幻方量化、DeepSeek-V3を発表：GPT-4に匹敵する性能、大幅に低減された訓練コスト
幻方量化は12月26日夜、次世代大規模言語モデルDeepSeek-V3を発表し、驚異的な技術的ブレークスルーを示しました。MoE（Mixture of Experts）アーキテクチャを採用したこのモデルは、トップレベルのクローズドソースモデルに匹敵する性能を示すだけでなく、低コストで高効率である点が業界の注目を集めています。主要なパラメーターとしては、DeepSeek-V3は6710億パラメーター（活性化パラメーター370億）を備え、14.8兆トークンのデータ規模で事前学習が行われました。前世代モデルと比較して、新モデルの生成速度は3倍に向上しています。
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