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- This year, Sam Altman shared insights about the future of artificial general intelligence (AGI) at Harvard.
- He envisions AGI as a means to boost productivity and foster collective intelligence.
- OpenAI’s goal is to create AGI that replicates human-like reasoning.
Sam Altman, the head of OpenAI, frequently finds himself in the public eye, addressing numerous inquiries regarding technology and its implications.
In a recent interview at Harvard Business School that was released this year, venture capitalist Patrick Chung posed an intriguing question to Altman: what inquiry would he prefer regarding artificial general intelligence? Since its establishment in 2015, OpenAI has been dedicated to realizing this theoretical form of machine intelligence that aims to emulate or even exceed human capabilities.
Altman responded with two pivotal questions: What vision do you have for society once AGI is realized? How do you envision a beneficial outcome from this development?
The CEO noted that his perspective on these questions has shifted over time. Initially, he imagined reaching a point where self-enhancing superintelligence would emerge—a remarkable entity capable of answering any query while continuously seeking ways to improve our world. He described it as potentially both ”utopian and profoundly dystopian.”
However, during his interview in May, he expressed a more grounded outlook. He suggested we are moving towards an era where AGI will simply “integrate into society and the economy.”
Mainly, it will take shape through tools designed to enhance individual productivity. Additionally, it will contribute to building a framework of “shared intelligence,” which he likened to “scaffolding connecting us all.”
This concept implies that one expert could provide valuable insights into material science that might assist another team in creating advanced technologies like transistors or mini semiconductors.
“Superintelligence does not reside within any single neural network,” he explained. Instead, it arises from “the connections between various neural networks,” forming what he calls a ”technology tree.” This structure allows society to achieve objectives beyond what any individual network can accomplish alone.
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