Pre-Release Technical Specs
Intended for early partners, OEMs, and design-in evaluation.
Exploring NE-1000
Key Features and Benefits
| Ultra-Low Power Consumption | Typical 0.1W (idle) to 1.0W (peak) for edge AI workloads. |
| High Compute Performance | 50 TOPS (8-bit equivalent) for LLM and edge AI models. |
| Massive Parameter Storage | Up to 50B parameters via 3D Memristor stacking. |
| Real-Time On-Chip Learning | STDP-based continuous learning without cloud dependency. |
| Memristor-SNN Hybrid Architecture | Combines SNN and memristor for ultra-efficient AI tasks. |
| Dynamic Precision Handling | 1-bit to 8-bit mixed precision for optimized AI performance. |
| Small Form Factor | Compact, stackable edge AI module. |
| Secure & Private AI Processing | On-device learning compliant with HIPAA and GDPR. |
| Industrial Grade Reliability | Designed for sustained operation in demanding environments. |
| Cost Efficiency | Estimated $0.5/TOPS, suitable for large-scale deployment. |