12-24-2025, 05:43 AM
I'm leading a small startup developing edge computing devices for industrial IoT, and we're hitting a wall with our current processor's ability to handle real-time machine learning inference. We need to upgrade to a dedicated AI chip but are overwhelmed by the options from NVIDIA, Intel, and newer players. For engineers who have integrated specialized AI chips into hardware products, what were the key factors in your selection, balancing raw TOPS performance with power efficiency, thermal design, and software stack maturity? How did you navigate the trade-offs between developing for a proprietary ecosystem versus a more open architecture, and what was the actual timeline from prototyping to stable deployment?