Day 7
My Session Status
Sub Sessions
Reasoning is the action of drawing conclusions efficiently by composing learned concepts. In this presentation I’ll give a few examples illustrating why it is hard to learn to reason with current machine learning approaches. I will describe a general framework (generalization of the unseen) that characterizes most reasoning problems and out-of-distribution generalization in general, and give insights about intrinsic biases of current models. I will then present the specific problem of length ...
Large Language Models have displayed an uncanny ability to store information at scale and use it to answer a wide range of queries in robust and general ways. However, they are not truly generative in the sense that they depend on massive amounts of externally generated data for pre-training and lesser but still significant amounts of human feedback for fine-tuning. Conversely, cognitive architectures have been developed to reproduce and explain the structure and mechanisms of human cognition...
Human intelligence and that of today’s AI’s are just two points within a huge space of possible diverse intelligences. It is critical, for the development of both engineering advances and essential ethical frameworks, to improve our innately limited ability to recognize minds in unconventional embodiments. I will describe our work using the collective intelligence of body cells solving problems in anatomical and physiological spaces, to map out a framework for communicating with and understan...