starting to emerge. AI agents could reshape how users interact with digital systems – from customer support and onboarding to research, scheduling, and internal operations. Enterprises are leading the charge; Act (3/25 = Research Preview Release) Agent Released Select Capabilities • Automated customer support • Case resolution • Lead qualification • Order tracking • Control computer screen directly to estimates and may not align between companies. Oracle Cloud revenue includes Cloud Services & License Support, as well as Cloud License & On-Premise License. IBM Cloud includes all ‘Infrastructure’ line items

TVM can support many kinds of hardware platform: Intel/arm CPU, Nividia/arm GPU, VTA…5 �������������� 1. Get a .log file from the autotvm on Ubuntu 2. Use the .log from step1 on Windows to generate generate the .dll for deployment 3. For application on 32bits, no support of 32bit tensorflow , a workround from FrozenGene a. python/tvm/contrib/ndk.py options = options if options else [ “-shared”, “-fPIC”

run hello-world 如果返回消息中带有：成功，表明安装成功。 4.3 步骤二 docker 部署 lobechat 通过 docker 部署，只需要一两行命令，非常简单。 无论 windows 还是 mac，都是打开命令窗口，输入下面命令： docker pull lobehub/lobe-chat:latest 这条命令用于从 Docker Hub 上拉取最新的 lobehub/lobe-chat llama3，这样就可以免费使用大模型 llama3。网站里提供很多 助手，选择某个助手，进入会话状态，如图 25。 24 Figure 25: 自带很多助手 4.5 部署常见问题 4.5.1 权限问题 Windows 系统安装，错误提示中带有 Access is denied. 如图 26所示。 Figure 26: ollama 部署权限错误 解决方法：Ollama 默认安装的路径： C:\User

instructions Use existing documents When creating routines, use existing operating procedures, support scripts, or policy documents to create LLM-friendly routines. In customer service for example, routines both sales and support: Python 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 from agents import Agent, Runner technical_support_agent = Agent( ] ) order_management_agent = Agent( name= , instructions=( "Technical Support Agent", "You provide expert assistance with resolving technical issues, system outages, or product

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 Core loops e Support for different integer division modes, floor division and truncating division. e Unified Object and Node system for TVM runtime o Lays groundwork forimproved multi-language support for expPosing BERT have recently become very Popular and require first class support in TVML. ee What we've done: o Extend the relay ONNX frontend to support all opset versions of BERT. 里This enables importing of native

(Py/Java/Go) lib = tvm.module.load("mylib.so") func = lib["npufunction0"] func(a, b) Automatic RPC Support remote = tvm.rpc.connect(board_url, port) remote.upload("mylib.so") remote_mod = remote.load_module(“mylib runtime for dynamic models Credit: Jared Roesch, Haichen Shen et.aluTVM: TVM on bare-metal Devices Support bare-metal J-TAG devices, no OS is needed ARM Cortex-M RISC-V Credit: Logan WeberuTVM upcoming: TPUsTensorization Challenge Compute primitives scalar vector tensor Challenge: Build systems to support emerging tensor instructionsTensorization Challenge C = tvm.compute((m, n), 
 lambda y, x:

$40 million in profit improvement, all while maintaining satisfaction scores on par with human support. These results didn’t happen overnight. Klarna achieved this performance by continuously testing easier to customize and fine-tune models—whether as a self-service approach or using our tools and support. We worked closely with Lowe’s, the Fortune 50 home improvement company, to improve the accuracy with AI every day, so we’re often spotting new ways to automate our own work. An example: Our support teams were getting bogged down, spending time accessing systems, trying to understand context, craft

proposal / roipooling / permute / priorbox绝赞招聘中 未来 命令行工具 将 caffe 模型转换的功能，通过一组命令行工具提供，命令行工具支持 windows / linux 平台。 支持更多 caffe op / net 随着客户需求和社区发展，提供更多的 caffe 分支变种的 op / net 支持。绝赞招聘中 THANKS

Driver ● Arm Compute Library has been integrated by: ○ MATLAB Coder ○ ONNX RuntimeArm platform support in TVM upstream IPs Target Hardware/Model Options Codegen CPU arm_cpu pixel2 (snapdragon 835), t860) N/A opencl bifrost hikey960 (mali g71) N/A FPGA vta pynq, ultra96 N/A sdaccel Out-of-tree support or WIP: Hexagon DSP (via llvm), Ascend NPU, and more Green: Linaro 96BoardsLinaro for TVM ● Linaro Linaro AI/ML group can be a good fit for TVM collaborations on Arm based platforms to support more devices with various accelerator configurations (from microcontrollers to HPC) by working together with

个⼈⽤户：不建议部署32B及以上模型，硬件成本极⾼且运维复杂。 企业⽤户：需专业团队⽀持，部署前需评估ROI（投资回报率）。 ⼆、本地部署核⼼配置要求 1. 模型参数与硬件对应表 模型参 数 Windows 配置要求 Mac 配置要求 适⽤场景 1.5B - RAM: 4GB - GPU: 集成显卡/现代CPU - 存储: 5GB - 内存: 8GB （M1/M2/M3） - 存储: 5GB