Generative AI is quickly becoming a popular tool in the enterprise, with ChatGPT leading the way. As its use continues to expand, businesses are beginning to realize that generative AI’s future lies in smaller and more focused language models rather than a one-size-fits-all approach.
Smaller language models allow for greater customization of applications and services by focusing on specific tasks or areas of expertise. For example, if an organization needs assistance with customer service inquiries they can create a model specifically tailored for this purpose without having to worry about other aspects, such as product recommendations or sales support. This not only saves time but also allows companies to focus their resources where they will be most effective while still providing quality results from their generative AI system.
In addition, these smaller models can be implemented faster than larger ones since there is less data processing involved, which reduces development costs significantly compared to traditional methods such as natural language processing (NLP). Furthermore, it provides organizations with greater control over how their systems interact with customers since they have full visibility into what information is being processed and used by the model at any given time.
Overall, generative AI’s future in business looks promising due to its ability to provide customized solutions quickly and cost-effectively while giving organizations more control over how it interacts with customers through focused language models instead of relying on general-purpose approaches like NLP.
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