We’re very excited to launch AGI Experimental Framework, AGIEF, our open source framework. We first introduced it a while back, at the end of 2015 here, and it has certainly come a long way. AGIEF was created to make running rigorous AI experiments convenient, reproducible and scalable. The goals are:… Read More »AGI Experimental Framework
Our brain is a source of great inspiration for the development of Artificial General Intelligence. In fact, one of the common views is that any effort in developing human-level AI is almost destined to fail without an intimate understanding of how the brain works. However, we do not understand our… Read More »Unsupervised Learning with Spike-Timing Dependent Plasticity
Today’s post tries to fit the theoretical concept of Predictive Coding with the unusual structure and connectivity of Pyramidal cells in the Neocortex. Pyramidal neurons Pyramidal neurons are interesting because they are one of the most common neuron types in the computational layers of the neocortex. This almost certainly means… Read More »Pyramidal Neurons and Predictive Coding
Hello everyone! I am Yi-Ling and I am the newest member of the AGI project team. It is an incredibly exciting time to be dipping one’s toes in the field of Artificial Intelligence, given the impressive progress and explosion of AI applications in recent years. In my case, I am… Read More »Introducing Yi-Ling
In our most recent post we discussed the current set of experiments that we are conducting, using the MNIST dataset. We’ve also been looking at the NIST dataset which is similar, but extends to handwritten letters (as well as digits). These are extremely popular datasets and freely available, so make… Read More »Open Sourcing MNIST and NIST Preprocessing Code
Typical results from our experiments: Some active cells in layer 3 of a 3 layer network, transformed back into the input pixels they represent. The red pixels are positive weights and the blue pixels are negative weights; absence of colour indicates neutral weighting (ambiguity). The white pixels are the input… Read More »Region-Layer Experiments
Figure 1: The Region-Layer component. The upper surface in the figure is the Region-Layer, which consists of Cells (small rectangles) grouped into Columns. Within each Column, only a few cells are active at any time. The output of the Region-Layer is the activity of the Cells. Columns in the Region-Layer… Read More »The Region-Layer: A building block for AGI
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… Read More »Reading list – May 2016
A Minecraft API is now available to train your AGIs Our News We are working hard on experiments, and software to run experiments. So this week there is no normal blog post. Instead, here’s an eclectic mix of links we’ve noticed recently. First, AlphaGo continues to make headlines. Of interest… Read More »Reading list: Assorted AGI links. March 2016
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… Read More »What’s after AlphaGo?