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Using GPT-4 for content moderation
We use GPT-4 for content policy development and content moderation decisions, enabling more consistent labeling, a faster feedback loop for policy refinement, and less involvement from human moderators.
Confidence-Building Measures for Artificial Intelligence: Workshop proceedings
Frontier Model Forum
We’re forming a new industry body to promote the safe and responsible development of frontier AI systems: advancing AI safety research, identifying best practices and standards, and facilitating information sharing among policymakers and industry.
Accurately analyzing large scale qualitative data
Viable uses GPT-4 to analyze qualitative data at a revolutionary scale with unparalleled accuracy.
Improving mathematical reasoning with process supervision
We've trained a model to achieve a new state-of-the-art in mathematical problem solving by rewarding each correct step of reasoning (“process supervision”) instead of simply rewarding the correct final answer (“outcome supervision”). In addition to boosting performance relative to outcome supervision, process supervision also has an important alignment benefit: it directly trains the model to produce a chain-of-thought that is endorsed by humans.
Language models can explain neurons in language models
We use GPT-4 to automatically write explanations for the behavior of neurons in large language models and to score those explanations. We release a dataset of these (imperfect) explanations and scores for every neuron in GPT-2.
GPTs are GPTs: An early look at the labor market impact potential of large language models
Powering virtual education for the classroom
Khan Academy explores the potential for GPT-4 in a limited pilot program.
Preserving languages for the future
How Iceland is using GPT-4 to preserve its language.
Forecasting potential misuses of language models for disinformation campaigns and how to reduce risk
OpenAI researchers collaborated with Georgetown University’s Center for Security and Emerging Technology and the Stanford Internet Observatory to investigate how large language models might be misused for disinformation purposes. The collaboration included an October 2021 workshop bringing together 30 disinformation researchers, machine learning experts, and policy analysts, and culminated in a co-authored report building on more than a year of research. This report outlines the threats that language models pose to the information environment if used to augment disinformation campaigns and introduces a framework for analyzing potential mitigations. Read the full report here.
Creating next-gen characters
Using GPT-3 to create the next generation of AI-powered characters.
The power of continuous learning
Lilian Weng works on Applied AI Research at OpenAI.
Point-E: A system for generating 3D point clouds from complex prompts
Scaling laws for reward model overoptimization
Our approach to alignment research
We are improving our AI systems’ ability to learn from human feedback and to assist humans at evaluating AI. Our goal is to build a sufficiently aligned AI system that can help us solve all other alignment problems.
Efficient training of language models to fill in the middle
A hazard analysis framework for code synthesis large language models
DALL·E 2: Extending creativity
As part of our DALL·E 2 research preview, more than 3,000 artists from more than 118 countries have incorporated DALL·E into their creative workflows. The artists in our early access group have helped us discover new uses for DALL·E and have served as key voices as we’ve made decisions about DALL·E’s features.
DALL·E 2 pre-training mitigations
In order to share the magic of DALL·E 2 with a broad audience, we needed to reduce the risks associated with powerful image generation models. To this end, we put various guardrails in place to prevent generated images from violating our content policy.