{"id":532062,"date":"2025-12-08T09:00:36","date_gmt":"2025-12-08T08:00:36","guid":{"rendered":"https:\/\/silicon-saxony.de\/fraunhofer-ipms-den-datenhunger-der-ki-zaehmen-mit-kleinsten-technologieknoten-zur-energieeffizienten-ki-2\/"},"modified":"2025-12-08T09:02:57","modified_gmt":"2025-12-08T08:02:57","slug":"fraunhofer-ipms-den-datenhunger-der-ki-zaehmen-mit-kleinsten-technologieknoten-zur-energieeffizienten-ki-2","status":"publish","type":"post","link":"https:\/\/silicon-saxony.de\/en\/fraunhofer-ipms-den-datenhunger-der-ki-zaehmen-mit-kleinsten-technologieknoten-zur-energieeffizienten-ki-2\/","title":{"rendered":"Fraunhofer IPMS: Den Datenhunger der KI z\u00e4hmen: Mit kleinsten Technologieknoten zur energieeffizienten KI"},"content":{"rendered":"

They are based on ferroelectric field-effect transistors (FeMFETs) made from hafnium oxide, which are particularly efficient. With a joint research program, Fraunhofer IPMS, Fraunhofer IMWS, and the Taiwanese research institute TSRI are laying the foundation for the next generation of energy-efficient AI chips \u2013 from smartphones and automobiles to medical devices.<\/p>\n

Given the rapidly growing demand for artificial intelligence (AI) and neuromorphic computing, the energy consumption of data centers and edge systems is increasing dramatically. A key bottleneck is the transfer of data between main memory and the computing unit. A joint German-Taiwanese project aims to address precisely this issue: innovative memory technology will enable computing \u201cdirectly in memory\u201d, with significantly lower latency and energy consumption.\n<\/p>\n<\/p>\n

\u201cWe are designing a platform that more closely links the memory technology and computing power of state-of-the-art chips. This opens new possibilities for AI systems while reducing energy consumption,\u201d says Dr. Maximilian Lederer, project manager at Fraunhofer IPMS.<\/p>\n

Hafnium oxide-based ferroelectric FETs (FeFETs) are considered particularly suitable for this purpose: thanks to thin hafnium oxide layers, the technology can be integrated into modern semiconductor processes. In addition, these components operate capacitively (rather than resistively) and thus consume up to about 100 times less energy in embedded systems than comparable non-volatile memory solutions.<\/p>\n

The goal of the collaboration is to establish a 300 mm research line that develops memory not only for consumer applications, but also for automotive, industrial, and medical technology.<\/p>\n

\u201cThe German-Taiwanese cooperation combines key competencies \u2013 from material development and high-resolution material characterization to state-of-the-art device architectures. Together, we are creating a platform for the next generation of energy-saving memory technologies,\u201d adds Dr. Chien-Nan Liu, Director General of the Taiwan Semiconductor Research Institute, National Institutes of Applied Research (TSRI, NIAR).<\/p>\n

_ _ _ _ _\n<\/p>\n

About Fraunhofer IPMS
\n<\/h3>\n
Fraunhofer IPMS is a leading international research and development service provider for electronic and photonic microsystems in the application fields of Smart Industrial Solutions, Bio and Health, Mobility as well as Green and Sustainable Microelectronics. Research focuses on customer-specific miniaturized sensors and actuators, MEMS systems, microdisplays and integrated circuits as well as wireless and wired data communication. The institute develops systems and components on 200 and 300 mm wafers in their state-of-the-art clean rooms. Services range from consulting and design to process development and pilot series production. As an expert in secure data communication solutions, the Business Unit of Data Communication and Computing (DCC) develops innovative technologies in the future-oriented fields of IP cores, Li-Fi (light-based data transmission) and quantum technologies. These developments pave the way for new and secure communication solutions in key industries such as mobility, telecommunications, industrial automation and energy supply.<\/div>\n
<\/div>\n
_ _ _ _ _ <\/div>\n

Further Links<\/h3>\n
\ud83d\udc49 Press release<\/a><\/div>\n
\n<\/div>\n
\n<\/div>\n<\/p>\n<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"

Artificial intelligence works fast, but its energy consumption is growing rapidly. A German-Taiwanese research team is now developing a solution: new memory for leading chip technologies smaller than 3 nm. 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