See how we deliver cloud-level AI inference performance at the edge, with orders of magnitude better energy efficiency and processing speed - while drastically reducing customer operating costs.
Talk with us at DSEI Japan.
Are you exploring Edge AI for Defense Applications?
Meet the EdgeCortix team in person at DSEI Japan from March 15 - 17, 2023, in Makuhari Messe, Chiba, Japan, where we will be in Booth H8-320! We'll be demonstrating the EdgeCortix Edge AI platform and how developers can easily move applications from GPU-based platforms to SWaP-C-optimized solutions.
Also, we will be presenting a live seminar session on how edge AI is reshaping the defense industry today, featuring Stan Crow, EdgeCortix’s SVP of Defense and Space Technology, and Professor Tomoyuki Furutani of Keio University, Faculty of Policy Management and the head of the Drone Social Co-Creation Consortium at Keio University. Topics they will cover:
Today's geopolitical environment and modern warfare
Why edge computing and edge AI technology is now mission-critical
A path forward for Japan and its allies and partners – and how academia, government, and industry should work together on edge AI concepts
DSEI Japan attendees: Schedule a one-on-one meeting with an EdgeCortix team member to see a demonstration or learn more about edge AI in defense.
Not at the conference? Meet with us virtually for the same insights. Either way, we look forward to seeing you and discussing your ideas.
Latest Blog: Connecting Edge AI Software with PyTorch, TensorFlow Lite, and ONNX
PyTorch, TensorFlow, and ONNX are familiar tools for many data scientists and AI software developers. Using the EdgeCortix MERA compiler, models can move to an edge AI chip or FPGA with no retraining and automatic hardware configuration.
AI Hardware Summit: Software, the Elephant in the Room for Edge-AI Hardware Acceleration
Companies today are focused on trying to deliver peak efficiency in machine learning inference (ML) by encouraging customers to move to purpose-built accelerators for ML inference. While this is directionally correct, oftentimes hardware specific solutions are unable to match customers’ performance and efficiency goals. The issue, solving for ‘peak efficiency’ cannot be accomplished by simply throwing a combination of silicon and power at the problem; this is especially true at the edge.
See more of these insights in a fireside conversation between Sakya Dasgupta, our Founder & CEO, and Mike Demier, Semiconductor Technology Analyst.
Partner Solution: EdgeCortix Inference Pack on BittWare FPGA Accelerator Cards
Accelerate ML projects with EdgeCortix DNA IP in ready-to-use bitstreams for BittWare IA-840F and IA-420F cards featuring high-performance Intel® Agilex™ FPGAs.
