The limitations of deep learning (advanced topic)
This post is adapted from Section 2 of Chapter 9 of my book, Deep Learning with Python (Manning Publications). It is part of a series of two posts ...
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Neural Networks and Deep Learning (AI)
Artificial intelligence, AI, Neural Networks and Deep Learning
Resources
Resources
The Unreasonable Effectiveness of Recurrent Neural Networks
Musings of a Computer Scientist.
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Neural Networks Demystified - lumiverse
Neural Networks Demystified - lumiverse
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What is a convolutional neural network? | Artificial Intelligence
Convolutional neural networks (CNN) are a type of neural network which have been widely used for image recognition tasks.
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What a Deep Neural Network thinks about your #selfie
Musings of a Computer Scientist. GitHub
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Deep learning sharpens views of cells and genes | Nature
Neural networks are making biological images easier to process.
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Amazon is flooding the zone with new cloud A.I. tools that translate, transcribe, and track people
New cloud tools for translation, transcription and language understanding could help AWS move forward
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A 'Brief' History of Neural Nets and Deep Learning, Part 4 – Andrey Kurenkov
About the mid-2000s neural net comeback, and how deep learning ascended to the tsunami it is today “When you want a revolution, start with a con...
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Why Self-Taught Artificial Intelligence Has Trouble With the Real World | Quanta Magazine
The latest artificial intelligence systems start from zero knowledge of a game and grow to world-beating in a matter of hours. But researchers are ...
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The Downsides to Deep Learning | Wired
Greedy, Brittle, Opaque, and Shallow: The Downsides to Deep Learning WIRED’s new columnist Jason Pontin on the limits of modern artificial intel...
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MIT AGI: Future of Intelligence (Ray Kurzweil)
This is a talk by Ray Kurzweil for course 6.S099: Artificial General Intelligence. For this entire recording, Ray did not use slides, so the video ...
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GitHub - Deep Learning based project for colorizing and restoring old images
A Deep Learning based project for colorizing and restoring old images - jantic/DeOldify
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A neural network can learn to organize the world it sees into concepts—just like we do - MIT Technology Review
Generative adversarial networks are not just good for causing mischief. They can also show us how AI algorithms “think.”
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China's AI scientists teach a neural net to train itself | ZDNet
Researchers at China's Sun Yat-Sen University, with help from Chinese startup SenseTime, improved upon their own attempt to get a computer to disce...
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Foundations Built for a General Theory of Neural Networks | Quanta Magazine
Neural networks can be as unpredictable as they are powerful. Now mathematicians are beginning to reveal how a neural network’s form will influence...
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2010 – 2019: The rise of deep learning
No other technology was more important over the past decade than artificial intelligence. Stanford’s Andrew Ng called it the new electricity, and b...
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There’s a big problem with AI: even its creators can’t explain how it works - MIT
No one really knows how the most advanced algorithms do what they do. That could be a problem.
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A radical new neural network design could overcome big challenges in AI - MIT Technology Review
Researchers borrowed equations from calculus to redesign the core machinery of deep learning so it can model continuous processes like changes in h...
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