When ChatGPT was released in November 2023, it could only be accessed through the cloud because the model behind it was downright enormous.
Today I am running a similarly capable AI program on a Macbook Air, and it isn’t even warm. The shrinkage shows how rapidly researchers are refining AI models to make them leaner and more efficient. It also shows how going to ever larger scales isn’t the only way to make machines significantly smarter. — Read More
Daily Archives: May 27, 2024
Four Singularities for Research
As a business school professor, I am keenly aware of the research showing that business school professors are among the top 25 jobs (out of 1,016) whose tasks overlap most with AI. But overlap doesn’t necessarily mean replacement, it means disruption and change. I have written extensively about how a big part of my job as a professor – my role as an educator – is changing with AI, but I haven’t written as much about how the other big part of my job, academic research, is being transformed. I think that change will be every bit as profound, and it may even be necessary.
Even before ChatGPT, something alarming was happening in academia. Though academics published ever more work, the pace of innovation appeared to be slowing rapidly. In fact, one paper found that research was losing steam in every field, from agriculture to cancer research. More researchers are required to advance the state of the art, and the speed of innovation appears to be dropping by 50% every 13 years. The reasons for this are not entirely clear, and are likely complex, but it suggests a crisis already occurring, one that AI had no role in. In fact, it is possible that AI may help address this issue, but not before creating issues of its own.
I think AI is about to bring on many more crises in scientific research… well, not crises – singularities. I don’t mean The Singularity, the hypothetical moment that humans build a machine smarter than themselves and life changes forever, but rather a narrower version. A narrow singularity is a future point in human affairs where AI has so altered a field or industry that we cannot fully imagine what the world on the other side of that singularity looks like. I think academic research is facing at least four of these narrow singularities. Each has the potential to so alter the nature of academic research that it could either restart the slowing engine of innovation or else create a crisis to derail it further. The early signs are already here, we just need to decide what we will do on the other side. — Read More
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