This article mainly interprets the evaluation of current large models by famous computer scientist Michael Jordan in an exclusive interview with Zhiyuan Community. He pointed out that large models still need improvement in quantifying the uncertainty of prediction results and establishing economic models that incentivize knowledge contributors. Professor Jordan's views are based on his profound knowledge in the fields of statistics and microeconomics. He advocates a "collectivist machine learning" approach to solve complex social problems and calls on governments and foundations to support the construction of a more inclusive AI ecosystem. system.
Michael Jordan, a well-known computer scientist, said in an exclusive interview with Zhiyuan Community that the current large models still need to continue to work hard in two aspects: first, they lack the ability to quantify the uncertainty of prediction results and give certainty measures; second, Large models lack an economic incentive model that can retroactively reward knowledge contributors. His view is related to his understanding in the fields of statistics and microeconomics. Michael Jordan believes that solving social problems such as medical care and transportation requires consideration from the system and collective levels and a collectivist machine learning. He also said that governments and foundations should not only support large companies, but should help build an ecosystem where everyone's ideas have a chance to be realized.All in all, Professor Michael Jordan’s views point out the way for the future development direction of large models, emphasizing the importance of combining technological development with social benefits, as well as the necessity of building a fair and open AI ecosystem, which is worthy of our deep thought.