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 ...

In the new paper Generative Agents: Interactive Simulacra of Human Behavior, a team from Stanford University and Google Research presents agents that draw on generative models to simulate both ...

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

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 ...

Large language models (LLMs) like GPTs, developed from extensive datasets, have shown remarkable abilities in understanding language, reasoning, and planning. Yet, for AI to reach its full potential, ...

Cambricon Technologies, one of China’s AI chip giant founded in 2016, has raised US $369 million in IPO at the Shanghai Stock Exchange’s STAR Market.

Recent strides in large language models (LLMs) have showcased their remarkable versatility across various domains and tasks. The next frontier in this field is the development of large multimodal ...