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Where AI Is Headed: 13 Artificial Intelligence Predictions for 2018 NVIDIA Blog

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Publications like The Wall Street Journal, Forbes and Fortune have all called 2017 "The Year of AI." AI outperformed professional gamers and poker players in new realms. Access to deep learning education expanded through various online programs. The speech recognition accuracy record was broken multiple times, most recently by Microsoft. And research universities and organizations like Oxford, Massachusetts General Hospital and GE's Avitas Systems invested in deep learning supercomputers. These are a few of many milestones in 2017.


Inventor Sorts 2 Million Lego Bricks with AI NVIDIA Blog

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Jacques Mattheij didn't expect to buy two tons of Lego bricks. For his Lego sorting machine, Mattheij first built a proof of concept made of (what else?) The Lego sorting machine now sorts 4,000 pieces an hour with an accuracy rate of 97 percent, but Mattheij thinks he can boost speed without compromising accuracy. The Lego sorting machine at work, seen in slow motion.


The Difference Between AI, Machine Learning, and Deep Learning? NVIDIA Blog

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For example, when Google DeepMind's AlphaGo program defeated South Korean Master Lee Se-dol in the board game Go earlier this year, the terms AI, machine learning, and deep learning were used in the media to describe how DeepMind won. Another algorithmic approach from the early machine-learning crowd, Artificial Neural Networks, came and mostly went over the decades. Today, image recognition by machines trained via deep learning in some scenarios is better than humans, and that ranges from cats to identifying indicators for cancer in blood and tumors in MRI scans. Deep Learning has enabled many practical applications of Machine Learning and by extension the overall field of AI.


The AI Revolution Is Eating Software: NVIDIA Is Powering It NVIDIA Blog

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It's great to see the two leading teams in AI computing race while we collaborate deeply across the board – tuning TensorFlow performance, and accelerating the Google cloud with NVIDIA CUDA GPUs. Dennard scaling, whereby reducing transistor size and voltage allowed designers to increase transistor density and speed while maintaining power density, is now limited by device physics. Such leaps in performance have drawn innovators from every industry, with the number of startups building GPU-driven AI services growing more than 4x over the past year to 1,300. Just as convolutional neural networks gave us the computer vision breakthrough needed to tackle self-driving cars, reinforcement learning and imitation learning may be the breakthroughs we need to tackle robotics.


Check Out These NVIDIA-Powered AI and VR Tools at SIGGRAPH 2017 NVIDIA Blog

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They're in our SIGGRAPH booth demonstrating their "Aging of 3D Worlds" platform. Its deep learning technology, along with NVIDIA CUDA, cuDNN and cuBLAS running on NVIDIA GPUs, generate dozens of aged textures in minutes at a resolution of up to 4K. "Being able to predict their final products and spot potential production challenges while still in design is critical to Bombardier," says Eric Kam, Product Marketing Manager at ESI Group. IC.IDO also incorporates NVIDIA VRWorks technologies, such as VR SLI, and Single Pass Stereo, to improve the performance, efficiency and image quality of its VR rendering.


Artificial Emotional Intelligence For Web Browsing NVIDIA Blog

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The first public pilot UK-based Emotions.Tech's artificial emotional intelligence, launched in May, allows users to search according to how they want the results to make them feel. "We need that acceleration to keep up with the complexities of human emotion," Tero says. To do that, Emotions.Tech turned to GPU-powered deep learning to rank, list and search web pages according to their emotional content. They then use this data to train artificial neural networks.


The AI Revolution Is Eating Software: NVIDIA Is Powering It NVIDIA Blog

#artificialintelligence

It's great to see the two leading teams in AI computing race while we collaborate deeply across the board – tuning TensorFlow performance, and accelerating the Google cloud with NVIDIA CUDA GPUs. Dennard scaling, whereby reducing transistor size and voltage allowed designers to increase transistor density and speed while maintaining power density, is now limited by device physics. Such leaps in performance have drawn innovators from every industry, with the number of startups building GPU-driven AI services growing more than 4x over the past year to 1,300. Just as convolutional neural networks gave us the computer vision breakthrough needed to tackle self-driving cars, reinforcement learning and imitation learning may be the breakthroughs we need to tackle robotics.


Can AI Diagnose Concussions from Your Voice? NVIDIA Blog

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A Utah-based startup is easing that process using AI and the patient's voice to detect telltale shifts in vocal patterns -- shifts human ears can't pick up -- to help doctors make the right call. The company, Canary Speech, is building voice tests that use GPU-accelerated deep learning to pick up the subtle voice tremors, slower speech and gaps between words that may reveal brain injuries, or warn of diseases such as Parkinson's or Alzheimer's. Later this year, the company plans to roll out a deep learning tool that coaches and trainers can use to diagnose concussions on the sidelines. No test can definitively diagnose Alzheimer's, but O'Connell said AI could analyze how patients talk to identify warning signs of the disease.


AI Shows Rainforest More Biodiverse Than Believed NVIDIA Blog

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If a tree falls in Peru's rainforest, Greg Asner can tell you what kind it was. Asner, an ecologist at the Carnegie Institution for Science and Stanford University, uses artificial intelligence and a powerful spectral imaging method to map the rainforest in unprecedented detail. By identifying each tree species by its chemical composition, he has shown the rainforest is more diverse than anyone thought. Asner's map takes the guesswork out of protecting one of the most biodiverse places on Earth and pinpointing new areas for conservation. "It's really advancing our ability to save forests and curb climate change," he said.