Summary Bullets:

• As training techniques improve, small language models (SLMs) are becoming more and more accurate, increasing their appeal.
• The smaller models make sense for simpler tasks; they can work offline and are a good alternative when organizations want to process information close to the source of collection.

The generative AI (GenAI) landscape has been evolving at breakneck speed since OpenAI exploded onto the scene in late 2022.  And despite the numerous new GenAI solutions and product enhancements already brought to market in the last 18 months, momentum around natural language processing (NLP) shows no signs of slowing down. The latest buzz worth paying attention to is around SLMs, which offer capabilities similar to large language models (LLMs) but require far less training data and processing power.  Easier to adopt, less expensive to run, and with a smaller carbon footprint, these models hold the potential to further accelerate the already rapid pace of GenAI adoption.

Continue reading “Generative AI Watch: Small Language Models’ Growing Role in a Multi-Model World” →