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Deep learning customer stories

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114 examples of NVIDIA's Customer Successes using AI.

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Deep learning customer stories

  1. 1. Rochelle Silveira, Voice of the Customer, September 2018 AI AND DEEP LEARNING CUSTOMER STORIES
  2. 2. 2 Doctors typically use their eyes to examine CT scan images, looking for small nodules in an attempt to deduce whether they’re benign or malignant. When the nodules are small, they’re harder to spot. And the result is that lung cancer is often detected too late, leading to a dismal 17% survival rate. Trained on DGX Station, 12 Sigma Technologies could reduce the time-consuming workload for both diagnostic and reporting, as well as change the existing lung disease diagnostic practice from being dependent on the subjective experience of radiologists to being based on objective clinical data. AI TO SPOT LUNG CANCER EARLY
  3. 3. 3 In the healthcare industry, there exists mountains of underutilized data. 16 Bit is using AI to unlock the value hidden in this data to augment diagnostics and improve the quality and accessibility of healthcare. 16 Bit is using GPU-accelerated deep learning and big data to assist radiologists in detecting breast cancer, analyze CT scans of the brain to exclude acute diseases, and accurately measure pediatric bone age. Their Bone Age analyzer has an accuracy rate of +/- 4 months and returns results in milliseconds―earning 16 Bit 1st place in the 2017 RSNA Machine Learning Challenge. 16 BIT.AI RSNA BONE AGE CHALLENGE WINNER Try the 16 Bit algorithm at 16bit.ai/bone-age
  4. 4. 4 MRIs can take 20 minutes to 2 hours. Subsampled data speeds scanning time but contributes to inaccurate image reconstruction and diagnostics. Researchers from the MGH/Martinos Center for Biomedical Imaging and Harvard University are working to speed MRI image reconstruction. Powered by the NVIDIA DGX-1 AI supercomputer, they’ve created AUTOMAP (Automated Transform by Manifold Approximation). AUTOMAP uses deep learning to reconstruct images directly from sensor data using a cascade of densely connected and sparse convolutional neural network layers—it filters out noise and defects to reconstruct images 100x faster and with 5x higher accuracy to deliver more accurate diagnostic outcomes. AI IMPROVES DIAGNOSTIC SPEED AND ACCURACY
  5. 5. 5 Retinopathy of prematurity (ROP) affects preterm babies born before 31 weeks, weighing <2¾ pounds. It’s treatable if caught early but diagnosing the severity of ROP is subjective—doctors compare the infant’s retina with photos selected by experts in the 1980s. Using a dataset of 6,000 images matched with expert ROP diagnoses and a DGX-1 with cuDNN-accelerated DL frameworks, researchers at Athinoula A. Martinos Center for Biomedical Imaging trained a deep neural network to differentiate ROP severity. Still work in progress, this method could be deployed in countries where access to specialists is lacking, and help make a difference in reversing preventable blindness worldwide. AUTOMATING THE DIAGNOSIS OF INFANT BLINDNESS
  6. 6. 6 AI-ACCELERATED CYBER DEFENSE Our daily life, economic vitality, and national security depend on a stable, safe and resilient cyberspace. But attacks on IT systems are becoming more complex and relentless, resulting in loss of information and money and disruptions to essential services. Accenture’s dedicated cyber security lab uses NVIDIA GPUs, CUDA libraries, and machine learning to accelerate the analysis and visualization of 200M-300M alerts daily so analysts can take timely action.
  7. 7. 7 SETTING THE GOLD STANDARD FOR NOTE TAKING After downloading Otter from your Appstore, you can go to your next meeting and focus 100% on the conversation while your new assistant captures comments with clear labels, and produces voice and text content you can search and extract meaningfulinsights from. This incredible work on smart speech recognition and processing at over 90% accuracy involves terabytes of data and complex speech AI models, made possible today by the computationalstrength of NVIDIA Tesla GPUs and formidable infrastructure on the Google Cloud.
  8. 8. 8 BREAKING DOWN BUSINESS BARRIERS The Alibaba Group services 8.3B translation requests daily, enabling international business trade. Alibaba uses neural machine translation (NMT) which improves translation quality significantly but drives up latency and computation cost. To remedy this and accelerate online NMT-based services, Alibaba deployed NVIDIA Tesla GPUs and achieved a 3x increase in number of requests serviced while cutting latency by a factor of three.
