For years, embedding models based on bidirectional language models have led the field, excelling in retrieval and general-purpose embedding tasks. However, past top-tier methods have relied on ...

This is the fourth Synced year-end compilation of "Artificial Intelligence Failures." Our aim is not to shame nor downplay AI research, but to look at where and how it has gone awry with the hope that ...

Just hours after making waves and triggering a backlash on social media, Genderify — an AI-powered tool designed to identify a person’s gender by analyzing their name, username or email address — has ...

Recent advancements in training large multimodal models have been driven by efforts to eliminate modeling constraints and unify architectures across domains. Despite these strides, many existing ...

Generative adversarial networks (GANs) have become AI researchers’ “go-to” technique for generating photo-realistic synthetic images. Now, DeepMind researchers say that there may be a better option.

Turing Award Winner and Facebook Chief AI Scientist Yann LeCun has announced his exit from Twitter after getting involved in a long and often acrimonious dispute regarding racial biases in AI.

This research addresses a well-known phenomenon regarding large batch sizes during training and the generalization gap.

Studies have shown that scaling up powerful pretrained models and their training data sizes significantly improves performance, and that these performance improvements can transfer to downstream tasks ...

The Beijing Academy of Artificial Intelligence (BAAI) releases Wu Dao 1.0, China’s first large-scale pretraining model.

AI research aims to develop autonomous agents that can adaptively operate in complex social environments. Multi-agent reinforcement learning (MARL) methods, however, face significant challenges in ...