We all know about large language models (LLMs) that are facilitating computers to generate and process big data, enabling them to respond to natural language questions. But now, small language models (SLMs), which have the capability to generate human-like language and are trained on datasets that are limited, are also becoming all the rage. It is understood that they can be trained and used easily, besides being more cost-effective and using less computational power, making them ideal for specific tasks. Big tech giants Microsoft, Google, Meta, Amazon and others are investing billions in developing generalpurpose LLMs to handle a variety of tasks, but they might not be able to be customised for certain needs. They may require a smaller version of generative AI.
Infosys chief technology officer Mohammed Rafee Tarafdar was recently quoted as saying that several small language models for India-specific needs have already been launched and with a growing developer base, a lot more GenAI applications will be implemented for Indian and global markets. Last year saw several launches of lightweight models such as Microsoft's Phi family of SLMS, Google's Gemma and a smaller variant of Meta's Llama model. Microsoft's Sundar Srinivasan was also quoted as saying that while LLMs have pushed the boundaries of accuracy across various AI tasks throughout 2024, SLMs have driven mass adoption and true democratisation of AI. Industry experts are certainly looking at SLMs as the next big thing in AI.
A godfather's warning
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