Larger language models are not necessarily better as companies seek returns on AI investments
Small language models – streamlined versions of larger ones – are expected to gain popularity
LARGE language models (LLMs) – artificial intelligence (AI) systems such as ChatGPT that process vast amounts of text data to comprehend and generate human language – have been touted as a game changer with the potential to make workers far more productive, or even replace them in certain jobs.
But, powerful as they may be, industry watchers believe that LLMs will need to be leaner and less expensive to run before they are more widely adopted in commercial use cases.
Sri Ambati, founder and chief executive of AI startup H2O.ai, noted that LLMs have been effective at demonstrating that computers can answer questions about a wide range of topics.
However, applying LLMs to a call-centre AI agent would be akin to asking someone with a doctorate to answer the phone quickly and effectively, he said.
Moreover, the cost of AI applications powered by LLMs can be prohibitive, Ambati added.
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