  9. 9. 9 APPLYING STYLE TRANSFER TO 3D TEXTURES Using the popular texture synthesis and style transfer technique, Artomatix is applying a high-level of detail of one texture to a lower- res texture which provides game artists with a quick automated process to generate usable textures with only minimal user input.
  10. 10. 10 New drug development can cost billions and take up to 14 years—and still only ~8% of drugs make it to market. Atomwise helps its customers make smarter decisions about which potential medicines to develop. With NVIDIA GPUs to power training and inference, Atomwise’s AtomNet deep learning software understands the interactions of millions of molecules and analyzes simulations to determine whether a potential treatment works against a target. AtomNet explored 8.2 million molecules and identified several candidates that could prove to be cures for Multiple Sclerosis. Effective in animal trials, those candidates are now undergoing further exploration. SPEEDING THE PATH TO MARKET The Janus kinas 3 protein, which has been implicated in cancer and immune function. Image courtesy of Atomwise.
  11. 11. 11 SMARTER INSPECTION SERVICES In business, ensuring equipment uptime and meeting safety and regulatory compliance is non-negotiable. Using deep neural networks developed on NVIDIA DGX-1 in the data center that can easily extend to NVIDIA DGX Station in the field, Avitas Systems delivers inspection services using robotic-based autonomous inspection and advanced data analytics. In addition to safeguarding workers, Avitas Systems AI solutions can reduce inspection costs by 25% and reduce maintenance downtime by 15%. The robots can handle the heat and use infrared cameras and chemical and other sensing technologies to inspect assets under dangerous conditions and keep production running. Image credit: Avitas Systems
  12. 12. 12 PUMPING AI INTO THE OIL & GAS INDUSTRY NVIDIA and Baker Hughes (BHGE) are using AI and GPU-accelerated computing to help companies distill oceans of data and reduce the cost of finding, extracting, processing and delivering oil. BHGE’s applied AI services and NVIDIA’s end-to-end AI supercomputing solutions ―from the NVIDIA DGX-1 in data centers, to the NVIDIA DGX Station deskside or at remote locations, to NVIDIA Jetson at the edge— can unlock insights from data that was previously as hidden as the oil underground.
  13. 13. 13 ACCELERATING DISCOVERIES WITH AI New drugs typically take 12-14 years and $2.6 billion to bring to market. BenevolentAI is using GPU deep learning for NLP to bring new therapies to market quickly and more affordably. They’ve automated the process of identifying patterns within large amounts of research literature, enabling scientists to form hypotheses and draw conclusions quicker than any human researcher could. And using the NVIDIA DGX-1 AI supercomputer with CUDA, they identified two potential drug targets for Alzheimer’s in less than one month.
  14. 14. 14 If a picture is worth a thousand words, imagine being able to skip the text and show your search engine what you’re looking for. This is the powerful experience Bing offers its users with automated object detection for accurate search results delivered quickly. No more manually cropping the object you’re interested in. Bing users simply click on the hotspot that’s over the object of interest and the bounding box automatically positions over the object and triggers the search. And the search is fast. With NVIDIA GPUs on Azure cloud, Bing speeds up object detection 60X to 40ms—well under the threshold for an excellent user experience. SMARTER, FASTER VISUAL SEARCH Try Bing: https://www.bing.com/images/
  15. 15. 15 FASTER PROCESSING, HAPPIER CUSTOMERS The insurance industry still relies largely on evidence-based, non-standardized documents such as paper, scans, and photos for contract management. Processing this type of documentation is often manual, tedious, and time consuming for the insurer and the insured. ‘Cardif Forward’ is BNP Paribas Cardif’s innovative digitization plan and AI is a key element. The company—known for leading-edge customer service—is developing GPU-accelerated deep learning image recognition algorithms to automatically recognize and process documents digitized by its clients. The AI solution will significantly reduce the complexity of contract management and speed the process.
