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[N] OpenAI releasing the 345M model of GPT-2 and sharing the 1.5B model “with partners working on countermeasures”

OpenAI has decided to adopt a staged release approach to their GPT-2 language model.

Announcement on Twitter: https://twitter.com/OpenAI/status/1124440412679233536

The following quotes are from the update on their blog: https://openai.com/blog/better-language-models/#update

Staged Release

Staged release involves the gradual release of a family of models over time. The purpose of our staged release of GPT-2 is to give people time to assess the properties of these models, discuss their societal implications, and evaluate the impacts of release after each stage.

As the next step in our staged release strategy, we are releasing the 345M parameter version of GPT-2. This model features improved performance relative to the 117M version, though falls short of the 1.5B version with respect to the ease of generating coherent text. We have been excited to see so many positive uses of GPT-2-117M, and hope that 345M will yield still more benefits.

While the misuse risk of 345M is higher than that of 117M, we believe it is substantially lower than that of 1.5B, and we believe that training systems of similar capability to GPT-2-345M is well within the reach of many actors already; this evolving replication landscape has informed our decision-making about what is appropriate to release.

In making our 345M release decision, some of the factors we considered include: the ease of use (by various users) of different model sizes for generating coherent text, the role of humans in the text generation process, the likelihood and timing of future replication and publication by others, evidence of use in the wild and expert-informed inferences about unobservable uses, proofs of concept such as the review generator mentioned in the original blog post, the strength of demand for the models for beneficial purposes, and the input of stakeholders and experts. We remain uncertain about some of these variables and continue to welcome input on how to make appropriate language model publication decisions.

We hope that ongoing research on bias, detection, and misuse will give us the confidence to publish larger models in a timely manner, and at the six month mark we will share a fuller analysis of language models’ societal implications and our heuristics for release decisions.

Partnerships

Since releasing this blog post in February, we have had conversations with many external researchers, technology companies, and policymakers about our release strategy and the implications of increasingly large language models. We’ve also presented or discussed our work at events, including a dinner co-hosted with the Partnership on AI and a presentation to policymakers in Washington DC at the Global Engagement Center.

We are currently forming research partnerships with academic institutions, non-profits, and industry labs focused on increasing societal preparedness for large language models. In particular, we are sharing the 762M and 1.5B parameter versions of GPT-2 to facilitate research on language model output detection, language model bias analysis and mitigation, and analysis of misuse potential. In addition to observing the impacts of language models in the wild, engaging in dialogue with stakeholders, and conducting in-house analysis, these research partnerships will be a key input to our decision-making on larger models. See below for details on how to get involved.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.