When LLMs Level the Playing Field

Earlier generations of natural language processing and machine learning had some uses, the most recent generation of large language models has shown a significant reduction in human effort hours required to meet the same quality work product. Even small firms can recognize this benefit, as it allows them to manage tight timelines or large projects without needing to hire for their high water mark.

For low-level tasks, such as those that occur in diligence and discovery, there are clear economic benefits to using LLMs to automate these tasks. When models like GPT-4 are combined with knowledge graphs, the LLMs are capable of performing even more complex annotations and reasoning, as often occurs in contract drafting, negotiation, interpretation and strategic planning. As these trends continue, many of the historical strategies for competitive advantage will be rendered obsolete.

With the rise of tools that reduce the risk of hallucination – among other things – it’s become increasingly possible for smaller organizations to perform work that was previously impossible for them. When everyone has access to the same models and data, what will competitive advantage look like? Regardless law firms need to ensure their AI strategy is flexible and adaptable, to take advantage of new developments as they emerge.

Source: Kelvin legal






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