LLMs + Ontologies
Within organisations, Large Language Models (LLMs) are gaining increasing significance. This is not just a fleeting fad but part of a transformative shift that all forward-thinking organisations must come to terms with. I believe, for an organisation to succeed in this transition, effectively leveraging ontologies is a crucial factor.
LLMs possess remarkable AI capabilities, allowing them to comprehend and generate human-like text by learning intricate patterns from vast volumes of training data. These powerful models are capable of crafting eloquent letters, analysing data, generating code, orchestrating workflows, and performing a myriad of other complex tasks. Their potential seems increasingly disruptive, with Microsoft even 'betting the house' on them.
However, when deploying LLMs within an enterprise context, reliability, trustworthiness, and understandability are vital concerns for those running and governing these systems. Hallucination is simply not an option.
Ontologies offer structured and formal representations of knowledge, defining relationships between concepts within specific domains. These structures enable computers to comprehend and reason in a logical, consistent, and comprehensible manner. Yet, designing and maintaining ontologies requires substantial effort. Before LLMs came along, they were the ‘top dog in town’ when it came to a semantic understanding, but now they seem relatively inflexible, incomplete and slow to change.
Enter the intriguing and powerful synergy created by the convergence of LLMs AND Ontologies. The ability of LLMs to generate and extend ontologies is a game-changer. Although you still need a 'human-in-the-loop,' the top LLMs demonstrate surprising effectiveness. Simultaneously, ontologies provide vital context to the prompts given to LLMs, enriching the accuracy and relevance of the LLM's responses. Ontologies can also be used to validate the consistency of those responses.
🔍 The LLMs help discover new knowledge, and the ontologies compile that knowledge down for future use🔍
This collaborative partnership between LLMs and ontologies establishes a reinforcing feedback loop of continuous improvement. As LLMs help generate better ontologies faster and more dynamically, the ontologies, in turn, elevate the performance of LLMs by offering a more comprehensive context of the data and text they analyse. I believe this positive feedback loop has the potential to catalyse an exponential leap in the capabilities of AI applications within organisations, streamlining processes, adding intelligence, and enhancing customer experiences like never before.
