AI’s Memorization Crisis

O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...
IEEE

BAM-Net: Hardware Friendly Associative Memory Using Binary Dominant Weights and NAND Logic

Abstract: This paper presents BAM-Net, a hardware-efficient binarization algorithm designed for associative memory (AM) implementation. BAM-Net aims to reduce memory overhead, power consumption, and ...
IEEE

Remember and Recall: Associative-Memory-Based Trajectory Prediction

Abstract: Trajectory prediction is a key component of autonomous driving systems, enabling the application of accumulated movement experience to current scenarios. Although most existing methods ...