Tag
8 articles
Learn to analyze emotional-like representations in language models using transformer activation analysis, attention visualization, and behavioral pattern detection techniques.
Learn how Falcon Perception is a new AI system that combines image and language processing to better understand natural language prompts and find specific objects in images.
This explainer explores the concept of General Artificial Intelligence (AGI) and how OpenAI's Greg Brockman believes GPT reasoning models are on a clear path toward achieving it, using the term 'line of sight' to describe this trajectory.
Explore the significance of Hugging Face's TRL v1.0, a unified framework for aligning large language models through post-training techniques like SFT, Reward Modeling, DPO, and GRPO.
Explains how Luma Labs' Uni-1 model introduces a reasoning phase before image generation, addressing the 'intent gap' that affects current diffusion models.
This article explains how a new AI model uses memory and flexible thinking time to solve problems more efficiently than traditional models.
Learn to implement and use State Space Models with the Mamba architecture, focusing on Mamba-3's 2x smaller states and enhanced hardware efficiency.
This article explains how a new AI technique called Attention Residuals changes the way information flows in Transformer models, potentially making them more efficient and easier to train.
