AI4SE（AI for Software Engineering），是指以大模型等AI技术为驱动的，以提高软件研发运营智能化水平为导向的，以提质增效为目标的，新一代智能化软件工程。AI4SE工作组首批成员单位名单 AI4SE工作组以“中国人工智能产业发展联盟”和“人工智能关键技术和应用评测工业和信息化部重点实验室”为依托，凝聚人工智能行业...
给 LLM 灌输行业知识,当前有两种方式,一种是 Fine Tuning(微调),另外一种是 Prompt Engineering。就目前实际的行业发展而言,Fine Tuning 还未形成共识,并且成本巨高,实际目前的大量应用都是基于 Prompt Engineering 做的——当前世界上应用最广泛的模型 GPT-4 并不提供 Fine Tuning 的选项。 但无论是 Fine Tuning...
随着ChatGPT的火热,ML/AI for XXX的项目越来越多,这里收集一些Github上其他人整理的list(慢慢补充) https://github.com/WangRongsheng/awesome-LLM-resoursesAwesome-AI-for-cybersecurityawesome-ml-for-cybe…
JetBrains andDelft University of Technologyhave joined forces to establish theAI for Software Engineering(AI4SE) research partnership. Through this collaboration, we are determined to pursue
In this talk, we'll explore opportunities for revolutionizing software engineering using large language models (LLMs).We'll cover some techniques for using LLMs, including chain-of-thought prompting, and a new technique called program-aided language models. We'll also present a computational model...
图2. 2010-2020年AI工程相关论文分布(Software Engineering for AI-Based Systems: A Survey, ACM TOSEM, 2021) 工业界各大公司以AI工程方法、技术和工具的发展为主,主要分两类: 1)以Google、Meta为代表的科技巨头,围绕TensorFlow、PyTorch等开源深度学习框架打造了一系列与AI工程相关的生态技术和工具,如高级API、...
software engineering, to develop a new, rich taxonomy of human-centric requirements for software ...
- Responsible for Vitis AI software framework research and development on Xilinx advanced Versal AI platform.- Deliver world-class AI software stack to support Xilinx global data center customers.Requirements- 3+ yeras strong experience of TensorFlow, PyTorch, or PaddlePaddle development.- Strong ...
The only AI-powered software platform designed for engineering teams to enhance research, innovation, and decision-making Learn More Electronics Parts Solutions Identify the best components for your products, with access to over 1.2 billion electronic, electro-mechanical and fastener parts documentation ...
Software engineers are looking towards AI for both potential increase in software 'power' that AI techniques seems to promise, and exploitation of complexity-reduction strategies that AI has, of necessity, pioneered. AI practitioners, struggling with fragile demonstrations, would dearly like to import ...