Isabella's AI-Powered News Aggregator

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 supervisio...

Democratic inputs to AI

Our nonprofit organization, OpenAI, Inc., is launching a program to award ten $100,000 grants to fund experiments in setting up a democratic process for deciding what rules AI systems should follow, within the bounds defined by the law.

Governance of superintelligence

Now is a good time to start thinking about the governance of superintelligence—future AI systems dramatically more capable than even AGI.

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.

New ways to manage your data in ChatGPT

ChatGPT users can now turn off chat history, allowing you to choose which conversations can be used to train our models.

Announcing OpenAI’s Bug Bounty Program

This initiative is essential to our commitment to develop safe and advanced AI. As we create technology and services that are secure, reliable, and trustworthy, we need your help.

Our approach to AI safety

Ensuring that AI systems are built, deployed, and used safely is critical to our mission.

March 20 ChatGPT outage: Here’s what happened

An update on our findings, the actions we’ve taken, and technical details of the bug.

GPT-4

We’ve created GPT-4, the latest milestone in OpenAI’s effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professi...

Planning for AGI and beyond

Our mission is to ensure that artificial general intelligence—AI systems that are generally smarter than humans—benefits all of humanity.

How should AI systems behave, and who should decide?

We’re clarifying how ChatGPT’s behavior is shaped and our plans for improving that behavior, allowing more user customization, and getting more public input into our decision-making in these areas.

Introducing ChatGPT Plus

We’re launching a pilot subscription plan for ChatGPT, a conversational AI that can chat with you, answer follow-up questions, and challenge incorrect assumptions.

New AI classifier for indicating AI-written text

We’re launching a classifier trained to distinguish between AI-written and human-written text.

OpenAI and Microsoft extend partnership

We’re happy to announce that OpenAI and Microsoft are extending our partnership.

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...

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.

Discovering the minutiae of backend systems

Christian Gibson is an engineer on the Supercomputing team at OpenAI.

Introducing ChatGPT

We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.

DALL·E API now available in public beta

Starting today, developers can begin building apps with the DALL·E API.

DALL·E now available without waitlist

New users can start creating straight away. Lessons learned from deployment and improvements to our safety systems make wider availability possible.

Introducing Whisper

We’ve trained and are open-sourcing a neural net called Whisper that approaches human level robustness and accuracy on English speech recognition.

DALL·E: Introducing outpainting

Extend creativity and tell a bigger story with DALL·E images of any size.

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.

New and improved content moderation tooling

We are introducing a new and improved content moderation tool. The Moderation endpoint improves upon our previous content filter, and is available for free today to OpenAI API developers.

Efficient training of language models to fill in the middle

DALL·E now available in beta

We’ll invite 1 million people from our waitlist over the coming weeks. Users can create with DALL·E using free credits that refill every month, and buy additional credits in 115-generation increments for $15.

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.

Learning to play Minecraft with Video PreTraining

We trained a neural network to play Minecraft by Video PreTraining (VPT) on a massive unlabeled video dataset of human Minecraft play, while using only a small amount of labeled contractor data. With fine-tuning, our model can learn to craft diamond tools, a task that usually takes proficient humans...

AI-written critiques help humans notice flaws

We trained “critique-writing” models to describe flaws in summaries. Human evaluators find flaws in summaries much more often when shown our model’s critiques. Larger models are better at self-critiquing, with scale improving critique-writing more than summary-writing. This shows promise for using A...