Goldman Sachs is exploring use cases for large language models, the same AI fueling ChatGPT. Here's 3 areas where the bank is experimenting with the tech.
Argenti noted the banks' blockage of ChatGPT is no different than the standard process of companies blocking completely unrestricted access to the internet on work devices.
Most banks already use a form of AI, called natural-language processing, to extract data from unstructured documents. However, large language models could be a more efficient way to attack the same problem, and potentially magnitudes faster than what is currently being deployed. A big time suck for software engineers is figuring out other peoples' code, Argenti said.
It's a simple task, but at the scale of which Goldman's engineering organization operates , it can make a big difference, Argenti said. Wall Street firms have long tried to unlock the benefits of low-code and no-code automation, which enables non-technical employees to automate processes through graphics or symbols on a computer screen instead of traditional computer programming. It'sby clicking through option buttons on Twitter, instead of writing the line of code.
That's because a lot of automation use cases rely on what is called an imperative approach to programming, which relies on telling a system how something should be done, step by step, Argenti said. Robotic process automation, which is software that automatically repeats certain tasks, is one such example.
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