Stop Using Public Chatbots and Create Your Own Instead
AI chatbots are becoming widespread in areas such customer service, marketing, and operational matters. With a variety of open and free-to-use large language models (LLMs) available, the most prominent being Open AI’s ChatGPT, employees have turned to these AI assistants to help them in their daily jobs. In addition to privacy concerns that make the headlines, there are other reasons why companies and their IT departments should “roll their own” when it comes to these tools.
Why Shift to Private LLMs?
1. Customization is Key
Private LLMs offer high customization, allowing responses to be tailored to your company’s specific needs. Imagine a chatbot that understands and interacts based on your policy manuals, product catalogs, technical references, or sales plans. Additionally, content in the knowledge base can be as current as you are able to keep it. This level of personalization can boost your customer service and sales and marketing efforts, and increase internal operational efficiency.
2. Enhanced Content Ingestion
Public models often struggle to fully and coherently process large volumes of specialized material. Private LLMs leverage advanced tools to overcome these limitations, ensuring your unique content is understood and incorporated completely into the custom bot’s knowledge base.
3. Safeguarding Intellectual Property
The confidentiality of company information and intellectual property is perhaps the top concern. Companies have now largely put policies in place prohibiting the significant use of public LLMs, though they were slow to respond initially. Private LLMs provide a secure environment where sensitive data remains protected from leaks that get out in the wild, or that may be used to train future public LLMs.
4. Bias and Ethical Control
Many of the headlines regarding LLMs relate to inadvertent bias and ethical issues. Private LLMs offer better control, allowing you to align the technology closely with your organizational values and legal requirements.
The Union Pacific Approach
An example of private LLM success can be found at Union Pacific, one of America’s leading railroads. They wanted to harness the power of private LLMs to reap benefits in operational efficiency while maintaining data security. Union Pacific’s approach demonstrates the practical applicability and advantages of custom AI solutions. Learn more about their story.
Moving Forward
As with most new technologies, and perhaps more so with Generative AI, there has been a lot of hype and some hyperventilating about them. But the pattern still holds that, after you cut through the hype, and assuage the privacy and ethics fears, there can be some well-defined solutions that work.
We invite you to explore a sample of these on our Generative AI page and discover how First Analytics can help you use the power of private LLMs for your business.
Disclosure: a small portion of this post was written by an AI, with human prompting. Check out our generative AI disclaimer.