"We present a systematic review of some of the popular machine learning based email spam filtering approaches."
"Our review covers survey of the important concepts, attempts, efficiency, and the research trend in spam filtering."
An interdisciplinary research project exploring the history and ideas behind the influential ELIZA chatbot, created in the 1960s. The project aims to contextualize ELIZA, analyze its code, and examine its cultural impact on human-computer interaction.
In this essay, Lance Fortnow, a computer scientist, argues that by embracing the computations that surround us, we can begin to understand and tame our seemingly random world. He discusses how even seemingly random events, like a coin flip or the mailing of a letter, can be seen as computational processes. The essay also touches on the progress made in artificial intelligence and machine learning, and how they are helping us manage randomness and complexity in our world.
This paper introduces Cross-Layer Attention (CLA), an extension of Multi-Query Attention (MQA) and Grouped-Query Attention (GQA) for reducing the size of the key-value cache in transformer-based autoregressive large language models (LLMs). The authors demonstrate that CLA can reduce the cache size by another 2x while maintaining nearly the same accuracy as unmodified MQA, enabling inference with longer sequence lengths and larger batch sizes.