Adopting large language models (LLMs) is not without its challenges, especially for enterprises.. To overcome these challenges and achieve maximum benefit from these models, the combination of composite AI with large language models is the best way forward for enterprises.
Better Control and Customization:
One of the main benefits of combining composite AI with large language models is the ability to have better control and customization over the models. Composite AI allows enterprises to combine multiple AI models to create a custom solution that fits their specific needs. This is particularly important for large language models, which can be too generic and may not provide the level of control that enterprises require.
Improved Accuracy and Performance:
Another benefit of the combination of composite AI with large language models is improved accuracy and performance. Large language models can generate huge amounts of data, which can be difficult to manage and interpret. Composite AI allows enterprises to use multiple models to analyze and interpret the data generated by large language models, leading to improved accuracy and performance. This is particularly important for applications such as customer service, where the accuracy of the model’s responses can have a significant impact on customer satisfaction.
Better Data Privacy and Security:
Data privacy and security are major concerns for enterprises when it comes to adopting large language models. Composite AI allows enterprises to control the data that is used by the models and ensures that sensitive information is properly secured. This can help to mitigate the risks associated with large language models and ensure that enterprises can adopt these models with confidence.
Lower Costs:
Adopting large language models can be expensive, both in terms of hardware and software costs. By combining composite AI with large language models, enterprises can reduce these costs and achieve more cost-effective solutions. This is because composite AI allows enterprises to use multiple models, each of which can be optimized for specific tasks, reducing the overall cost of the solution.
Better Integration with Existing Systems:
Large language models can generate huge amounts of data, which can be difficult to manage and integrate with existing systems. Composite AI allows enterprises to integrate multiple models and manage the data generated by large language models more effectively. This leads to better integration with existing systems and ensures that the data generated by the models is properly stored and managed.
In conclusion, the combination of composite AI with large language models is the best way forward for enterprises adopting large language models. By adopting this approach, enterprises can maximize the benefits of large language models and ensure that they are delivering the results they need.
PS: This is btw the opinion of ChatGPT itself
