Alexandr Wang - A Primer on AI - [Invest Like the Best, EP. 272]
Invest Like the Best with Patrick O'Shaughnessy
How Artificial Intelligence Will Slowly Automate Human Work
Artificial Intelligence (AI) is poised to gradually automate specific aspects of human work, particularly in the realm of digital tasks, while physical labor may remain largely untouched for the foreseeable future. Large language models like GPT-3 have leveraged two decades of internet data to excel in generating long-form text, demonstrating the significance of extensive datasets in training AI. In contrast, tasks that require visual skills, such as folding laundry or performing household chores, lack sufficient training data, making automation in these areas a challenging prospect. Surprisingly, while there are assumptions that blue-collar jobs are at the highest risk of automation, it appears that white-collar knowledge work is more susceptible. Routine, digital tasks, particularly those involving spreadsheet processes, are among the most likely to be automated, freeing human workers to engage in more creative and fulfilling roles. The phenomenon of jobless claims being at an all-time low suggests that technological advancements have not drastically disrupted employment. AI's influence will primarily lie in enhancing productivity by enabling humans to focus on higher-order tasks. Understanding the architecture of AI models is critical to grasp how they function. The lifecycle of AI models begins with data collection, where the quality and quantity of data—akin to ingredients in cooking—prove vital for success. Essentially, data has become the new 'code' for AI, driving the machine learning process where traditional software relied on code as its lifeblood. Thus, comprehending how AI models are built, starting from data collection to eventual predictions, is key to understanding the broad implications of AI in the workforce.
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