A fundamental scientific problem of our time is to understand how memory systems integrate present sensory stimuli, past experience, and future behavioural options. Modern neuroscience tries to ...

Abstract: Model compression is widely adopted for edge inference of neural networks (NNs) to minimize both costly DRAM accesses and memory footprints. Recently, XOR-based model compression has ...

Abstract: We consider memory errors and memory safety in the cases of the Java and Rust programming languages. We also give a view of how type safety fits in.

Skoltech scientists have devised a mathematical model of memory. By analyzing its new model, the team came to surprising conclusions that could prove useful for robot design, artificial intelligence, ...

Model Context Protocol, or MCP, is arguably the most powerful innovation in AI integration to date, but sadly, its purpose and potential are largely misunderstood. So what's the best way to really ...

Summary: A new memory model called Input-Driven Plasticity (IDP) offers a more human-like explanation for how external stimuli help us retrieve memories, building on the foundations of the classic ...

Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations -- it's a triumph of your associative memory, in which one piece of information (the first few ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

Transformer-based models have significantly advanced natural language processing (NLP), excelling in various tasks. However, they struggle with reasoning over long contexts, multi-step inference, and ...