Not to be a buzzkill, but let's take a deep dive into the disparity
and search engines soon followed suit. They showed that AI chatbots weren't designed just for question and answering, and could be a powerful versatile tool. Given input instructions, LLMs can perform other sorts of tasks like text summarization, classification, and search, and to do things like planning, reviewing reports, or writing docucments.
Generative AI, however, is still nascent. Although companies are keen to market themselves as forward-thinking and leaders of the trend, IT spending on the technology reveals a different story. The vast majority of AI cloud computing costs is mostly spent on predictive analytics, with other areas including computer vision, recommendation systems, or graph networks following behind. Generative AI is not a significant impact on bills for enterprises or revenues for cloud platforms quite yet.
Chetan Kapoor, director of product management for EC2 instances at AWS, agreed. He said Amazon's biggest generative AI contracts have come from key players like Anthropic and Stability AI. The next wave comes from tech companies building specific products like Adobe's new AI graphics software. Amazon is now starting to get interest from companies that are less tech-savvy too.
"The second category of customers are going to be startups and enterprises that actually don't either have the expertise or don't have the desire to build their own LLMs. What they essentially want to do is take something that is available publicly, fine tune it based on their datasets and use it for their applications to whatever extent possible."
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