Korean Researchers Double AI Speed Without Losing Accuracy

Waiting for an AI chatbot to finish typing could soon become a thing of the past, thanks to researchers who just cracked one of artificial intelligence's biggest speed challenges.

Professor Yi Young-min and graduate student Song Geun-soo at Sogang University in Seoul developed a technique called oFFN that makes large language models respond up to twice as fast. Their breakthrough targets the most computation-heavy part of AI systems, the layer where chatbots do the heavy lifting to generate each word you see.

The secret lies in how AI processes information. Traditional systems perform every single calculation because they can't predict which ones matter most. The Sogang team discovered that certain extreme values, called outliers, appear in predictable spots during these calculations.

Their new method reorganizes how AI handles these computations, arranging them so the system can work smarter instead of harder. In tests, the technique boosted processing speed by up to 5.46 times in the core network layer. Real users noticed responses coming roughly twice as fast.

Here's the best part: the speed didn't come at a cost. The system maintained nearly identical accuracy and quality compared to slower versions. It even ran about 13 percent faster than other cutting-edge approaches that researchers had previously developed.

The international computer architecture conference ASPLOS 2026 has already accepted their paper for presentation. ASPLOS ranks among the most prestigious venues for computer systems research, making this recognition particularly meaningful for the Korean research team.

Why This Inspires

This breakthrough matters because billions of people now rely on AI chatbots for work, learning, and creative projects. Faster responses mean less waiting, more productivity, and smoother conversations with AI assistants. Students getting homework help, workers drafting emails, and creators brainstorming ideas will all benefit from technology that keeps pace with human thought.

The research also shows how innovation can make powerful technology more accessible. When AI runs faster, it requires less computing power and energy, potentially lowering costs and environmental impact. That could help more people around the world access these tools.

The team will present their findings in Pittsburgh this month, where researchers from across the globe gather to share advances in computer architecture. Their work proves that sometimes the biggest leaps forward come not from building bigger systems, but from teaching existing ones to work more intelligently.