The dangers of artificial intelligence can be substantially reduced by regulating hardware, training and deployment.
called LLaMA appeared online. LLaMA was not intended to be publicly accessible, but the model was shared with AI researchers, who then requested full access to further their own projects. At least two of them abused Meta’s trust and released the model online, and Meta has been unable to remove LLaMA from the internet. The model can still be accessed by anyone., there is not yet cause for major alarm. The theft or leak of more capable AI models would be much worse.
The first is hardware. The creation of advanced AI models requires thousands of specialized microchips, costing tens or even hundreds of millions of dollars. Only a few companies — such as Nvidia and AMD — design these chips, and most are sold to large cloud-computing providers such as Amazon, Microsoft and Google, as well as the U.S. government, a handful of foreign governments, and just a few other deep-pocketed tech companies.
The next stage of AI oversight focuses on the training of each model. A developer can — and should be required to — assess a model’s risky capabilities during training. Problems detected early can be more easily fixed, so a safer, less expensive final product can be built in less time.Once training is complete, a powerful AI model should be subject to rigorous review by a regulator or third-party evaluator before it is released to the world.
AI regulation is already underway in Britain, the European Union and China. But many breakthrough models — and most of the advanced AI systems that have brought us to this moment — have been developed in the United States. We would do well to establish a model of oversight for the world that focuses on the three parts of the AI supply chain.
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