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Continual Learning Futures

Chart pathways beyond static language models by integrating continual learning, hybrid architectures, and on-the-job adaptation.

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Further reading and reference materials

  1. Continual learning surveys (2024–2025) – taxonomy of techniques and open challenges.
  2. Hybrid systems research from reinforcement learning pioneers (2025) – combining policy learning with language models.
  3. Safety oversight frameworks for adaptive AI (2024–2025) – governance patterns during continuous updates.
  4. Memory-augmented model case studies (2025) – architecture choices and deployment lessons.
  5. Regulatory whitepapers on adaptive AI (2025) – anticipated requirements for disclosure and auditability.
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