Development Trending = Unprecedented37 Machine-Learning Model* Trending = In 2015... Industry Surpassed Academia as Data + Compute + Financial Needs Rose *Machine Learning = A subset of AI where machines AI, an AI Index data provider, uses the term ‘notable machine learning models’ to designate particularly influential models within the AI/machine learning ecosystem. Epoch maintains a database of 900 Academia Era 2015-today: Industry Era Global Notable Machine Learning Models by Sector – 2003-2024, per Stanford HAI Annual New Notable Machine-Learning Models AI Development Trending = Unprecedented38

the input the model uses to predict a specific output. You don’t need to be a data scientist or a machine learning engineer – everyone can write a prompt. However, crafting the most effective prompt can hinder the model’s ability to provide meaningful output. You don’t need to be a data scientist or a machine learning engineer – everyone can write a prompt. Prompt Engineering February 2025 7 When you chat summarization, information extraction, question and answering, text classification, language or code translation, code generation, and code documentation or reasoning. Please feel free to refer to Google’s prompting

remote.load_module(“mylib.so") func = remote_mod[“npufunction0"] func(remote_a, remote_b)Virtual Machine: Supporting Dynamic Workload Dynamic shape workloads More runtime objects: Arrays, Tuples, Trees product readyInterpolate with Other Compilers MLIR-TF Function relay::Function TorchScript IR Translation Custom Packaging runtime::Module ExternModule DSOModule Function in Other IR ExternFunc

给出 输出结果，其中第一列是原文，第二列是翻译后的句子，每行只给出一个句子 所提供段落的语言是中文，以下是按要求的标记表格式翻译成英文的译文： Original (Chinese) Translation (English) 捕食是一个基本的生态过程，捕食的定义为：一种生物（捕食 者）捕食了另一种生物（猎物）（Begon等，1997）。 Predation is a fundamental compressive force (shell strength)following Burnett and Belk (2018). A universal material+testing machine(MTS System Corporation, Eden Prairie, MIN, USA, Model 661; Fig1,)was used to determine the shell compressive force (shell strength)following Burnett and Belk (2018). A universal material-testing machine (MTS System Corporation, Eden Prairie, MN, USA, Model 661; Fig. 1) was used to determine the shell

10 11 12 13 14 15 16 17 18 19 20 21 22 23 from import "manager_agent" "You are a translation agent. You use the tools given to you to translate." "translate_to_spanish" "Translate the user's {message.content}") async def for in print "Translate 'hello' to Spanish, French and Italian for me!" Translation step: Declarative vs non-declarative graphs

 Some frameworks are declarative, requiring developers

offer more and better insights to clients.
 They started with three model evals: 01 Language translation Measuring the accuracy and quality of translations produced 
 by a model. 02 Summarization Evaluating

Computational PhD in Machine Lesming Phb in Computer Arhiecure oon) PhD in Programming nd Complers Biology and Machine Professor Intel orMicrosof Apple Qualcomm 40+ years of combined experience in computer systems design and machine learning tr tvm 。 @zxnet 和os 全 W Open Source at OctoML ee We are big believers o Core Infrastructure Improvements to TVM o_uTVM: support for microcontrollers in TVM o_ Virtual Machine and dynamic NNs support (w/ AWS folks) o_ Improved NLP support, with focus on transformers QQ octoML

TVM ● Support Any-dim in typing ● Use shape function to compute the type at runtime ● Virtual machine as a new runtime for Relay ● Dynamic codegen (WIP) ○ Kernel dispatch for a single op ○ Graph dispatch dependent© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Relay virtual machine Relay Executable relay.vm.compile Relay Object (hardware independent) Code segment VM Func 0 type using the entries from a register. AllocClosure Allocates a closure with a lowered virtual machine function. If Jumps to the true or false offset depending on the condition. Goto Unconditionally

Liu, W. Che, L. Xiao, Z. Chen, W. Ma, S. Wang, and G. Hu. A span-extraction dataset for Chinese machine reading comprehension. In K. Inui, J. Jiang, V. Ng, and X. Wan, editors, Proceedings of the 2019 2024. K. Sun, D. Yu, D. Yu, and C. Cardie. Investigating prior knowledge for challenging chinese machine reading comprehension, 2019. M. Suzgun, N. Scales, N. Schärli, S. Gehrmann, Y. Tay, H. W. Chung arXiv:2403.04652, 2024. R. Zellers, A. Holtzman, Y. Bisk, A. Farhadi, and Y. Choi. HellaSwag: Can a machine really finish your sentence? In A. Korhonen, D. R. Traum, and L. Màrquez, editors, Proceedings of

Optimizations Symbols NNVM & Param Frontends Operators Algorithm &Schedule CUDA TOPI Backends Machine Learning Automated Optimizer Schedule explorer Cost model Mali TOPI ROCM TOPI PVRTOPI Alibaba