This Perspective article expands on a working memory-dependent dual-process model, originally proposed by Zheng et al. 1, to elucidate individual differences in the testing effect. This model posits ...

Forming memories and using acquired knowledge when needed is an essential cognitive capability. Imagine, for example, a teacher, who is trying to learn the names of students of a new class. For some ...

Open-source OCR from Baidu eliminates the GPU memory wall that limits long-document parsing. Unlimited OCR uses a constant KV ...

Google TurboQuant reduces memory strain while maintaining accuracy across demanding workloads Vector compression reaches new efficiency levels without additional training requirements Key-value cache ...

In modern CPU device operation, 80% to 90% of energy consumption and timing delays are caused by the movement of data between the CPU and off-chip memory. To alleviate this performance concern, ...

Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits. MeMo, a ...

In the fast-paced world of artificial intelligence, memory is crucial to how AI models interact with users. Imagine talking to a friend who forgets the middle of your conversation—it would be ...