Google's Nested Learning aims to stop LLMs from catastrophic forgetting
PositiveArtificial Intelligence

- Google Research has unveiled a new approach called 'nested learning' aimed at preventing large language models (LLMs) from experiencing catastrophic forgetting, thereby enhancing their ability to learn continuously without losing previously acquired knowledge.
- This development is significant for Google as it seeks to improve the reliability and performance of its AI models, particularly in light of recent benchmarks that have highlighted weaknesses in the factual accuracy of existing models, including its Gemini 3 Pro.
- The introduction of nested learning reflects a broader trend in AI development focused on enhancing model resilience and reliability, especially as competition intensifies among major players like OpenAI and Google, with ongoing discussions about the future of AI capabilities and ethical considerations.
— via World Pulse Now AI Editorial System







