Core Insights - The article discusses a significant advancement in AI hardware through a high-precision analog in-memory computing chip developed by Nanjing University, which has achieved the highest precision record in the field [1][2]. Group 1: Research and Development - The research team at Nanjing University has proposed a high-precision analog in-memory computing scheme and developed a chip based on complementary metal-oxide-semiconductor (CMOS) technology [1]. - The chip utilizes a weight remapping technique to enhance computational accuracy, achieving a root mean square error (RMSE) of only 0.101% in parallel vector-matrix multiplication operations, setting a new record for precision in analog vector-matrix multiplication [2]. Group 2: Performance in Extreme Conditions - The chip demonstrates stable operation in extreme environments, maintaining RMSE levels of 0.155% at -78.5℃ and 0.130% at 180℃ [2]. - Measurements in strong magnetic fields showed that the output current of the chip's core unit varied by no more than 0.21% compared to conditions without a magnetic field, confirming the reliability of the high-precision analog computing scheme under extreme conditions [2]. Group 3: Implications for AI Hardware - This breakthrough is seen as a critical step towards the practical application of analog in-memory computing technology, with the potential to promote the development of low-power, high-precision AI hardware [2].

Core Insights - Nanjing University has developed a high-precision analog computing scheme, leading to the creation of an analog computing chip based on complementary metal-oxide-semiconductor (CMOS) technology [1] - The chip achieved a record low root mean square error (RMSE) of only 0.101% in parallel vector-matrix multiplication operations, marking a significant advancement in analog computing precision [1] - The chip demonstrates stable performance in extreme environments, maintaining RMSE levels of 0.155% at -78.5℃ and 0.130% at 180℃, confirming the reliability of high-precision analog computing in harsh conditions [1] Technology Development - The research team utilized weight remapping technology to enhance the chip's performance in vector-matrix multiplication [1] - The breakthrough in analog computing technology is expected to facilitate the development of low-power, high-precision AI hardware [1]