How is SELF different from LLMs?
AI platforms are commonly based on Large Language Models (LLMs) that are able to comprehend and generate human language. They work by analysing massive data sets of language. LLMs like ChatGPT, Bard and Llama crawl the entire web and leverage huge networks of AI chips to continually train their algorithms and improve their capabilities. When a user submits a query, the LLM draws on the information it was trained on, up until its last update.
SELF functions differently in that it generates each individual’s Personal Language Model, which resides under the user’s control and instruction. SELF can access a number of sources when responding to a user query, including search platforms, databases and LLMs. However, no personally identifiable data is used or shared.
Simplified, it works like this:
A user query triggers SELF to compile a range of anonymized preference information.
SELF takes into account the specific wording of the query, combines it with the compilation of preference information and sends a request to the other services as required.
One or more services return the results, SELF processes the information through the user’s preference filters.
Once quality and relevance checking processes are complete SELF provides the user with a hyper-personalised result.
#PersonalLanguageModel #AIPrivacy #HyperPersonalization #UserControlledAI