Prompt Engineering Author: Lee Boonstra Prompt Engineering February 2025 2 Acknowledgements Content contributors Michael Sherman Yuan Cao Erick Armbrust Anant Nawalgaria Antonio Gulli Simone Cammel Grace Mollison Technical Writer Joey Haymaker Designer Michael Lanning Introduction 6 Prompt engineering 7 LLM output configuration 8 Output length 8 Sampling controls 9 Temperature 9 Top-K and top-P 29 Self-consistency 32 Tree of Thoughts (ToT) 36 ReAct (reason & act) 37 Automatic Prompt Engineering 40 Code prompting 42 Prompts for writing code 42 Prompts for explaining code 44 Prompts for

Stanford University… 1: AI ‘Winter’ was a term used by Nils J. Nilsson, the Kumagai Professor of Engineering in computer science at Stanford University, to describe the period during which AI continued to hypothetical endpoint, but as a reachable threshold. If / when achieved, AGI would redefine what software (and related hardware) can do. Rather than executing pre-programmed tasks, AGI systems would understand understand goals, generate plans, and self-correct in real time. They could drive research, engineering, education, and logistics workflows with little to no human oversight – handling ambiguity and novelty

People's Republic of China (MIIT) has released the "14th Five-Year Plan for the Development of Software and Information Technology Services", a typical signal that the open source sector will take off perspective of international politics, national strength, and national security. The recent open source software security incidents made everyone talk in succession. Such a mixed phenomenon may be likely to continue niche hobby, it was free to do almost anything. Nevertheless, today, as software devours the world and open source eats software, open source technology has become one of the infrastructures of the entire

new category of LLM-powered systems known as agents. This guide is designed for product and engineering teams exploring how to build their first agents, distilling insights from numerous customer deployments your first agent. 3 A practical guide to building agents What is an agent? While conventional software enables users to streamline and automate workflows, agents are able to perform the same workflows coupled with robust authentication and authorization protocols, strict access controls, and standard software security measures. 24 A practical guide to building agents Think of guardrails as a layered defense

Keeth Feedback The KiCad project welcomes feedback, bug reports, and suggestions related to the software or its documentation. For more information on how to sumbit feedback or report an issue, please Pin Table. Background images that can be displayed in the PCB Editor for reference or reverse engineering purposes. Optional automatic zone filling in the PCB Editor, which can be used instead of manually section presents a high-level overview of the typical KiCad workflow. Note that KiCad is a flexible software system, and there are other ways of working that are not described here. For more information about

issues About KiCad software: https://gitlab.com/kicad/code/kicad/issues About KiCad software i18n: https://gitlab.com/kicad/code/kicad-i18n/issues Publication date and software version March 05 2020 2.4. TransLine Transmission line theory is a cornerstone in the teaching of RF and microwave engineering. In the calculator you can choose different sorts of Line Types and their special parameters.

ues • About KiCad software: https://gitlab.com/kicad/code/kicad/issues • About KiCad software i18n: https://gitlab.com/kicad/code/kicad-i18n/issues Publication date and software version March 05 2020 2.4 TransLine Transmission line theory is a cornerstone in the teaching of RF and microwave engineering. PCB Calculator 4 / 7 In the calculator you can choose different sorts of Line Types and their

responsive customer experiences. 3 AI in the EnterpriseBut leveraging AI isn’t the same as building software or deploying cloud apps. The most successful companies are often those who treat it as a new paradigm a process are best-placed to improve 
 it with AI. 06 Unblock your
 developers Automating the software development lifecycle can multiply 
 AI dividends. 07 Set bold 
 automation goals Most processes Developer resources are the main bottleneck and growth inhibitor in many organizations. 
 When engineering teams are overwhelmed, it slows innovation and creates an insurmountable backlog of apps and ideas

Frameworks New operator introduced by operator fusion optimization potential benefit: 1.5x speedup Engineering intensiveMachine Learning based Program Optimizer TVM: Learning-based Learning System High-level board. • Move hardware complexity to software HW-SW Blueprint for Flexible Deep Learning Acceleration. Moreau et al. IEEE Micro 2019. VTA Hardware/Software Interface (ISA) VTA MicroArchitecture VTA

Technology, Austria Institute of Interactive Systems and Data Science Computer Science and Biomedical Engineering BMK endowed chair for Data Management Last update: Nov 11, 2021 2 706.015 Introduction to Scientific Which data / data sets should be used?  Which workload / queries should be run?  Which hardware & software should be used?  Metrics: What to measure? How to measure?  Comparison: How to compare? CSI: How components: #nodes, CPUs, memory, network, I/O  SW components: OS, programming language, versions, other software  Baselines and configuration  Use recent versions of baseline systems  Data and workloads w/