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KAIST method cuts 87 % of AI query errors and token costs
KAIST method cuts 87 % of AI query errors and token costs SEOUL, September 04 (AJP) - When an artificial intelligence system writes a database query that will not run, the database that rejected it already knows what is wrong with it. Most systems treat that rejection as a plain failure signal and hand the whole query back to the AI to be written again from scratch. A team at the Korea Advanced Institute of Science and Technology has built software that reads the rejection as a set of directions and repairs only the broken piece. Tested September 4, 2026