Artificial General Intelligence (AGI) is the holy grail of AI research, which aims to create machines capable of understanding, learning, and applying knowledge across a wide range of tasks. Lifelong Learning Machines (LLMs) are a step towards AGI, designed to learn continuously from experience, much like humans do.
LLMs are currently limited by their inability to generalise knowledge across tasks, but foundational models may hold the solution. These models, trained on vast datasets, can learn a broad base of knowledge that can be fine-tuned for specific tasks, allowing them to adapt to new situations more effectively.
The combination of LLMs and foundational models is a promising approach to AGI. By providing a general knowledge base, foundational models can enable LLMs to learn continuously and adapt to new tasks more effectively. This could revolutionise the field of AI, bringing us closer to the dream of AGI.
However, this approach also raises important ethical and societal concerns. The use of large datasets in training foundational models can lead to privacy issues, and the models themselves can be biased or unfair. Careful governance and regulation will be crucial to ensure the responsible development and use of these technologies.
Go to source article: https://towardsdatascience.com/towards-agi-llms-and-foundational-models-roles-in-the-lifelong-learning-revolution-f8e56c17fa66