The ability of humans to create and disseminate culture is often credited as the single most
important factor of our success as a species. In this Perspective, we explore the notion of …

More than one hundred benchmarks have been developed to test the commonsense
knowledge and commonsense reasoning abilities of artificial intelligence (AI) systems …

Reinforcement learning from human feedback (RLHF) is a technique for training AI systems
to align with human goals. RLHF has emerged as the central method used to finetune state …

The remarkable ability of large language models (LLMs) to comprehend, interpret, and
generate complex language has rapidly integrated LLM-generated text into various aspects …

This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …

Seismic advances in generative AI algorithms for imagery, text, and other data types has led
to the temptation to use synthetic data to train next-generation models. Repeating this …

Researchers have argued that large language models (LLMs) exhibit high-quality writing
capabilities from blogs to stories. However, evaluating objectively the creativity of a piece of …

Exploring large corpora can generate useful discoveries but is time-consuming for humans.
We formulate a new task, D5, that automatically discovers differences between two large …

Collective intelligence underpins the success of groups, organizations, markets and
societies. Through distributed cognition and coordination, collectives can achieve outcomes …

In the digital era, the integration of artificial intelligence (AI) in education has ushered in
transformative changes, redefining teaching methodologies, curriculum planning, and …