technology that will
Why Machine Learning is a Powerful Tool, Even Without Data Read More +
Paper cut cloud looking at the clouds (Image by rawpixel from Pixabay) This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Edge Computing market size is expected to reach USD 29 billion by 2025. In this decade there has been a transformational movement from on-premise Computing
You Need to Move from Cloud Computing to Edge Computing Now! Read More +
This blog post was originally published at Ambarella’s website. It is reprinted here with the permission of Ambarella. Onboard security is mandatory for today’s embedded processors. Our vision SoCs perform critical tasks in automotive safety, video security, and other AI camera applications where environmental perception—seeing and interpreting the world—plays a pivotal role. From front ADAS
Cybersecurity Designed For the Edge Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Researchers from NVIDIA, University of Texas at Austin and Caltech developed a simple, efficient, and plug-and-play uncertainty quantification method for the 6-DoF (degrees of freedom) object pose estimation task, using an ensemble of K pre-trained estimators with
NVIDIA Research: Fast Uncertainty Quantification for Deep Object Pose Estimation Read More +
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