  16. 16. 16 To speed advances in the fight against cancer, the Cancer Moonshot initiative unites the Department of Energy, the National Cancer Institute and other agencies with researchers at Oak Ridge, Lawrence Livermore, Argonne, and Los Alamos National Laboratories. NVIDIA is collaborating with the labs to help accelerate their AI framework called CANDLE as a common discovery platform, with the goal of achieving 10X annual increases in productivity for cancer researchers. AI PLATFORM TO ACCELERATE CANCER RESEARCH
  17. 17. 17 The number of mobile banking users is estimated to reach 2 billion by the year 2021. So it’s not surprising to see the rising popularity of Chatbots in the finance industry. Through convenience and ease-of-use, Chatbots optimize digital services at scale. Capital One is piloting an SMS text-based intelligent assistant named Eno. Eno uses GPU-powered deep learning to respond to natural language text messages from customers inquiring about their accounts. Customers text Eno to track their balance, recent charges, or to pay their bill. Eno takes mobile banking to the next level, which is just a text message away. AI CHATBOT THAT SPEAKS EMOJI
  18. 18. 18 “AUTO”MATIC RECOGNITION AND CATEGORIZATION Online retailer Carsales handles ~20,000 uploaded images each day. Having sellers input details on each car and having Carsales staff manually categorize photos was time-consuming and inefficient. Carsales implemented Cyclops, a GPU-powered AI tool that automatically recognizes cars in photos, categorizes angles and notifies sellers of missing angles and poor quality photos. With 97% accuracy, Cyclops exceeds human performance and saves Carsales 55 hours/day of valuable staff time.
  19. 19. 19 AI ADVANCES THE FIGHT AGAINST BREAST CANCER Breast cancer is the second leading cause of cancer death for women worldwide. Genomic tests help doctors determine a cancer’s aggressiveness so they can prescribe appropriate treatment. But testing is expensive, tissue-destructive, and takes 10-14 days. Case Western Reserve is using GPU-based deep learning with CUDA to develop an automated assessment of cancer risk at 1/20th the cost of current genomic tests.
  20. 20. 20 AI POWERED INSIGHTS FOR EFFECTIVE MEDICAL DECISION MAKING Electronic health records (EHR) offer huge volumes of data that doctors can combine with real-time analytics to improve their patient outcomes. Using NVIDA GPUs with CUDA, CloudMedx is creating a clinical AI platform that leverages both structured and unstructured data fields from EHRs, reads doctors’ patient-specific clinical notes and using evidence based guidelines, helps identify risks and correlates treatments. It’s a combination of machine learning and natural language processing that gives doctors the power to make time-critical decisions that has the potential to save lives.
  21. 21. 21 SEEING BEYOND IMAGE RECOGNITION CloudSight democratizes the power of AI and gives its users the ability to gain more insights from their images. Its API is a powerful visual cognition engine of >600m images. Powered by the NVIDIA DGX-1 to speed training and inference. CloudSight accelerates deep neural net training runs by 61x—enabling its engineers to experiment freely and improve services for its customers.
  22. 22. 22 Weather forecasting involves processing vast amounts of data to derive predictions that can save lives and protect property. Colorful Clouds is using GPU deep learning with CUDA to speed the processing of data by 30-50x. It’s location-based reporting tool can forecast and communicate weather and air-quality conditions with high- accuracy in real-time. AI-POWERED WEATHER FORECASTING
  23. 23. 23 REINVENTING TV WITH AI Comcast and AI are improving the TV viewing experience. With NVIDIA GPUs and the NVIDIA DGX-1 to power deep learning, Comcast parses millions of voice commands received daily through its Xfinity X1 platform. Each command is automatically processed so customers find the content they love in an instant. Add a recommendation engine that suggests programming based on individual preferences and Comcast delivers a truly personalized TV experience.
  24. 24. 24 AI INCREASES RETURN ON ADVERTISING SPEND In the Criteo commerce marketing ecosystem Big Data is put into action throughout the purchase journey. Criteo processes 600TB of shopper data per day and serves >900B ads that drive $550B in commerce sales per year. Criteo is piloting GPU-powered AI for data analytics to better understand buying habits and predictive search to enable its customers to propose the best product(s) at the best time.
  25. 25. 25 REDEFINING CYBERSECURITY We depend on a safe cyberspace for just about every aspect of our lives. Cyber attacks can be devastating, and in today’s world mutations have become the rule not the exception. Cylance leverages GPU-powered deep learning with CUDA to predict and prevent malicious code execution by identifying indicators of an attack. CylancePROTECT immediately prevented the execution of the May 2017 WannaCry attack on 100% of its customers’ endpoints.
