1월 1, 2026

✨ 2026년에 기업팀이 주목해야 할 4가지 AI 연구 동향

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The AI narrative has mostly been dominated by model performance on key industry benchmarks. But as the field matures and enterprises look to draw real value from advances in AI, we’re seeing parallel research in techniques that help productionize AI applications. At VentureBeat, we are tracking AI r

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The AI narrative has mostly been dominated by model performance on key industry benchmarks. But as the field matures and enterprises look to draw real value from advances in AI, we’re seeing parallel research in techniques that help productionize AI applications. At VentureBeat, we are tracking AI research that can help understand where the practical implementation of technology is heading. We are looking forward to breakthroughs that are not just about the raw intelligence of a single model, but about how we engineer the systems around them. As we approach 2026, here are four trends that can represent the blueprint for the next generation of robust, scalable enterprise applications.Continual learningContinual learning addresses one of the key challenges of current AI models: teaching them new information and skills without destroying their existing knowledge (often referred to as “catastrophic forgetting”).Traditionally, there are two ways to solve this. One is to retrain the model wi

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