(Blue Bars) As data volumes rise, CapEx required to build more hyperscale data centers, faster network infrastructure, & more compute capacity CapEx: +21% / Year Data: +28% / Year CapEx Spend – Big companies – with aggressive cash burn – tested this premise hard, built large-scale data-driven network effects based on product excellence / constant improvement, developed technology-driven competitive *Has a partnership with Oracle, SoftBank and MGX to build out the proposed Stargate data-center network. Source: Wall Street Journal, ‘Here’s How Big the AI Revolution Really Is, in Four Charts’ (4/25)

even the wording of a user-facing message) leaves less room 
 for errors in interpretation. Capture edge cases Real-world interactions often create decision points such as how to proceed when a user provides agents Manager pattern The manager pattern empowers a central LLM—the “manager”—to orchestrate a network of specialized agents seamlessly through tool calls. Instead of losing context or control, the manager be effective: 01 Focus on data privacy and content safety 02 Add new guardrails based on real-world edge cases and failures you encounter 03 Optimize for both security and user experience, tweaking your

Configurable Overlay Processor ˃ DNN Specific Instruction Set Convolution, Max Pool etc. ˃ Any Network, Any Image Size ˃ High Frequency & High Compute Efficiency ˃ Supported on U200 – 3 Instances Pooling Image Queue Instruction Buffer Cross Bar Pooling/ EWA© Copyright 2018 Xilinx Xilinx Edge DPU IP (DPUv2) Source: Published results from Huawei 18% 13% 14% 40% 24% 23% 85% 51% 52% Quantization Tool – vai_q ˃ 4 commands in vai_q quantize ‒ Quantize network test ‒ Test network accuracy finetune ‒ Finetune quantized network deploy ‒ Generate model for DPU ˃ Data Calibration data

separation of active material from the current collector, and disruption of the electronic conduction network within the electrode,ultimately resulting in a sharp decline in Li+ storage capacity and attenuation cracks, active material separating from the current collector, and a disrupted electronic conduction network within the electrode. All of these issues can cause a sharp decline in Li+ storage capacity and )was used to determine the shell strength. Each shell valve was placed horizontally with the shell edge on a flat surface, while a compressive force was applied at a constant loading rate of 10 mm-min

generate output that is robust to a variety of inputs, then it is important to include edge cases in your examples. Edge cases are inputs that are unusual or unexpected, but that the model should still be

High-Level Differentiable IR Tensor Expression and Optimization Search Space LLVM, CUDA, Metal VTA Edge FPGA Cloud FPGA ASIC Optimization AutoTVM Device FleetExisting Deep Learning Frameworks High-level

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np from tvm import relay 2. Load a pretrained network mod, params = relay.testing.mobilenet.get_workload(batch_size=1) 3. Partition and build the network with an external codegen mod = relay.build_extern(mod

?????????? Shared Expert Routed Expert Top-???????????????????????? Attention Feed-Forward Network … 3 4 RMS Norm RMS Norm Transformer Block ×???????????? DeepSeekMoE 0 Input Hidden ?????? (Vaswani et al., 2017), where each Transformer block consists of an attention module and a Feed-Forward Network (FFN). However, for both the attention module and the FFN, we design and employ innovative archi-

ecosystemLinaro AI Initiative Provide the best-in-class Deep Learning performance by leveraging Neural Network acceleration in IP and SoCs from the Arm ecosystem, through collaborative seamless integration with