How RAG Will Usher In the Next Generation of LLMs and Generative AI
Retrieval-augmented generation may provide a big step forward in addressing many of the issues that keep enterprises from adopting AI.
Retrieval-augmented generation may provide a big step forward in addressing many of the issues that keep enterprises from adopting AI.
Retrieval-augmented generation may provide a big step forward in addressing many of the issues that keep enterprises from adopting AI.
In our paper, A Theory of How Columns in the Neocortex Enable Learning the Structure of the World, we proposed that a single cortical column can learn models of complete objects through movement. Jeff Hawkins and Christy Maver explain our “Thousand Brains Model of Intelligence” and its implications for AI in this blog.
Neuromorphic chips, which emulate neurons in silicon, are essentially the hardware for the future of AI. The Human Brain Project’s Neuromorphic team recently unveiled a chip called BrainScaleS-2 that models neurons consistent with the model described in our 2016 paper “Why Neurons Have Thousands of Synapses.”
Earlier this year, the Simons Institute at Berkeley kicked off a new program called The Brain and Computation. Numenta research engineer Scott Purdy attended the workshop, Representation, Coding and Computation in Neural Circuits, and shares how the workshop relates to Numenta’s brain theory in this blog.
Numenta has two missions: reverse-engineer the neocortex to understand how we learn and behave and enable technology based on brain theory. Our progress to date can be summarized by two important discoveries. Here’s a summary of Numenta’s brain theory, as explained by Christy Maver.
How does Numenta’s theory compare to Geoffrey Hinton’s capsule theory? Subutai Ahmad, Numenta VP Research, shares his thoughts and breaks down the similarities and differences in this blog comparing HTM and capsules.
The Brain Science Podcast features recent discoveries about neuroscience and interviews with scientists around the world. In this episode of the Brain Science Podcast, Jeff Hawkins explains how our latest research uncovers a key feature of cortical function that has been completely missed: a location signal.