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Elon Musk AI creates news generator that's 'too dangerous' to release!

Research group Open AI developed a 'large-scale unsupervised language model' that is able to generate news stories from a simple headline.  But the group insists it will not be releasing details of the programme and instead has unveiled a much smaller version for research purposes.  Its developers claim the technology is poised to rapidly advance in the coming years and the full specification and details of the project will only be released when the negative applications have been discussed by researchers.   Scroll down for video  OpenAI is a group founded by Musk and backed by Silicon Valley heavyweights, including LinkedIn's Reid Hoffman.  Musk has famously been an outspoken critic of AI, calling it the biggest existential threat to humankind and warning '[we could create] an immortal dictator from which we would never escape.'   While OpenAI is describing its work in the paper, it is not releasing the full model out of concern it could be misused.  The researchers said: 'Due to our concerns about malicious applications of the technology, we are not releasing the trained model.

GPT-2 displays a broad set of capabilities, including the ability to generate conditional synthetic text samples of unprecedented quality, where we prime the model with an input and have it generate a lengthy continuation.

These samples have substantial policy implications: large language models are becoming increasingly easy to steer towards scalable, customized, coherent text generation, which in turn could be used in a number of beneficial as well as malicious ways.

On other language tasks like question answering, reading comprehension, summarization, and translation, we are able to get surprising results without any fine-tuning of our models, simply by prompting the trained model in the right way (see below for examples of how we do this), though we do still fall short of state-of-the-art for specialized systems.

We can anticipate how systems like GPT-2 could be used to create: We can also imagine the application of these models for malicious purposes, including the following (or other applications we can't yet anticipate): These findings, combined with earlier results on synthetic imagery, audio, and video, imply that technologies are reducing the cost of generating fake content and waging disinformation campaigns.

Today, malicious actors — some of which are political in nature — have already begun to target the shared online commons, using things like “robotic tools, fake accounts and dedicated teams to troll individuals with hateful commentary or smears that make them afraid to speak, or difficult to be heard or believed”.

We should consider how research into the generation of synthetic images, videos, audio, and text may further combine to unlock new as-yet-unanticipated capabilities for these actors, and should seek to create better technical and non-technical countermeasures.

Nearly a year ago we wrote in the OpenAI Charter: "we expect that safety and security concerns will reduce our traditional publishing in the future, while increasing the importance of sharing safety, policy, and standards research,"

This decision, as well as our discussion of it, is an experiment: while we are not sure that it is the right decision today, we believe that the AI community will eventually need to tackle the issue of publication norms in a thoughtful way in certain research areas.

Other disciplines such as biotechnology and cybersecurity have long had active debates about responsible publication in cases with clear misuse potential, and we hope that our experiment will serve as a case study for more nuanced discussions of model and code release decisions in the AI community.

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