Our papers are the official record of our discoveries. They allow others to build on and apply our work. Each paper is the result of many months of research, so we make a special effort to make them clear, beautiful and inspirational, and publish them in leading journals.

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  • The working limitations of large language models

    Machine learning

    MBM. BurtsevMRM. ReevesAJ MIT Sloan Management Review

    The limits of LLMs

    Large language models like ChatGPT can generate human-like text but businesses that overestimate their abilities risk misusing the technology.

  • Taming complexity

    Theory of innovation

    MRM. ReevesSLTFT. FinkAL Harvard Business Review

    Taming complexity

    Insights from biology, physics and business shed light on the nature and costs of complexity and how to manage it in business organizations.

  • How much can we influence the rate of innovation?

    Theory of innovation

    TFT. FinkMRM. Reeves Science Advances

    The rate of innovation

    The distribution of product complexity helps explain why some technology sectors tend to exhibit faster innovation rates than other sectors.

  • Searching for great strategies

    Theory of innovation

    TFT. FinkPGMRM. Reeves Strategy Science

    The science of strategy

    The usefulness of components and the complexity of products inform the best strategy for innovation at different stages of the process.

  • Theory of innovation

    MIT Sloan Management Review

    The secret structure of innovation

    Firms can harness the shifting importance of component building blocks to build better products and services and hence increase their chances of sustained success.

  • Theory of innovation

    Nature Communications

    Serendipity and strategy

    In systems of innovation, the relative usefulness of different components changes as the number of components we possess increases.