  26. 26. 26 Even more than its meticulous engineering, Mercedes-Benz is defined by its continuous innovation. Since inventing the car in 1886, the company has never stopped reinventing it. And now Mercedes-Benz is using AI to enhance the user experience behind the wheel by having its cars predict where drivers want to go. Trained on driver behavior data from 24,000 road trips, the NVIDIA GPU-accelerated destination prediction AI learns the driver’s habits over time in order to make better suggestions. AI-POWERED DESTINATION PREDICTION AND ROUTE PLANNING
  27. 27. 27 ENABLING AI SOLUTIONS EDGE TO CLOUD DarwinAI optimizes deep learning neural networks ― making them faster, scalable, portable and understandable. It’s Generative Synthesis AI-driven technology observes the inner workings of a neural network, then generates an optimized version that is orders of magnitude smaller and faster. And, when combined with TensorRT running on NVIDIA GPUs, DarwinAI solutions run up to 7000 times faster than CPUs. RapidID enables real-time detection and identification of objects in scenes on embedded and mobile devices.
  28. 28. 28 DELIVERING GREATER BUSINESS INSIGHTS Insights from call center audio can help companies increase sales, enhance employee training and improve customer satisfaction, but most companies are only able to manually harness data from ~2% of their recorded calls. Powered by NVIDIA DGX Systems for deep learning training and inference, Deepgram recognizes speech more completely and precisely, enabling companies to utilize 100% of their recorded calls.
  29. 29. 29 AI TOOL BOOSTS CUSTOMER SERVICE KLM’s 350+ social media service agents handle 15K requests/week. To support the volume of incoming messages, KLM uses GPU- accelerated deep learning to predict the best response. Service agents review and either approve or personalize each response. The resulting time savings allows agents to focus on customers with more pressing needs and handle more questions while maintaining high levels of customer satisfaction.
  30. 30. 30 The field of AI holds tremendous promise to improve lives. Facebook A.I. Researchers (FAIR) are advancing the field of machine intelligence by creating new technologies that give people better ways to communicate. To manage the huge variety of projects, datasets, and ever-changing workloads, FAIR needed to update its research cluster. 128 NVIDIA DGXs with CUDA are the main component of the new cluster and deliver the extreme performance and flexibility FAIR needs to advance AI. 128 NODE DGX-1 CLUSTER SCALES DEEP LEARNING INFRASTRUCTURE
  31. 31. 31 HUNTING “GHOST PARTICLES” WITH DEEP LEARNING Tiny particles called neutrinos are the most abundant form of matter in the universe and understanding their properties is the focus of a world-wide campaign of experiments. Observing these ‘ghost particles’ in action requires instruments of incredible size and scale. Fermilab’s NOvA experiment applies two enormous detectors with a total weight of 30 Million pounds spaced 500 miles apart. It is effectively one of the world’s largest cameras, snapping 2 million images per second and analyzing them for neutrino activity. NOvA’s scientists developed deep neural networks trained on NVIDIA GPUs with CUDA to improve the machine’s detection rate by 33% - increasing the discovery potential of NOvA and other large scale experiments probing fundamental questions of the universe.
  32. 32. 32 SPEEDING UP NASCAR WITH AI In NASCAR, the difference between victory and defeat can be measured in milliseconds. That’s why Ford Motorsports is optimizing aerodynamics with AI powered by the NVIDIA DGX-1 running TensorRT. Hours before a race, Ford trains its model to recognize the field. During the race, the AI analyzes video feeds and assesses performance in real-time. Ford teams receive immediate feedback and adjust their cars as needed to stay ahead of the competition.
