From Party Trick to Productivity Powerhouse: The Steady Ascent of Large Language Models
In recent years, the development of large language models (LLMs) has sparked heated discussions about their capabilities, potential, and the nuances of technological progress. An insightful conversation delves into the trajectory of these technologies, highlighting the leaps made from earlier models to the sophisticated versions we see today, such as GPT-4 and GPT-5.
One of the central themes is the dichotomy between the perceived suddenness of technological advancement and the lengthy underlying research that makes these leaps possible. This phenomenon, often encapsulated by Amara’s Law, states that people tend to overestimate technology’s short-term effects while underestimating its long-term impact. In the case of LLMs, this has been evident in how GPT-3.5 to 4 marked the transformation of artificial intelligence from being a novel party trick to a tool worthy of subscription, indicative of its utility in basic and niche tasks.