New ‘SLED’ method cuts AI hallucinations by tapping earlier neural layers

Researchers have developed Self Logits Evolution Decoding (SLED), a technique that reduces AI hallucinations by analyzing multiple neural network layers rather than just the final output. While traditional large language models only use the last layer's result, SLED combines outputs from early and final layers to create more accurate responses. Testing showed SLED consistently improved truthfulness across various AI tasks without requiring major model modifications, offering a practical solution to AI reliability problems.