Value of Small Language Models and Constellation Model in AI Innovation

Small language models are becoming more beneficial for BDB applications with their improving performance and cost-effectiveness compared to larger models. The rapid commoditization of out-of-date models is evident in the significant pricing difference between models. This trend is expected to lead to a bifurcation of model sizes, with smaller models like llama three proving effective for certain tasks while larger models like the 440 billion parameter model are still being developed. The concept of a constellation model, where a query is processed by a classifier that could be generative or classical, is emerging as a strategy to optimize AI performance by using a combination of big and small models based on specific use cases.

Transcript

Play full episode

Transcript

Episode notes

Remember Everything You Learn from Podcasts

Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.

Get the app