How some Large Language Models use your know-how to improve the model?

Using public API to interact with Large Language Models poses a significant risk to companies, undermining their ability to safeguard proprietary information and intellectual property. These models, typically hosted by third-party providers, possess the capability to process and analyze vast amounts of data, including sensitive corporate information. As a result, companies that utilize these API are exposed to the potential loss of confidential data and the potential for malicious actors to exploit vulnerabilities in the model's architecture.

To mitigate these risks, companies must exercise due diligence in selecting and implementing these models while also implementing robust security measures to protect sensitive information.

Let’s imagine you are a very well-known Alaskan salmon fisherman and want to write a book about your life. In that book, you will describe the things other fishermen won’t: you write down the physical location of the best spots for Alaska salmon. Even though you are the best fisherman of your generation, you are not a great writer. Next thing you do: you open a window on your browser, go to your favorite publicly available LLM and feed it with your text that identifies your very secret fishing spots and expect LLM to produce a better text. Next thing you know, the next version of the publicly available LLM will give the right answer to whoever asks “where are the best fishing spots in Alaska?” before you have the time to publish your book.

One solution to the risks associated with public language models is to use on-premise models instead. These models are hosted on servers owned by the organization, which reduces the risk of relying on the knowledge and expertise of external model creators. LightOn provides and deploys LLMs to your servers (On prem or private cloud) .LightOn offers Paradigm as the solution that enables organizations to build and run language models on their servers.

Paradigm platform paves the way to tailor language models to the specific needs and use cases of the Enterprise rather than being limited to the capabilities of public models.

In terms of performance, LightOn's language models are on par with other state-of-the-art models, such as ChatGPT. They can generate high-quality responses and make accurate predictions about the likelihood of a sequence of words.

Overall, LightOn's Paradigm is a robust and reliable solution for organizations using hosted language models for NLP tasks. They offer the benefits of private models, such as control over data and the ability to tailor the model to specific needs. They also provide the high performance and capabilities of models like ChatGPT.

In summary, utilizing public Large Language Models entails certain dangers for organizations, owing to their reliance on the expertise and knowledge of external model creators. An alternative approach to mitigate these risks is the implementation of on-premise models, which are hosted on servers owned by the organization. LightOn's Paradigm provides a robust and dependable solution that confers the benefits of on-premise models, such as data sovereignty and the capability to tailor the model to specific requirements, while offering comparable performance and functionality as models like ChatGPT. Paradigm can be equally hosted through a private cloud to obviate the dangers associated with public Large Language Models or private cloud.

Read more:

https://www.darkreading.com/risk/employees-feeding-sensitive-business-data-chatgpt-raising-security-fears