Anthony De Luca-Baratta
In 2012, DQN, an AI system developed by then-start-up DeepMind, discovered how to play classic Atari computer games with human-level skill, a major breakthrough at the time. By 2023, GPT-4 had become the most powerful and general AI model to date, showcasing the ability to ace several standardized tests, including the SAT and LSAT, pulling ahead of human doctors on several medical tasks, constructing full-scale business plans for startups, translating natural language to computer code, and producing poetry in the style of famous poets.
We haven’t seen anything yet. There are several reasons to believe that AI systems will continue to become more powerful, more general, and more ubiquitous.
First, there is the recent development and rapid improvement of machine learning algorithms known as foundation models, which take the knowledge learned from one task and apply it to other seemingly unrelated tasks. This ability makes them incredibly versatile and, thus, incredibly powerful. Large language models like GPT-4 are infant technologies that seem likely to undergo many more rounds of improvement as private and public money continue to pour into AI research. They require large amounts of data on which to train, which in turn require the appropriate hardware on which to be processed.
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