2020 in Review With Sheldon Fernandez
Synced has invited Mr. Sheldon Fernandez to share his insights about the current development and future trends of artificial intelligence.
Tag: DarwinAI
TinySpeech: Novel Attention Condensers Enable Deep Recognition Networks on Edge Devices
Novel attention condensers designed to enable the building of low-footprint, highly-efficient deep neural networks for on-device speech recognition on the edge.
Pandemics don’t wait: How we built COVID-Net in under 7 days
Rather than simply treating AI as a tool to be leveraged, this approach reimagines AI as a collaborator that learns from a developer’s needs and subsequently proposes multiple design approaches with different trade-offs in order to enable a rapid and iterative approach to model building.
DarwinAI Open-Sources COVID-Net as Medical Imaging in COVID-19 Diagnosis Debate Continues
Researchers recently developed and open-sourced COVID-Net, a convolutional neural network for detecting COVID-19 through chest radiography.
AttoNets: Compact and Efficient DNNs Realized via Human-Machine Collaboration
It is no secret that deep neural networks (DNNs) can achieve state-of-the-art performance in a wide range of complicated tasks. DNN models such as BigGAN, BERT, and GPT 2.0 have proved the high potential of deep learning. Deploying DNNs on mobile devices, consumer devices, drones and vehicles however remains a bottleneck for researchers.
Can a Canadian AI Startup Challenge Google in AutoML?
Enter DarwinAI, a Waterloo, Ontario based AI startup which recently released a beta version of an automated machine learning solution it says can generate models ten times more efficiently than comparable state-of-the-art solutions.