Build Smarter Defect Detection Systems with FPGA-based AI
Learn How Low-Cost FPGAs Outperform GPUs for a Common Industrial Edge-AI Application
Results showing how MAX® 10 FPGAs
Outperform Nvidia’s Jetson Orin Nano
Outperform Nvidia’s Jetson Orin Nano
488x
Lower Latency
24x
Higher Accuracy
20x
Lower Power
6x
Lower Cost
AI is transforming defect detection—but not all solutions are created equal. This exclusive white paper reveals how Altera’s MAX® 10 FPGAs, combined with ONE WARE’s ONE AI Platform, outperform Jetson Orin Nano in power, cost, latency, and performance.
Designed for engineers and product teams in industrial automation, robotics, and manufacturing, this paper provides the data, benchmarks, and architecture insights to make smart decisions— without overhauling your existing systems.
What You’ll Learn:
- How to integrate AI directly into the existing FPGA design
- Real-world benchmark comparisons: MAX 10 FPGA vs. Jetson Orin Nano GPU
- Design flow and performance metrics using quantization-aware AI
- Why MAX 10 devices are a power- and cost-efficient platform for edge inference
- Case study: AI-enhanced quality inspection in extrusion machines
Resources
- Choose a MAX 10 FPGA-Based Board
- Easily deploy these boards into custom applications or integrate them as a component in broader system designs.
- Choose a Power and Cost-Optimized FPGA Device
- Select the best FPGA to meet your requirements.
- One Ware, a new Altera Solution Acceleration Partner
- Integrate AI into existing systems using FPGAs with ONE WARE’s ONE AI Platform—designed for fast, scalable deployment.
