ADI正在展示其将大型AI模型能力从云端下沉到边缘设备的技术路径,核心是通过模型蒸馏、定制化协同设计芯片等手段实现高效推理。同时,ADI正为机器人社区构建开源的基准测试与物理排行榜,并致力于开发多模态触觉传感器、高保真仿真资产等,以最小化仿真与现实之间的差距。这体现了其从系统层面推动硬件协同创新与数据采集的生态化产品战略。
The full chat with Mishek Musa on how ADI is shrinking inference down to the edge and setting up physical leaderboards for the robotics community.
Chapters: 0:00 - Introduction & ADI's Emerging Tech Hub 0:56 - Inside the Multimodal Tactile Sensor 1:52 - Automating Data Center Maintenance 2:28 - Open-Source Robotics Benchmarks 3:24 - High-Fidelity Simulation Assets 4:00 - The System-Level Product Strategy 4:37 - Data Collection & Minimizing the Sim-to-Real Gap 5:53 - Co-Innovation Hub Collaborations 6:30 - Distilling Large Models for Edge Inference 7:47 - Custom Co-Designed Silicon vs. Generic GPUs 8:59 - Wrap-Up & Concluding Thoughts