In artificial intelligence, the capacity of Large Language Models (LLMs) to negotiate mirrors a leap toward achieving human-like interactions in digital negotiations. At the heart of this exploration is the…

Researchers have challenged the prevailing belief in the field of computer vision that Vision Transformers (ViTs) outperform Convolutional Neural Networks (ConvNets) when given access to large web-scale datasets. They introduce…

CodeCompose, an AI-powered code authoring tool utilized by tens of thousands of developers at Meta, has undergone scaling from providing single-line to multiline suggestions. This transition involved addressing unique challenges…

Language models like GPT-3 are designed to be neutral and generate text based on the patterns they’ve learned in the data. They don’t have inherent sentiments or emotions. If the…

Reinforcement learning (RL) comprises a wide range of algorithms, typically divided into two main groups: model-based (MB) and model-free (MF) methods. MB algorithms rely on predictive models of environment feedback,…

Despite having some parallels to other sequence modeling issues, like text, audio, or video, time series has two characteristics that make it particularly difficult. Aggregated time series datasets frequently include…

Artificial intelligence (AI) is witnessing an era where language models, specifically large language models (LLMs), are not just computational entities but active participants in the digital ecosystem. These models, through…

ULTRA is a model designed to learn universal and transferable graph representations for knowledge graphs (KGs). ULTRA creates relational illustrations by conditioning them on interactions, enabling it to generalise to…