A novel, quantum model for NLP: a step towards AGI.

一种新颖的 NLP 量子模型：迈向 AGI 的一步。

• 批准号: 10075658
• 金额: $ 39.54万
• 依托单位: SECQAI LTD
• 依托单位国家: 英国
• 项目类别: Feasibility Studies
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10075658
• 关键词: novel; quantum; model; NLP; step

Large language models such as ChatGPT have recently undergone a step-change in their user-perceived efficacy, and as such they have caught the attention of journalists and then the imagination of the general public. These A.I. systems appear to deliver responses to user-posed questions that are both informative and delivered with substantial expertise. The application of this nascent, yet extraordinarily useful, technical breakthrough across whole ranges of industries is only starting to become apparent.Large language models are effective since they capture and codify, in their models, significant portions of all human knowledge, through the process of ingesting the entirety of the World-Wide-Web. The resultant models are staggeringly large (for example, ChatGPT3 contains some 175 billion parameters) and thus, these models take months to train and use a great deal of power to run.It is our intention to build a Chat-GPT like large language model A.I. system that utilises a quantum calculation engine. The system shall employ a fundamentally different processing, model and systems architecture to current systems, leading to a step change in the efficiency and power of the resultant system. We shall build software to run such a system and demonstrate its increased efficiency in both training models, which shall be much more energy efficient during the training process, and in speed of execution and energy use when in operation. These benchmarks shall be performed against the requirements of the NLP and voice processing industry as understood by the consortium.

ChatGPT 等大型语言模型最近在用户感知功效方面发生了巨大变化，因此引起了记者的注意，进而引起了公众的想象力。这些人工智能。系统似乎可以对用户提出的问题做出答复，这些答复既内容丰富，又具有丰富的专业知识。这种新生但非常有用的技术突破在整个行业的应用才刚刚开始变得明显。大型语言模型之所以有效，是因为它们通过以下过程在其模型中捕获并编码了所有人类知识的重要部分：吸收整个万维网。由此产生的模型非常大（例如，ChatGPT3 包含约 1750 亿个参数），因此，这些模型需要数月的时间来训练并使用大量的算力来运行。我们的目的是构建一个类似 Chat-GPT 的大型语言模型人工智能。利用量子计算引擎的系统。该系统应采用与当前系统根本不同的处理、模型和系统架构，从而导致最终系统的效率和功率发生阶跃变化。我们将构建软件来运行这样的系统，并在两种训练模型中展示其效率的提高，这在训练过程中以及在运行时的执行速度和能源使用方面将更加节能。这些基准测试应根据联盟所理解的 NLP 和语音处理行业的要求来执行。