From the archive
Large language models (LLMs) have revolutionized artificial intelligence, particularly in natural language understanding and generation. These models, trained on vast amounts of text data, excel in tasks such as question…
Neuromorphic computing takes design cues from nervous systems, including event-based signals and distributed state. This guide explains representative architectures and hardware, then considers candidate workloads and the evidence needed to…
In recent years, natural language processing has advanced greatly with the development of large language models (LLMs) trained on extensive text data. For AI systems to fully interact with the…
AI can support explanation, practice, and feedback, but students still need to understand and verify their work. This guide outlines useful learning applications, risks such as submitting generated work as…
As artificial intelligence (AI) becomes more advanced, a new issue has emerged - AI deception. This occurs when AI systems deceive people into believing false information in order to achieve…
Apple has launched OpenELM, a groundbreaking open-source language model that outperforms even ChatGPT and GPT-3 in some areas. Built on innovative techniques like Grouped Query Attention and Switched Gated Linear…
Microsoft has recently announced the release of Phi-3, a revolutionary language model that brings a supercomputer-like performance to the realm of smartphones. This compact model surpasses larger models in various…
Over the past few years, language models have emerged as a fundamental component of artificial intelligence, significantly advancing various natural language processing tasks. However, Transformer-based models face challenges in terms…
Mixture-of-Depths (MoD) is a revolutionary approach to transformer architectures that dynamically allocates computational resources based on token importance. Developed by Google DeepMind, MoD utilizes per-block routers, efficient routing schemes, and…
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