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 ...

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 ...

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 ...

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.

AI is experiencing a transformative shift with significant advancements driven by the integration of multiple large language models (LLMs) and other complex components. Consequently, developing ...

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 recent Nobel Prize for groundbreaking advancements in protein discovery underscores the transformative potential of foundation models (FMs) in exploring vast combinatorial spaces. These models are ...

The rise of large language models (LLMs) has sparked questions about their computational abilities compared to traditional models. While recent research has shown that LLMs can simulate a universal ...