Should AI research be open or closed? Experts disagree.
, but as researchers and experts pore over its accompanying materials, many have expressed disappointment at one particular feature: that despite the name of its parent company, GPT-4 is not anOpenAI has shared plenty of benchmark and test results for GPT-4, as well as some intriguing demos, but has offered essentially no information on the data used to train the system, its energy costs, or the specific hardware or methods used to create it.
“I think we can call it shut on ‘Open’ AI: the 98 page paper introducing GPT-4 proudly declares that they’re disclosing *nothing* about the contents of their training set,”Here, Schmidt is referring to a section in the GPT-4Given both the competitive landscape and the safety implications of large-scale models like GPT-4, this report contains no further details about the architecture , hardware, training compute, dataset construction, training method, or similar.
“On the competitive landscape front — it’s competitive out there,” said Sutskever. “GPT-4 is not easy to develop. It took pretty much all of OpenAI working together for a very long time to produce this thing. And there are many many companies who want to do the same thing, so from a competitive side, you can see this as a maturation of the field.”
“On the safety side, I would say that the safety side is not yet as salient a reason as the competitive side. But it’s going to change, and it’s basically as follows. These models are very potent and they’re becoming more and more potent. At some point it will be quite easy, if one wanted, to cause a great deal of harm with those models. And as the capabilities get higher it makes sense that you don’t want want to disclose them.
“I fully expect that in a few years it’s going to be completely obvious to everyone that open-sourcing AI is just not wise.”
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