What can LLMs do and more importantly, not do?

 

A very interesting position paper worth a read for any follower of AI: “LLMs Can't Jump: Why the Abductive Leap is the Final Frontier of AI Discovery.” The thought is simple. AI may be good at some forms of inference, like deduction and induction, but it is not able to do the third type: abduction. “While AI can compress data (Induction) and prove theorems (Deduction), it cannot yet recreate the intuitive leap Albert Einstein took to formulate the axioms of General Relativity—a process rooted in embodied physical simulation rather than symbolic manipulation.”

The Three Pillars of Inference

The paper adopts the framework of Charles Sanders Peirce to categorize AI’s missing link:

• Deduction (Rule + Case → Result): Applying a known law to a specific situation. (AI status: SOTA - Achieved)
• Induction (Case + Result → Rule): Spotting patterns in data to find a general rule. (AI status: SOTA - Achieved)
• Abduction (Rule + Result → Case/New Rule): Inventing a hypothesis to explain a surprising or singular phenomenon. (AI status: The Missing Jump)

There is still room for importing thinking by analysts. The market has to understand which skills are important for analysts and what can be done by quants.