The incomplete understanding of human brains and how to endow computers with common sense are among AI’s most enduring challenges. New research from DeepMind London, Imperial College London and the University of Cambridge argues that common sense in humans is founded on a set of basic capacities that are also possessed by many other animals, and that animal cognition can therefore serve as inspiration for many AI tasks and curricula.
In a paper published in Trends in Cognitive Sciences journal this month, the researchers identify just how much AI research might benefit from the field of animal cognition.
There is no universally accepted definition of “common sense.” While much research has used language as a touchstone, the new paper temporarily sets language aside to focus on other common sense capacities found in non-human animals. …
Historians and nostalgic residents alike take an interest in how cities were constructed and how they developed — and now there’s a tool for that. Google AI recently launched the open-source browser-based toolset “rǝ,” which was created to enable the exploration of city transitions from 1800 to 2000 virtually in a three-dimensional view.
Google AI says the name rǝ is pronounced as “re-turn” and derives its meaning from “reconstruction, research, recreation and remembering.” This scalable system runs on Google Cloud and Kubernetes and reconstructs cities from historical maps and photos.
There are three main components to the toolset.
Warper is a crowdsourcing platform,where users can upload photos of historical print maps and georectify them to match real world coordinates. These can then be converted to an OpenStreetMap (OSM) vector format with an Editor app. …
Modern AI has produced models that exceed human performance across countless tasks. Now, an international research team is suggesting AI might become even more efficient and reliable if it learns to think more like worms.
In a paper recently published in Nature Machine Intelligence journal, the team from MIT CSAIL, TU Wien in Vienna, and IST Austria proposes an AI system that mimics biological models. The system was developed based on the brains of tiny animals such as threadworms and is able to control a vehicle using just a small number of artificial neurons.
Modern AI has produced models that exceed human performance across countless tasks. Now, an international research team is suggesting AI might become even more efficient and reliable if it learns to think more like worms. …