the more your organization benefits from compounding improvements. Klarna, a global payments network and shopping platform, introduced a new AI assistant to streamline customer service. Within a few creditworthiness faster and 
 more accurately. The Legal team Uses it to answer 40,000 questions a year on policies, compliance, and more. The Customer Service team Automates the sentiment analysis of NPS surveys compliance. Flexible retention Adjust settings for logging and storage to match your organization’s policies. For more on OpenAI and security, visit our Security page or the OpenAI Security Portal. 23 AI

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 if constraints are breached. 

 Guardrails can be implemented as functions or agents that enforce policies such as jailbreak prevention, relevance validation, keyword filtering, blocklist enforcement, or

Rising Priority77 Source: NVIDIA (2/25 & 5/25) Government = Increasingly Adopting Sovereign AI Policies Education / Government / Research AI Adoption = Rising Priority NVIDIA Sovereign AI Partners – (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

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 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

�������������������� 1. OpenVino a black box, can not deploy our network(with depthwise conv2d, ) 2. TVM can not only deploy our network, but also get a good performance gain by autotuning 3. TVM can

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

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

?????????? 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