Data Action Layer May 8, 2023
Powerful large language models (LLMs) like GPT are opening up new possibilities for integrating advanced AI and machine learning into business workflows. While there’s a lot of excitement around the fast-moving advances in AI, there’s also uncertainty around how these technologies can fit into enterprise technology architectures. Information security is a major concern for any business, and the advent of GPT and generative AI challenges our existing understanding of data use, while presenting new opportunities to leverage data. If you use GPT to help process your business and customer data, how is that data handled? Are the security provisions for how your data is used changing, or likely to change in the future? What’s the difference between ChatGPT and just GPT? Questions like these are top of mind for our customers.
To use this new technology safely and effectively, it’s important to first understand the difference between the models themselves and the tools that use them, and what that means for your data.
ChatGPT is a chatbot built on OpenAI’s GPT large language model. The tool is free to use, and in return, its default setting is to learn from your input, storing your conversations and training itself with your data to better answer others’ questions in the future (this setting can be manually toggled off by the user). In response to the security concern that user conversations are stored on external servers and may be used for training, some companies (and countries) are banning ChatGPT on corporate devices to prevent employees from inadvertently sharing company data. At Alkymi, we do not process any customer data using ChatGPT.
Microsoft, however, offers OpenAI’s GPT models through the enterprise-level Azure OpenAI Service REST API. When using the API, all data sent and received is encrypted (both at rest and in transit), only stored temporarily, and not used for training the model. User prompts are not made available to other users, under any circumstances. Tools and products built using the GPT models from enterprise APIs like Azure’s give companies and end users the opportunity to utilize GPT to power their workflows without putting their data at risk.
To be confident in your data security, you need to understand where your data is going, how it’s being used, and stay up to date on any changes. We’ve been working with LLMs at Alkymi since our launch in 2017, and we’re used to meeting demanding enterprise architecture requirements for some of the world’s leading financial services firms. To date, we’ve built most of our data extraction models in-house. Powering our platform with LLMs like GPT through the Azure API, as well as with Alkymi-created and self-hosted large language (and many other kinds of) models, means we can deliver new innovative solutions to our customers while maintaining high standards for data security and privacy.
Our GPT-powered products and features are built using our own secure deployment. Our customers’ data is encrypted and not used to train other companies’ models. Your data remains yours. You’re in complete control of how it’s handled, from how it’s hosted—with the option for SaaS or private cloud deployments—to determining precisely where your data flows. Where needed, Alkymi can limit GPT results to a set of approved sources, eliminating the possibility of answers being drawn from within the model’s training set. We’re also launching new GPT-powered data enrichment features this year that will allow you to automatically query the model to fill in the gaps in your data, without sharing source documents publicly.
GPT is a powerful new tool for your business. Leveraging it in the right way with the right security in place can give you a competitive advantage, unveil new ways to utilize your data, and help you make better, faster, and more accurate decisions.
Find out how Alkymi’s GPT-powered products can unlock your data securely with a demo today.
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