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13 posts
In the last blog we looked at the phenomenon of “jagged intelligence” — the paradox that AIs are simultaneously superhuman and stupid in adjacent skills. We identified a lack of continual, fast learning and embodiment as possible causes of this weirdness, and noted that embodiment is also a “learning problem”, because current ML models can’t learn from a single thread of…
Authors: Hoang Long Dang and David RawlinsonUPDATE: Full HRM-Agent paper now available. When the Hierarchical Reasoning Model was released, we were very excited about its combination of small size and impressive reasoning abilities. These qualities seem to be enhanced by recurrent processing, but with a surprisingly simple gradient update based on the converged recurrent forward state — turning a…
Since the arrival of Chat GPT, I’ve felt that progress in AI has been largely incremental. Of course, even Chat GPT was/is mostly just a scaled up Transformer model, which was introduced by Vaswani et al in 2017. The belief that AI is advancing relatively slowly is a radical and unpopular opinion these days, and it’s been…
Over the last few years, there have been several breakthroughs and exciting new research directions in Reinforcement Learning, Hippocampus Inspired Architectures, Attention and Few-Shot Learning. There has been a move towards multi-component, heterogeneous, stateful architectures, many guided by ideas from cognitive sciences. Google DeepMind and Google Brain are leading the way making progress on several…
Today’s blog post is about Reinforcement Learning (RL), a concept that is very relevant to Artificial General Intelligence. The goal of RL is to create an agent that can learn to behave optimally in an environment by observing the consequences – rewards – of its own actions. By incorporating deep neural networks into RL agents,…
This month’s reading list has two parts: a non-Reinforcement Learning list, and a Reinforcement Learning list. Since our next blog post will be on Reinforcement Learning, readers might like to refer to our RL reading list separately. Non-Reinforcement Learning reading list A Framework for searching for General Artificial Intelligence Authors: Marek Rosa, Jan Feyereisl, The…
This article assesses the research paper, ‘A Distributional Perspective on Reinforcement Learning’ by the authors, Marc G. Bellemare, Will Dabney and Remi Munos, published in the proceedings of the 34th International Conference on Machine Learning (ICML) in 2017. Bellemare et al.’s paper will be assessed on several criteria. Firstly, content is assessed through providing some…
Digit classification error over time in our experiments. The image isn’t very helpful but it’s a hint as to why we’re excited :) Project AGI A few weeks ago we paused the “How to build a General Intelligence” series (part 1, part 2, part 3, part 4). We paused it because the next article in…
What’s AlphaGo? AlphaGo is a system that can play Go at least as well as the best humans. Go was widely cited as the hardest (and only remaining) game at which humans could beat machines, so this is a big deal. AlphaGo has just defeated a top-ranked human expert. AlphaGo Nature paper (Silver et al 2016)…
Erik Laukien is back with a demo of Sparse, Distributed Representation with Reinforcement Learning. This topic is of intense interest to us, although the problem is quite a simple one. SDRs are a natural fit with Reinforcement Learning because bits jointly represent a state. If you associate each bit-pattern with a reward value, it is…
This post is about a fantastic new paper by Michael R. Ferrier, titled: Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function The paper was posted to the NUPIC mailing list and can be found via: http://numenta.org/community-content.html The paper itself is currently hosted at:…
It’s exciting to see growing interest and participation in the AGI community. This is another brief post to share two examples. In this case, they both build on one approach to AGI, and that is HTM. FXAI – Explorations Into Computational Intelligence A blog that is pretty well described by the title. The author, Felix…
by David Rawlinson and Gideon Kowadlo The Blog This blog will be written by several people. Other contributors are welcome – send us an email to introduce yourself! The content will be a series of short articles about a set of common architectures for artificial general intelligence (AGI). Specifically, we will look at the…