AI for Productive Research & Innovation in eLectronics (APRIL) Hub

人工智能(AI)正在经历一个爆炸性增长的时代。随着越来越有能力的人工智能代理，如Chat GPT，AlphaFold，Gato和Dall-E抓住了公众的想象力，人工智能对现代社会的潜在影响正变得越来越清晰。4月是一个旨在将人工智能的好处带给英国电子行业的项目。具体地说，我们渴望开发人工智能工具，以缩短从电子设备的新型基础材料到复杂的微芯片设计和系统架构的所有东西的开发时间，从而带来更快、更便宜、更环保、整体更省电的电子产品。想象一下，在未来，极其复杂和复杂的材料结构远比人类单独设计的复杂得多，通过强大的算法(如半导体材料的AlphaFold)进行优化。或者想想拥有领域专业知识的智能机器(想想一个在正确的技能环境中接受过培训的类似Gato的系统)，日夜试验制造技术，以制造完美的电子元件。或者，如果我们通过与工程师用自然语言互动(就像拥有专业知识的聊天GPT)来训练算法来设计电路，会发生什么？对于那些将负责测试和验证日益复杂的系统(如手机芯片组或飞机航空电子软件)的最繁琐的部分，或者实际上是对电子设备进行建模和仿真的系统，也可以发表类似的评论(这两种情况都可能通过使用半自动人工智能编码器实现，比如谷歌的“Palm”模型)。这正是阿普丽尔试图开发的技术鸡尾酒。在未来，人工智能--凭借其查找相关信息的能力、在接到指令时执行简单任务的能力以及令人难以置信的速度--将在经验丰富的工程师的监督下运行，帮助他们创造适合日益增长的要求的电子产品，从低功耗系统到制造可回收的芯片，再到处理最敏感和最隐私数据的超安全系统。为了实现这一目标，4月将一个由大学、行业和政府机构组成的大型联盟聚集在一起，共同开发：i)未来的新技术，ii)使这些技术成为现实的工具，以及非常重要的是，iii)拥有必要技能的人(构建和使用这些新工具)，以确保英国在全球电子行业保持有能力和技术先进的参与者。

Artificial intelligence (AI) is undergoing an era of explosive growth. With increasingly capable AI agents such as chatGPT, AlphaFold, Gato and DALL-E capturing the public imagination, the potential impact of AI on modern society is becoming ever clearer for all to see. APRIL is a project that seeks to bring the benefits of AI to the electronics industry of the UK. Specifically, we aspire developing AI tools for cutting development times for everything from new, fundamental materials for electronic devices to complicated microchip designs and system architectures, leading to faster, cheaper, greener and overall, more power-efficient electronics.Imagine a future where extremely complex and intricate material structures, far more complex than what a human could design alone, are optimised by powerful algorithms (such as an AlphaFold for semiconductor materials). Or consider intelligent machines with domain-specialist knowledge (think of a Gato-like system trained on exactly the right milieu of skills) experimenting day and night with manufacturing techniques to build the perfect electronic components. Or yet what if we had algorithms trained to design circuits by interacting with an engineer in natural language (like a chatGPT with specialist knowledge)? Similar comments could be made about systems that would take care of the most tedious bits of testing and verifying increasingly complex systems such as mobile phone chipsets or aircraft avionics software, or indeed for modelling and simulating electronics (both potentially achievable by using semi-automated AI coders such asGoogle's "PaLM" model). This is precisely the cocktail of technologies that APRIL seeks to develop.In this future, AI - with its capabilities of finding relevant information, performing simple tasks when instructed to do so and its incredible speed - would operate under the supervision of experienced engineers for assisting them in creating electronics suited to an ever-increasing palette of requirements, from low-power systems to chips manufactured to be recyclable to ultra-secure systems for handling the most sensitive and private data. To achieve this, APRIL brings together a large consortium of universities, industry and government bodies, working together to develop: i) the new technologies of the future, ii) the tools that will make these technologies a reality and very importantly, iii) the people with the necessary skills (for building as well as using such new tools) to ensure that the UK remains a capable and technologically advanced player in the global electronics industry.