Hi
Welcome (back) to The Prompt. We’re recapping recent updates, sharing what’s top of mind for us, and calling out favorite ways in which people are using our tools.
We also have something new with this edition: a video featuring Chief Global Affairs Officer Chris Lehane and other colleagues breaking down this week’s news and insights.
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[Policy] When progress requires pacing
AI capabilities are accelerating, and as they advance, our standards must rise, too.
Our research gives us a window into what future models may be able to do – including increasingly powerful cybersecurity work. This week, we explained how we’re responding: slowing the scaling of some of our most advanced training runs to accelerate work on safeguards.
That means expanding monitoring to detect concerning behavior, training models to behave safely and remain responsive to human oversight, and strengthening security in the environments where we develop them. We’re applying these safeguards earlier in training and across more internal testing, not just as we prepare models for public release.
We took a two-week pause in reinforcement learning – a training method that uses feedback to improve how models behave – on our latest models intended for release. Separately, our largest planned run of that training remains on hold while smaller-scale training and testing continue. This is not a pause on all research, training, or customer-facing products.
Stronger safeguards must also work for customers with the strictest privacy requirements. This week, we previewed Private Safety Processing, a new approach that gives our safety systems more context to identify patterns of serious abuse while allowing us to continue offering Zero Data Retention. Customer content can remain in infrastructure they control, or in privacy-preserving storage secured with customer-managed keys. Our systems can analyze that information without giving OpenAI personnel access to it; discard the data after analysis; and retain only narrowly defined signals about any abuse detected. Safety and privacy advance together.
We’re investing the engineering work, time, and computing resources needed to meet these higher standards. Building models people can trust is essential to delivering better products, helping more people use AI, and making its benefits broadly available.
This is what responsible frontier development requires. The point is not to stop progress, but to make sure our ability to understand, align, and secure increasingly capable systems stays ahead of their capabilities.
[Perspective] Our inflection point, powered by broad access
Our business is at an inflection point, with enterprise now surpassing consumer to represent over half of our revenue. While Sol is delivering tremendous value to people and businesses, this is a story about a diversified business with different levers that compound one another.
OpenAI started with an unusually broad consumer base – scale that is important not just as a measure of adoption, but as the foundation for a business that can serve people in many different ways.
Some people pay for subscriptions. Some use ChatGPTWork, helping drive a business that now serves more than 2 million customers. Developers build new products and businesses on our API. Small and medium-sized businesses use these tools to grow in ways that just weren’t possible before. And increasingly, advertisers can help support access for the vast majority of our users who may never pay for a subscription at all.
Just six months after launching ads in ChatGPT, tens of thousands of advertisers are now on the platform globally. And next week, ChatGPT Ads will expand into 31 new European markets including Germany, France, Spain, and Italy.
There’s a larger point here about the economics of making AI broadly accessible. If advanced AI is going to become a tool for everyone, it needs a business model capable of serving everyone. A billion-plus users won’t all use AI in the same way, and they won’t all pay for it in the same way. Diversification lets us meet people where they are: subscriptions for consumers who want more, enterprise products for businesses, APIs for developers, and advertising that can help support broad access. And all this is powered by more compute making it possible to serve AI for everyone at scale.
That creates a reinforcing flywheel. Broad access creates scale. Scale creates opportunities for new businesses. A more diversified business supports greater investment in compute and research. And those investments make increasingly capable AI available to more people.
So the story in this week’s numbers isn’t simply that OpenAI is building a robust business – it’s that the scale created by broad access is allowing us to build a more diversified one, which in turn can help make even broader access possible.
[Video] How OpenAI’s flywheel turns
OpenAI’s revenue momentum is creating a fast-turning flywheel, Chris Lehane explains: better models lead to more users and revenue, which funds the computing power needed to build the next generation of technology. In a new OpenAI Forum video, Lehane and our head of policy development, Morgan Dwyer, also discuss ChatGPT for Teens and the case for a democratic, worker-centered AI economy whose benefits are broadly shared.
[Weekly wrap] What else caught our attention
AI built for teens, with learning and protections at the center: We introduced ChatGPT for Teens, which places users ages 13-17 into an experience with stronger safeguards, Study Mode, responsible homework reminders, Study Hours, and new healthy-use features. And through a new partnership with CodeAI, we will help students learn how AI works, question its outputs, use it responsibly, and create with it through programs including Hour of AI, a national Builders Challenge, and classroom resources.
A major investment in southern Ohio: OpenAI joined the PORTS-Pike project in Pike County, Ohio, an approximately 8-gigawatt AI infrastructure development expected to support 35,000 construction jobs and 2,500 long-term operating jobs. The project will cover its own energy and infrastructure costs, use closed-loop cooling, and include an additional $40 million OpenAI community fund. We are also providing up to $84 million in Codex credits for eligible Ohio college, community college, and technical-school students.
Strengthening California’s frontier safety framework: We called for updates to SB 53 that would, among other provisions, require monitoring frontier models during training and evaluation for potential serious incidents and strengthen cybersecurity protections throughout the model-development lifecycle, building on state action toward a harmonized national standard.
User stories we love: After two surgeries for a benign pituitary tumor, Amy Deng used AI to collect and analyze her health data, helping her and her doctors make better decisions faster. Amy is an AI researcher, but what she created can be built by anyone. Sandhya Simhan taught ChatGPT to understand her interpretation of Hinduism, creating a tool that helps her apply her values to life decisions and adapt faith stories for the preschool students she teaches. And Fidji Simo used ChatGPT to analyze her whole-genome sequencing results, research experimental treatments, and brainstorm possible tests to discuss with her doctor.
AI’s back-to-school savings: USA Today and other outlets covered how ChatGPT can help parents find back-to-school savings on laptops and other school supplies.
[Disclosure]
Graphics created by Base Three using ChatGPT.
https://substack.com/@danielsethroberts/note/p-211207664?r=8cnl84