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

创新伙伴关系-研究伙伴关系（PFI-RP）项目的广泛影响延伸到科学、技术和社会领域。通过专注于开发弹性，快速切换和节能的磁阻随机存取存储器（MRAM），本研究旨在彻底改变移动人工智能（AI）的格局。与目前的内存选项不同，这种创新就像智能手机或智能手表的增压引擎，只需一次充电，就能让它们变得更智能，使用寿命更长。这不仅意味着更快的处理速度，还意味着在你的设备中有一个更小、更个性化的人工智能。这项研究解决了热挑战、复杂的设计和纳米制造，使这项技术无缝地工作，目标是创造就业机会，为学生的未来做好准备。把它想象成升级你的小工具的大脑。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于实现全新的应用程序。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如何使用人工智能方面取得重大突破，同时使我们的设备和隐私得到安全保护。该项目还将使不同群体的学生掌握创新和半导体制造的关键技能。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，重点是增强热稳健性，实现快速和持久的开关，并确保可持续的能源效率。该研究特别关注移动人工智能的应用，寻求创新的解决方案，以解决目前限制MRAM技术广泛采用的挑战。在不断发展的移动计算领域，人工智能算法有望带来革命性的用户体验，数据安全和隐私问题至关重要。传统的人工智能模型在云端进行了广泛的训练，存在泄露用户个人信息的风险。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理想。该项目将在硬件层面利用基于非易失性mram的联想存储器，在软件层面利用基于嵌入式的神经网络，从而推动移动人工智能的发展。通过这样做，研究设想了一个未来，移动设备上的人工智能应用不仅高效（节省电池电量），而且安全（将私人数据保存在自己的设备上），确保为各种人工智能工具的用户提供更具包容性和响应性的体验。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.