Instances U250 – 4 Instances Amazon F1 ˃ ~1536 DSPs @ 700MHz Execution Controller Spill / Restore DMA Controller Weights DMA Controller Systolic Array Bias ReLU Bias ReLU Bias ReLU Bias ReLU Pooling 80% 100% VGG16 ResNet-50 GoogleNet-V3 Aristotle on 7020 FPGA Iphone8plus Kirin 970 CPU MEM CONTROLLER BUS Data Mover IMG WR SCHEDULER WEIGHTS WR SCHEDULER SMART MEM FABRIC IMG RD SCHEDULER

new questions about the one-size-fits-all LLM approach, with smaller, cheaper models trained for custom use cases** now emerging. Will providers try to build horizontal platforms? Will they dive into training, inference optimization, dataset engineering, & model evaluation. Application development = custom AI-powered applications (varied use cases). Source: Chip Hyuen via GitHub (3/24) Cumulative Number to improve their supply chains to manage long lead times. That shift is accelerating the rise of custom silicon – especially ASICs, or application-specific integrated circuits. Unlike GPUs, which are

AI Adoption at BBVA. “With custom GPTs, anyone can create apps to solve unique problems—it’s very easy to start.” In five months, BBVA employees created over 2,900 custom GPTs—some of which reduce 
 a human would. It can also run processes across a wide range of tools and systems—no need for custom integrations or APIs. Enterprises use it to automate workflows that previously required human intervention

relay::Function TorchScript IR Translation Custom Packaging runtime::Module ExternModule DSOModule Function in Other IR ExternFunc te::Function IRModule Custom codegenTimeline RFC: now Main area