way to continuously improve the AI-enabled processes, with expert feedback at every step. How it started Morgan Stanley’s first eval focused on making their financial advisors more efficient and effective the time spent on repetitive tasks, they could offer more and better insights to clients.
 They started with three model evals: 01 Language translation Measuring the accuracy and quality of translations customized context. 
 The performance uplift was significant: A 20% increase in job applications started A 13% uplift in downstream success—not only were more candidates likely to apply, 
 but employers

developers, enterprises and governments. And unlike the Internet 1.0 revolution – where technology started in the USA and steadily diffused globally – ChatGPT hit the world stage all at once, growing in should mention something amazing about [the new Duolingo curriculum in] chess is that it really started with a team of two people, neither of whom knew how to program…and they basically made prototypes truth-seeking AI. - xAI Founder & CEO Elon Musk – 5/25 AI Going Full-Circle: DeepMind’s AlphaGo (2014) started with humans training machines…Duolingo Chess now has machines training humans… Tech Incumbent

prompt engineering in detail. We will look into the various prompting techniques to help you getting started and share tips and best practices to become a prompting expert. We will also discuss some of the simplest type of prompt. It only provides a description of a task and some text for the LLM to get started with. This input could be anything: a question, a start of a story, or instructions. The name zero-shot

Hardware DEPLOY VTA ON INTEL FPGA©2019 HARMAN INTERNATIONAL INDUSTRIES, INCORPORATED 11 Getting Started DEPLOY VTA ON INTEL FPGA Step 1: Get DE10-Nano and download & install Quartus Prime 18.1 Lite Edition

number of turns. 14 A practical guide to building agents For example, in the Agents SDK, agents are started using the method, which loops over the LLM until either: Runner.run() 01 A final-output tool is

LLMOps 开发 工具 26 / 32 LLM 的工具和平台：LLMOps LangChain 架构图 （图源：https://python.langchain.com/docs/get_started/introduction） �� LangChain 是一个帮助开发者使用 LLM 创建应用的开源框 架，它可以将 LLM 与外部数据源进行连接，并允许与 LLM 进行交互。 LangChain