From the archive
Large Language Models (LLMs) like GPT-4, Claude, Gemini, and T5 have achieved remarkable success in natural language processing tasks. However, they can produce biased or inappropriate outputs, raising concerns about…
The emergence of Large Language Models (LLMs) has greatly transformed the field of Artificial Intelligence (AI) by equipping machines with natural language processing capabilities. However, one of the major challenges…
AGI claims need a stated definition and evidence of broad, reliable capability; how much autonomy a system receives is a separate deployment question. Models, agents, speech systems, and specialized hardware…
Agentive AI describes a human-centered approach to systems that support a person’s goal; it is related to, but distinct from, systems often called agentic. This guide examines applications, enabling technologies,…
A New research paper called "Self-Discover: Large Language Models Self-Compose Reasoning Structures" explores the possibilties to enhance problem-solving abilities in Large Language Models (LLMs) by mimicking human cognitive processes. It…
The "Self-Rewarding Language Models" research paper introduces a novel approach to language model training. This method enables iterative improvement through self-alignment by allowing models to generate and evaluate their own…
Mistral AI has developed a new open-source model called Mixtral 8x7B, which uses Sparse Mixture of Experts (SMoE) technology. This model features eight feedforward blocks in each layer for efficient…
Large Language Models (LLMs) have impressive natural language processing capabilities, but they require significant computational resources. Apple's "LLM in a flash" solution overcomes this challenge by using flash memory to…
The field of artificial intelligence is constantly evolving. Emu2 is a state-of-the-art multimodal model that boasts an impressive 37 billion parameters. It has shown exceptional skill in in-context learning and…
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