Q&A with Viviane Clay, Director of the Thousand Brains Project
In this Q&A, we talked to the Viviane Clay, director of the Thousand Brains Project, Numenta’s new open-source research initiative.
In this Q&A, we talked to the Viviane Clay, director of the Thousand Brains Project, Numenta’s new open-source research initiative.
In this Q&A, we talked to the Viviane Clay, director of the Thousand Brains Project, Numenta’s new open-source research initiative.
Numenta Visiting Research Scientist Vincenzo Lomonaco, Postdoctoral Researcher at the University of Bologna, gives a machine learner’s perspective of HTM (Hierarchical Temporal Memory). He covers the key machine learning components of the HTM algorithm and offers a guide to resources that anyone with a machine learning background can access to understand HTM better.
Numenta Research Staff Member Lucas Souza shares his thoughts on the topic of sparsity in neural networks by diving into several different papers on the topic. He starts by examining the topic of pruning.
Three months into our experiment with livestreaming our research meetings, VP Marketing Christy Maver shares some of the highlights.
Numenta Research Staff Member Lucas Souza attended ICML 2019 with VP Research Subutai Ahmad. In this blog post, he shares the highlights and key takeaways of this year’s conference and reflects on the major themes related to our current machine learning research.
What does a livestream gaming platform have to do with Numenta? Matt Taylor explains how he found a window into research at Numenta in an unexpected place. Read on to learn more about the value of Twitch, the opportunities it provides, and how it might just save humanity.
In our most recent peer-reviewed paper published in Frontiers in Neural Circuits, A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex, we put forward a novel theory for how the neocortex works. In this updated blog about the Thousand Brains Theory of Intelligence originally published in March 2018, Jeff Hawkins and Christy Maver describe the key insights of our theory and how it compares to the classic view of the hierarchy, as well as its implications for AI.