Eight technologies that could change healthcare beyond recognition

Smartphones, genome sequencing and wearable technology will bring benefits but also challenges to health and social care. Machine learning is a type of artificial intelligence that enables computers to learn without being explicitly programmed, meaning they can teach themselves to change when exposed to new data. New insights into big datasets Several businesses hope to […]

Thirteen Companies That Use Deep Learning To Produce Actionable Results

Our means for gathering data have largely outstripped our tools for analyzing that data. The result is a mountain of unstructured and largely inaccessible information gathered from social media, app permissions, website cookies and hardware and software service agreements. There’s gold in that mountain, but you need the right tools to get at it. For […]

ResNet in ResNet: Generalizing Residual Architectures

Article Abstract Residual networks (ResNets) have recently achieved state-of-the-art on challenging computer vision tasks. We introduce Resnet in Resnet (RiR): a deep dualstream architecture that generalizes ResNets and standard CNNs and is easily implemented with no computational overhead. RiR consistently improves performance over ResNets, outperforms architectures with similar amounts of augmentation on CIFAR-10, and establishes […]

The Promise of Artificial Intelligence Unfolds in Small Steps

When IBM’s Watson computer triumphed over human champions in the quiz show “Jeopardy!” it was a stunning achievement that suggested limitless horizons for artificial intelligence. Read the full article at The New York Times

In Radiology, Man Versus Machine

Will radiologists eventually be replaced by artificial intelligence? Call it artificial intelligence. Deep learning. Computer cognition. Whatever its name, it’s the same thing – machines recognizing clinical problems in digital images ahead of the radiologists charged with making the diagnosis. The artificial intelligence (AI) trend is new, but it’s gaining ground quickly, according to industry […]

Enlitic: Deep Learning Algorithms for Medical Imaging

Let’s say you could program a deep learning algorithm to read medical images as good as doctors can. Would you then replace all your radiologists with a deep learning program? Maybe you wouldn’t, but what if that deep learning algorithm was better than your radiologists? What if it just wasn’t marginally better, but 10X better? […]

18 Deep Learning Startups You Should Know

Over the last few weeks we’ve been working on applying Deep Learning algorithms for a new VentureRadar feature we’re adding in the coming weeks. This piqued my interest in finding out more about the startups leading the way in developing and applying Deep Learning, so I decided to pick out the eighteen highest ranked companies […]

Enlitic’s CEO Talks Data Driven Medicine using Deep Learning

In case you haven’t noticed, the age of artificial intelligence is upon us. What was once reserved for science fiction plots is now playing out in real life to save real lives, as a matter of fact. Chances are you’ve already heard of deep learning’s potential; remember IBM’s Watson and his impressive Jeopardy win? Read […]

Gradnets: Dynamic Interpolation between Neural Architectures

Article Abstract In machine learning, there is a fundamental trade-off between ease of optimization and expressive power. Neural Networks, in particular, have enormous expressive power and yet are notoriously challenging to train. The nature of that optimization challenge changes over the course of learning. Traditionally in deep learning, one makes a static trade-off between the […]