PFI-RP: Resilient and Energy-Efficient Memory Chips for Enhanced Mobile AI and Personalized Machine Learning

这一创新-研究伙伴关系(PFI-RP)项目的影响范围更广，涉及科学、技术和社会领域。通过专注于开发一种弹性、快速切换和节能的磁阻随机存取存储器(MRAM)，这项研究旨在彻底改变移动人工智能(AI)的格局。与目前的内存选择不同，这项创新就像智能手机或智能手表的增压引擎，只需充电一次，它们就会变得更智能，续航时间更长。这不仅意味着更快的处理，而且还意味着更小、更个性化的人工智能就在你的设备上。这项研究解决了热挑战、复杂的设计和纳米制造，以使这项技术无缝地工作，目标是创造就业机会，并为学生的未来做好准备。可以把它看作是升级你的电子产品的大脑。一旦开发出来，这种人工智能芯片可以被苹果或特斯拉等公司用来实现全新的应用。对这种技术的需求是巨大的，而且还在不断增长，它可能会导致我们在日常生活中使用人工智能的方式取得重大突破，同时使我们的设备和隐私得到安全保护。该项目还将增强不同群体的学生在创新和半导体制造方面的关键技能。拟议的项目旨在解决下一代MRAM材料和器件开发中的关键技术障碍，重点是增强热稳定性，实现快速和持久的切换，并确保可持续的能源效率。这项研究特别关注移动人工智能中的应用，寻求创新的解决方案，以应对目前限制MRAM技术广泛采用的挑战。在不断发展的移动计算格局中，人工智能算法承诺提供变革性的用户体验，数据安全和隐私问题是最重要的。传统的人工智能模型在云中接受了广泛的培训，存在泄露个人用户信息的风险。此外，它们在移动设备上的部署通常会导致某些用户组的性能不佳。该项目将通过在硬件级别利用基于非易失性MRAM的联想存储器和在软件级别利用基于嵌入的神经网络来推动移动人工智能的最先进技术。通过这样做，该研究展望了移动设备上的人工智能应用程序不仅高效(节省电池电量)而且安全(将私人数据保存在自己的设备上)的未来，确保各种人工智能工具的用户获得更具包容性和响应性的体验。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact of this Partnerships for Innovation - Research Partnerships (PFI-RP) project extends across scientific, technological, and societal realms. By focusing on the development of a resilient, fast-switching, and energy-efficient magnetoresistive random access memory (MRAM), this research aims to revolutionize the landscape of mobile artificial intelligence (AI). Unlike current memory options, this innovation is like a supercharged engine for your smartphone or smartwatch, making them smarter and much longer lasting with just one charge. This means not just faster processing, but also a smaller, personalized AI right in your device. The research tackles thermal challenges, design intricacies and nanofabrication to make this technology work seamlessly, with the goal of creating jobs and preparing students for the future. Think of it as upgrading the brain of your gadgets. Once developed, this AI chip could be used by companies like Apple or Tesla to enable brand-new applications. The demand for this kind of tech is huge and growing, and it could lead to a major breakthrough in how we use AI in our daily lives, while making our devices and privacy securely protected. The project will also empower a diverse group of students with crucial skills for innovation and semiconductor fabrication.The proposed project aims to tackle critical technical hurdles in the development of the next generation of MRAM materials and devices, focusing on enhancing thermal robustness, achieving fast and enduring switching, and ensuring sustainable energy efficiency. With a specific focus on applications in mobile AI, the research seeks innovative solutions that address challenges currently limiting the widespread adoption of MRAM technologies. In the evolving landscape of mobile computing, where AI algorithms promise transformative user experiences, data security and privacy concerns are paramount. Traditional AI models, trained extensively in the cloud, pose risks of compromising personal user information. Moreover, their deployment on mobile devices often results in suboptimal performance for certain user groups. This project will advance the state of the art in mobile AI by leveraging nonvolatile MRAM-based associative memories at the hardware level and embeddings-based neural networks at the software level. By doing so, the research envisions a future where AI applications on mobile devices are not only efficient (preserving battery power) but also secure (keeping private data locally on your own device), ensuring a more inclusive and responsive experience for users of all kinds of AI tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.