or generating a report. Applications that integrate LLMs but don’t use them to control workflow execution—think simple chatbots, single-turn LLMs, or sentiment classifiers—are not agents. More concretely manage workflow execution and make decisions. It recognizes when a workflow is complete and can proactively correct its actions if needed. In case 
 of failure, it can halt execution and transfer control Examples Data Enable agents to retrieve context and information necessary for executing the workflow. Query transaction databases or systems like CRMs, read PDF documents, or search the web. Action Enable

to computing, calculating or counting patents. Google patents data changes somewhat between each query so numbers are rounded and should be viewed as directionally accurate. Source: USA Patent & Trademark agents, but deploying them, investing in frameworks and building ecosystems around autonomous execution. What was once a messaging interface is becoming an action layer.90 Source: Google Trends via rich context within the enterprise through the Ontology. We remain differentiated in our elite execution to deliver quantified exceptionalism for our customers, ever widening their advantage over the

approaches have been explored to address this issue, including Grouped-Query Attention (GQA) (Ainslie et al., 2023) and Multi-Query Attention (MQA) (Shazeer, 2019). However, these methods often compromise limit the inference efficiency. In order to reduce the KV cache, Multi-Query Atten- tion (MQA) (Shazeer, 2019) and Grouped-Query Attention (GQA) (Ainslie et al., 2023) are proposed. They require a smaller respectively: q? = ??h?, (1) k? = ? ?h?, (2) v? = ??h?, (3) 6 Grouped-Query Attention (GQA) Multi-Head Attention (MHA) Multi-Query Attention (MQA) Multi-Head Latent Attention (MLA) Keys Queries Values

阿里巴巴人工智能实验室 PowerVR GPU Alibaba Al.Labs 阿里巴巴人工智能实验室 PowerVR support by TVM NNVM Compiler -Execution graph -Model layers functions Computation Graph Optimizations -Param TvM

Efficiency ˃ Supported on U200 – 3 Instances U250 – 4 Instances Amazon F1 ˃ ~1536 DSPs @ 700MHz Execution Controller Spill / Restore DMA Controller Weights DMA Controller Systolic Array Bias ReLU

specific aspects of the RAG system that impact what content was inserted into the prompt, including the query, chunk settings, chunk output, and other information. Once you feel the prompt is close to perfect