基礎研究を中心におきながら，変化の早い社会の要請に応えるために，常に応用・社会実装を見据えた問題抽出と課題解決を意識した研究活動を行っています。半年程度の成果が見込める研究と，２，３年かけて取り組むテーマを両立させることで，継続的なインテグレーションを実現します。

While focusing on fundamental studies on AI, our research activities are always focused on problem extraction and problem-solving for application and social implementation in order to meet the demands of a rapidly changing society. Continuous integration can be achieved by combining research that can be expected to yield results in about six months with themes that can be tackled over two or three years.

近年大きな飛躍を遂げた人工知能と機械学習の技術をさらに高度化し，様々な分野でイノベーションの創出が期待できる画期的な知能化技術・理論の確立をめざしています。とくに，効率的・高速な学習アルゴリズムや，学習結果の再利用・転移のしくみを明らかにすることにより，実環境でオンライン・ロバストに動作する知的要素技術を実現します。また，最先端の機械学習技術を追求しながらも，他領域の技術・考え方も柔軟にとりいれ，新たな知能システム分野の開拓，融合分野の深化をはかります。

We aim to establish groundbreaking intelligence technologies and theories that are expected to create innovations in a variety of fields by further advancing the technologies of artificial intelligence and machine learning, which have made great strides in recent years. In particular, by clarifying efficient and fast learning algorithms and the mechanisms of reuse and transfer of learning, we will realize intelligent elemental technologies that work online and robustly in real environments. While pursuing the latest machine learning technologies, we will also flexibly incorporate technologies and ideas from other fields to develop new fields of intelligent systems and deepen the integration of these fields.

医療は高度な医学知識と多くのデータに基づく高度な知能システムであるという視点から，人工知能による医師の意思決定や業務を支援する様々な応用研究を進めています。特に，生活習慣病予防や未病対策にむけた知的ヘルスケアアプリケーションや，高度福祉やリハビリテーションに応用可能な知的ロボット制御など，ライフサイエンス全体にわたる知能化環境・サービスの実現をめざした要素技術と設計論を提案し，人類の健康と福祉に貢献していきます。

From the viewpoint that medicine is an advanced intelligence system based on advanced medical knowledge and a large amount of data, we are conducting research on various applications of artificial intelligence to support doctors' decision-making and business operations. In particular, we will contribute to the health and welfare of mankind by proposing elemental technologies and design theories for the realization of intelligent environments and services throughout the life sciences, such as intelligent healthcare applications for lifestyle disease prevention and prevention of pre-morbidities, and intelligent robot control for advanced welfare and rehabilitation.

老朽化が進むインフラや大規模システムにおいて，これまで人間の経験や勘にたよっていた様々なモノのライフサイクル管理を，人工知能によって効率化・高度化することで，保守作業の効率化，モノの自律的リノベーション，安全・安心な社会の持続的発展に貢献する研究に取り組んでいます。機器・機械・システム固有の運転・運用をオンラインで監視しながら，正常からの逸脱度を定量化するシステムの開発を，企業とともに進めています。

In aging infrastructures and large-scale systems, artificial intelligence is expected to improve the efficiency and sophistication of lifecycle management of various objects, which was previously based on human experience and intuition. We are engaged in research that contributes to the efficiency of maintenance work, the autonomous renovation of things, and the sustainable development of a safe and secure society.  We are working with companies to develop a system that quantifies the degree of deviation from normal while monitoring the operation and operation of equipment, machines, and systems.