Google Unveils ‘HOPE’, a New AI Model Advancing Continual Learning

Published: 11 Nov 2025

Author: Precedence Research

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A leading global tech player, Google, just introduced a self-modifying architecture called HOPE. This new model is expected to perform better at long–term memory management than existing AI models that use state-of-the-art architectures. It's a major step for Google to build an AI system that continuously learns and improves without external interference. It is expected to serve as a proof-of-concept for a novel approach called nested learning devised by Google researchers. In this, a single model is considered a system of interconnected, multi-level learning problems that are optimized simultaneously. It works as a multi-level process rather than continuously, according to a Google post.

Google said, "We believe the Nested Learning paradigm offers a robust foundation for closing the gap between the limited, forgetting nature of current LLMs and the remarkable continual learning abilities of the human brain.”

According to the tech giant, this new model will help address limitations imposed by large language models, such as the need for continual learning, a critical stepping stone on the path to artificial general intelligence, intelligence that surpasses the human brain's capabilities so far.

In the last month, Andrej Karpathy, a widely respected and popular AI/ML research scientist who also works as a former employee at Google Deep Mind, said that AGI is still a decade away, mainly because no one has been able to develop an AI system that learns nonstop and constantly while working on its limitations every time, like a feedback loop does. He further said in his statement about AGI development and its future possibilities that, “they don’t have continual learning. You can’t just tell them something and expect them to remember it. They’re cognitively lacking, and it’s just not working. It will take about a decade to work through all of those issues”.

The researchers have published their findings in a paper with the title ‘Nested Learning: The Illusion of Deep Learning Architectures’ at NeurIPS 2025. Though LLMs are still capable of effectively owning AI chatbots so far, they have some limitations, such as not learning from experience like the human brain. Good. We are trying to resolve this issue by launching this innovative architecture; expect it to revolutionize AGI soon.