The important moves in artificial intelligence.

Text2SQL using Hugging Face Dataset Viewer API and Motherduck DuckDB-NSQL-7B

Video generation models as world simulators

We explore large-scale training of generative models on video data. Specifically, we train text-conditional diffusion models jointly on videos and images of variable durations, resolutions and aspect ratios. We leverage a transformer architecture that operates on spacetime patches of video and image latent codes. Our largest model, Sora, is capable of generating a minute of high fidelity video. Our results suggest that scaling video generation models is a promising path towards building general purpose simulators of the physical world.

From OpenAI to Open LLMs with Messages API on Hugging Face

Building an early warning system for LLM-aided biological threat creation

We’re developing a blueprint for evaluating the risk that a large language model (LLM) could aid someone in creating a biological threat. In an evaluation involving both biology experts and students, we found that GPT-4 provides at most a mild uplift in biological threat creation accuracy. While this uplift is not large enough to be conclusive, our finding is a starting point for continued research and community deliberation.

New embedding models and API updates

How OpenAI is approaching 2024 worldwide elections

We’re working to prevent abuse, provide transparency on AI-generated content, and improve access to accurate voting information.

A guide to setting up your own Hugging Face leaderboard: an end-to-end example with Vectara's hallucination leaderboard

Personal Copilot: Train Your Own Coding Assistant

Deploying the AI Comic Factory using the Inference API

Non-engineers guide: Train a LLaMA 2 chatbot

SafeCoder vs. Closed-source Code Assistants

OpenAI partners with Scale to provide support for enterprises fine-tuning models

OpenAI’s customers can leverage Scale’s AI expertise to customize our most advanced models.