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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.
Discovering the minutiae of backend systems
Christian Gibson is an engineer on the Supercomputing team at OpenAI.
Evolution through large models
Measuring Goodhart’s law
Goodhart’s law famously says: “When a measure becomes a target, it ceases to be a good measure.” Although originally from economics, it’s something we have to grapple with at OpenAI when figuring out how to optimize objectives that are difficult or costly to measure.
Helen Toner joins OpenAI’s board of directors
Today, we’re excited to announce the appointment of Helen Toner to our board of directors.
Will Hurd joins OpenAI’s board of directors
OpenAI is committed to developing general-purpose artificial intelligence that benefits all humanity, and we believe that achieving our goal requires expertise in public policy as well as technology. So, we’re delighted to announce that Congressman Will Hurd has joined our board of directors.
Understanding the capabilities, limitations, and societal impact of large language models
Organizational update from OpenAI
It’s been a year of dramatic change and growth at OpenAI.
Learning Day
At OpenAI, each Thursday is Learning Day: a day where employees have the option to self-study technical skills that will make them better at their job but which aren’t being learned from daily work.
Why responsible AI development needs cooperation on safety
We’ve written a policy research paper identifying four strategies that can be used today to improve the likelihood of long-term industry cooperation on safety norms in AI: communicating risks and benefits, technical collaboration, increased transparency, and incentivizing standards. Our analysis shows that industry cooperation on safety will be instrumental in ensuring that AI systems are safe and beneficial, but competitive pressures could lead to a collective action problem, potentially causing AI companies to under-invest in safety. We hope these strategies will encourage greater cooperation on the safe development of AI and lead to better global outcomes of AI.
OpenAI Fellows Fall 2018: Final projects
Our second class of OpenAI Fellows has wrapped up, with each Fellow going from a machine learning beginner to core OpenAI contributor in the course of a 6-month apprenticeship. We are currently reviewing applications on a rolling basis for our next round of OpenAI Fellows Summer 2019.
OpenAI Fellows Summer 2018: Final projects
Our first cohort of OpenAI Fellows has concluded, with each Fellow going from a machine learning beginner to core OpenAI contributor in the course of a 6-month apprenticeship.
Team update
The OpenAI team is now 45 people. Together, we’re pushing the frontier of AI capabilities—whether by validating novel ideas, creating new software systems, or deploying machine learning on robots.
Infrastructure for deep learning
Deep learning is an empirical science, and the quality of a group’s infrastructure is a multiplier on progress. Fortunately, today’s open-source ecosystem makes it possible for anyone to build great deep learning infrastructure.
Machine Learning Unconference
The latest information about the Unconference is now available at the Unconference wiki, which will be periodically updated with more information for attendees.
Special projects
Impactful scientific work requires working on the right problems—problems which are not just interesting, but whose solutions matter.