For the past few weeks, I’ve been engaged in an email exchange with my favourite anarcho-syndicalist Noam Chomsky. I reached out to him initially to ask whether recent developments in ANNs (artificial neural networks) had caused him to reconsider his famous linguistic theory Universal Grammar. Our conversation touched on the possible limitations of Deep Learning, how well ANNs really model biological brains and also meandered into more philosophical territory. I’m not going to quote Professor Chomsky directly in this article as our discussion was informal but I will attempt to summarise the key take-aways. Read More
Daily Archives: December 8, 2020
Model describes complete grasping movement planning in the brain
Neuroscientists at the German Primate Center (DPZ)-Leibniz Institute for Primate Research in Göttingen have developed a model that can seamlessly represent the entire planning of movement from seeing an object to grasping it. Comprehensive neural and motor data from grasping experiments with two rhesus monkeys provided decisive results for the development of the model, an artificial neural network that is able to simulate processes and interactions in the brain after training with images of specific objects. The neuronal data from the artificial network model were able to explain the complex biological data from the animal experiments and thus prove the validity of the functional model. This could be used in the long term for the development of better neuroprostheses, for example, to bridge the damaged nerve connection between brain and extremities in paraplegia and thus restore the transmission of movement commands from the brain to arms and legs. Read More
Use real-time anomaly detection reference patterns to combat fraud
Businesses of every size and shape have a need to better understand their customers, their systems, and the impact of external factors on their business. How rapidly businesses mitigate risks and capitalize on opportunities can set apart successful businesses from businesses that can’t keep up. Anomaly detection—or in broader terms, outlier detection—allows businesses to identify and take action on changing user needs, detect and mitigate malignant actors and behaviors, and take preventive actions to reduce costly repairs.
The speed at which businesses identify anomalies can have a big impact on response times, and in turn, associated costs.
… At Google Cloud, our customer success teams have been working with an increasing number of customers to help them implement streaming anomaly detection. In working with such organizations to help them build anomaly detection systems, we realized that providing these reference patterns can significantly reduce the time to solution for those and future customers. Read More
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