Intel Speeds AI Development, Deployment and Performance with New Class of AI Hardware from Cloud to Edge :: Intel Corporation (INTC)
Blog: Aldec Blog - How to develop high-performance deep neural network object detection/recognition applications for FPGA-based edge devices - FirstEDA
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
Are ASIC Chips The Future of AI?
The New Deep Learning Memory Architectures You Should Know About — eSilicon Technical Article | ChipEstimate.com
How to Choose Hardware for Deep Learning Inference
How to make your own deep learning accelerator chip! | by Manu Suryavansh | Towards Data Science
Processing AI at the Edge: GPU, VPU, FPGA, ASIC Explained - ADLINK Blog
Are ASIC chips going to be the future of AI? | ASIC chips
FPGA Based Deep Learning Accelerators Take on ASICs
Comparison of neural network accelerators for FPGA, ASIC and GPU... | Download Scientific Diagram
8-Bit Precision for Training Deep Learning Systems | IBM Research Blog
Accelerate Deep Learning Applications Using FPGAs Course
My take on the Gartner Hype Cycle | by Jens Møllerhøj | Medium
A Breakthrough in FPGA-Based Deep Learning Inference - EEWeb
An on-chip photonic deep neural network for image classification | Nature
AI Special Feature: “The Cyborg Will See You Now” – PharmaLive
How to Develop High-Performance Deep Neural Network Object Detection/Recognition Applications for FPGA-based Edge Devices - Embedded Computing Design
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Deep Learning Has Hit a Wall, Intel's Rao Says
FPGA Based Deep Learning Accelerators Take on ASICs
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
Cisco Tech Blog | AI 2.0 - Episode #1, Introduction
Processing AI at the Edge: GPU, VPU, FPGA, ASIC Explained - ADLINK Blog
FPGA-based Accelerators of Deep Learning Networks for Learning and Classification: A Review
FPGA Based Deep Learning Accelerators Take on ASICs
Hardware for Deep Learning. Part 4: ASIC | by Grigory Sapunov | Intento
