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The challenges for system architects developing edge artificial intelligence (AI) systems is delivering sufficient computing performance while satisfying environmental hardening and stringent size, weight, and power (SWaP) constraints. Addressing these challenges, the ADLINK DLAP-3000-CF gives system developers the flexibility they need to cost-effectively achieve the right mix of SWaP and AI performance. Download the DLAP-3000-CF solution brief to learn why there is no need to buy a server to run AI inferencing, facial recognition, object detection, or many other AI-based applications at the edge.
Key Takeaways
- Challenges for space-constrained AI applications
- Many options for scaling AI performance
- Thermally-optimized and industrial-grade system design
- Use cases requiring optimized SWaP and AI performance
keyword: MXM, GPU, DLAP, deep learning, AI inference, Turing, Quadro, RTX, NVIDIA, edge AI, edge computing