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Can Neural Networks Show Imagination? DeepMind Thinks they Can

#artificialintelligence

I recently started a new newsletter focus on AI education. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Creating agents that resemble the cognitive abilities of the human brain has been one of the most elusive goals of the artificial intelligence(AI) space. Recently, I've been spending time on a couple of scenarios that relate to imagination in deep learning systems which reminded me of a very influential paper Alphabet's subsidiary DeepMind published last year in this subject.


AI diagnoses Alzheimer's with more than 95% accuracy

#artificialintelligence

An artificial intelligence (AI) algorithm has produced another significant breakthrough using attention mechanisms and a convolutional neural network to …


Can Neural Networks Show Imagination? DeepMind Thinks They Can - KDnuggets

#artificialintelligence

I recently started a new newsletter focus on AI education. TheSequence is a no-BS (meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Creating agents that resemble the cognitive abilities of the human brain has been one of the most elusive goals of the artificial intelligence(AI) space. Recently, I've been spending time on a couple of scenarios that relate to imagination in deep learning systems which reminded me of a very influential paper Alphabet's subsidiary DeepMind published last year in this subject.


Future of AI Part 2

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This part of the series looks at the future of AI with much of the focus in the period after 2025. The leading AI researcher, Geoff Hinton, stated that it is very hard to predict what advances AI will bring beyond five years, noting that exponential progress makes the uncertainty too great. This article will therefore consider both the opportunities as well as the challenges that we will face along the way across different sectors of the economy. It is not intended to be exhaustive. AI deals with the area of developing computing systems which are capable of performing tasks that humans are very good at, for example recognising objects, recognising and making sense of speech, and decision making in a constrained environment. Some of the classical approaches to AI include (non-exhaustive list) Search algorithms such as Breath-First, Depth-First, Iterative Deepening Search, A* algorithm, and the field of Logic including Predicate Calculus and Propositional Calculus. Local Search approaches were also developed for example Simulated Annealing, Hill Climbing (see also Greedy), Beam Search and Genetic Algorithms (see below). Machine Learning is defined as the field of AI that applies statistical methods to enable computer systems to learn from the data towards an end goal. The term was introduced by Arthur Samuel in 1959. A non-exhaustive list of examples of techniques include Linear Regression, Logistic Regression, K-Means, k-Nearest Neighbour (kNN), Naive Bayes, Support Vector Machine (SVM), Decision Trees, Random Forests, XG Boost, Light Gradient Boosting Machine (LightGBM), CatBoost. Deep Learning refers to the field of Neural Networks with several hidden layers. Such a neural network is often referred to as a deep neural network. Neural Networks are biologically inspired networks that extract abstract features from the data in a hierarchical fashion.


Why Top Machine Learning Conferences Should Promote Art & Creativity

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One cannot, in all their seriousness, comprehend what went into writing the "Requiem for a dream" or painting the frescoes on the ceiling of the Sistine Chapel. But, what happens when this intelligence is augmented with an external entity, an algorithm? Artificial intelligence has intruded into the space of creativity, the final frontier of the human intellect, through algorithms such as Generative Adversarial Networks (GANs). GANs have become fertile tools for artistic exploration. Artists such as Refik Anadol, Robbie Barrat, Sofia Crespo, Mario Klingemann, Jason Salavon, Helena Sarin, and Mike Tyka generate fascinating imagery with models learned from natural imagery.


DeepMind Explores Deep RL for Brain and Behaviour Research

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As a basis for modelling brain function, deep learning has in recent years been used to model systems in vision, audition, motor control, navigation, and cognitive control. In a new paper, DeepMind researchers call attention to another "fundamentally novel" development in AI research -- deep reinforcement learning (deep RL) -- which they believe also has vital implications for neuroscience and deserves more attention from neuroscientists. The first neuroscience applications of supervised deep learning can be traced back to the 1980s. The increasing availability of more powerful computers over the past decade has renewed research efforts in applying AI approaches -- especially supervised deep learning -- to neuroscience. Deep RL unites deep learning and reinforcement learning, a computational framework that has already had a substantial impact on neuroscience research.


AI Can Read and Visualize Our Thoughts

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Imagine a computer-based system visualizing your thoughts and secret thoughts; yes, it's possible now by artificial intelligence assistance. Recent advancements in hardware innovation have re-energized technology. It becomes more accurate, authentic, can produce better sound, accurate visualization, and understanding of the location. Outstanding computer processors support computer to make a decision, plan outputs and don't repeat the mistake as they learn from it. The four scientists in Kyoto at Kyoto University did an exceptional experiment that exceeds the global expectations about such a dreamy truth. They have done their experiment in ATR Computational Neuroscience Laboratories. The artificial intelligence system becomes so smart and real to duplicate human minds and show what they're thinking in their minds.


Artificial Intelligence for Precision Medicine and better Healthcare

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Precision medicine is a medical model, which proposes customization of the healthcare to a subgroup of patients, based on a genetics, lifestyle and environment. This technique allows doctors and researchers to prognosis treatment and prevention strategies for a specific disease which can work on a group of people. It is opposed to a one-size-fits-all approach, in which disease treatment and prevention techniques are advanced for the average individual with much less attention for the variations among individuals. There is an overlap between the terms "precision medication" and "personalized medicine." As per the National Research Council, "personalized medicine" is a traditional word with a meaning close to "precision medication."


How neural networks work - A simple introduction

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Last updated: June 17, 2020. Which is better--computer or brain? Ask most people if they want a brain like a computer and they'd probably jump at the chance. But look at the kind of work scientists have been doing over the last couple of decades and you'll find many of them have been trying hard to make their computers more like brains! With the help of neural networks--computer programs assembled from hundreds, thousands, or millions of artificial brain cells that learn and behave in a remarkably similar way to human brains. What exactly are neural networks?


Artificial Intelligence for Precision Medicine and better Healthcare

#artificialintelligence

Precision medicine is a medical model, which proposes customization of the healthcare to a subgroup of patients, based on a genetics, lifestyle and environment. This technique allows doctors and researchers to prognosis treatment and prevention strategies for a specific disease which can work on a group of people. It is opposed to a one-size-fits-all approach, in which disease treatment and prevention techniques are advanced for the average individual with much less attention for the variations among individuals. There is an overlap between the terms "precision medication" and "personalized medicine." As per the National Research Council, "personalized medicine" is a traditional word with a meaning close to "precision medication."