On Friday, OpenAI said that it will train its models using cached copies and simulated versions of the internet instead of the live web because the models are too unpredictable to be trusted with live internet access.
The frontier lab announced its new policy two weeks after its rival, Anthropic, began limiting its newest and, in theory, most capable models from accessing the live internet. Researchers adopted these policies after months of incidents in which models pursuing training tasks broke into external systems in search of answers, collaborated on obscure message boards, and developed exotic hacking strategies.
That’s why they’re resorting more and more on reinforcement learning. Give the AI a task. Quantify how well the AI performed the task. Less parroting what’s said on the Internet.
They’ll still scrape the internet. The difference is that the models will only have access to a cached version of the internet during the reinforcement learning process (for example, check the documentation of a programming framework). I’m surprised it took them this long to realize it’s a bad idea to do reinforcement learning with live internet access.