Since the arrival of ChatGPT, large language models have improved significantly, with GPT-4 achieving 95% accuracy on common sense reasoning, showcasing astounding advancements in generative AI.
Despite advancements, Gartner's 2024 hype cycle indicates that generative AI has passed its peak of inflated expectations, largely due to high costs and privacy concerns surrounding usage.
Smaller language models offer a potential solution to the drawbacks of larger models by being less costly to train and allowing on-premises hosting for better data control.
To optimize efficiency, enterprises are exploring domain-specific small models trained on domain-specific data, improving accuracy for particular use cases while reducing the need for extensive resources.
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