  33. 33. 33 Automakers use Computational Fluid Dynamics (CFD) to help speed development, but Ford takes it up a notch. The auto giant applies GPU-accelerated AI to CFD to prepare its NASCAR racing teams for optimal performance. Augmenting traditional CFD, Ford developed a virtual wind tunnel Neural Network on the DGX-1 to simulate configurations of its racing teams’ cars and predict how each car will perform under different scenarios. Simulations are 99% accurate and completed in a few hours vs. 3-4 days, enabling the Ford teams to adjust their vehicles before every race. FORD & AI TAKE NASCAR TO THE FINISH LINE
  34. 34. 34 Health and life insurance administrators spend countless hours manually reviewing statements, physician notes, and other forms to correct any discrepancies. Digitizing this paperwork is complex―it involves extracting heterogeneous data from documents and using multiple techniques to interpret it accurately. With NVIDIA Tesla V100 GPUs on AWS for training and inference, the Friendly AI platform transforms medical and insurance paperwork into a structured, analyzable format and then uses natural language processing to extract information to create digital claims. Friendly clients process claims 40% faster (in minutes vs. days) and with 20% fewer errors―equaling annual cost savings of up to hundreds of thousands of dollars. NEXT GENERATION CLAIMS PROCESSING
  35. 35. 35 Customizing dental restorations to get the perfect color, shape, and fit means happier patients and fewer returns. Glidewell combines automation with AI to speed the design process and meet a demanding manufacturing workload of 10,000+ units per day. Trained on >100k patient cases and 3D data, Glidewell’s AI design automation tool uses a convolutional neural network to accurately determine if designs will produce products to each patient’s satisfaction. Additionally, patients no longer wait for weeks to receive their custom restorations as production time has been reduced to 2-3 days. AI-BASED PRECISION DENTAL CARE
  36. 36. 36 Heart disease, the world’s biggest killer, is responsible for ~9 million deaths annually. Until recently, the best test to diagnose heart disease was an angiogram―an invasive and costly procedure. HeartFlow applies GPU-accelerated deep learning to the analysis of coronary blood vessels to deliver non- invasive diagnostics. Trained on CT scans and computational fluid dynamics, HeartFlow’s AI creates a personalized 3D model of a patient’s coronary arteries and analyzes the impact of blockages. With HeartFlow, clinicians can provide personalized treatment for each patient and improve quality of life. It also means 61% of patients can avoid an angiogram, reducing healthcare system costs by 26%. HEART SMART: AI TO DETECT HEART DISEASE Image is not representative of actual product. Courtesy of HeartFlow, Inc.
  37. 37. 37 THE AI BRAIN OF SMART CITIES A key technology component of any Smart City is video surveillance. With millions of cameras in large cities, analyzing the massive amount of video content generated is a huge undertaking. Hikvision is using deep learning and the NVIDIA DGX-1 to speed intelligent video content analysis for Smart Cities to safeguard citizens and property, manage traffic, and increase criminal investigation efficiencies.
  38. 38. 38 AI PREDICTS AND PREVENTS DISEASE GPU deep learning is giving doctors a life- saving edge by identifying high-risk patients before diseases are diagnosed. Icahn School of Medicine at Mount Sinai built an AI-powered tool, “Deep Patient,” based on NVIDIA GPUs and the CUDA programming model. Deep Patient can analyze a patient’s medical history to predict nearly 80 diseases up to 1 year prior to onset.
  39. 39. 39 AI CHANGES THE GAME Sports team managers have limited data. ICEBERG’s automated AI system uses cameras to capture millions of data points describing hockey players’ positions, speed, plays and tactics at every point in the game. With this new level of data-driven understanding, managers can make changes to their game plan during periods to gain a competitive advantage.
  40. 40. 40 SCALE SERVICES, REDUCE TCO Speech translation breaks language barriers for travelers, businesses, students, and more. When iFLYTEK wanted to scale its Mandarin speech service to serve multiple accents and dialects, the company expanded its use of GPUs by moving its inference operations to Tesla GPUs and TensorRT. iFLYTEK now handles 10x the number of concurrent requests, has improved accuracy by 20%, and yielded a 20% reduction in operational TCO.
  41. 41. 41 NEXT GEN AI-POWERED IMAGE RECOGNITION Fast and easy to implement functionalities are vital in helping organizations enhance services. Imagga helps developers and enterprises optimize projects and quickly build scalable, image-intensive cloud apps. With an API and solutions built on the NVIDIA DGX Station to speed training and inference, Imagga speeds service delivery up to 88%, while maintaining high levels of accuracy.
  42. 42. 42 IMAGINE NO LIMITATIONS TO DRUG DISCOVERY It takes 12 years and $2.6B to bring a new drug to market. Insilico Medicine takes an innovative approach to speed drug discovery and uses GPU-accelerated Generative Adversarial Networks (GANs) to "invent" new molecular structures on demand. With GANs, in only a few months’ time, Insilico did what would have taken years with conventional research methods – identified 69 new molecules. To date, Insilico has generated 5,000+ new molecules, integrated GANs into a comprehensive drug discovery framework, and established working collaborations with large pharmaceutical companies. This unique approach could dramatically reduce the time and cost of developing novel substances with medicinal properties.
  43. 43. 43 AI CAD TOOL SPEEDS DESIGN Design for Manufacturability (DFM) is the process of designing products so they're easy to manufacture. Traditional rule-based DFM relies on the experience and training of individual designers which can vary widely. Scientists at ISU are using CUDA on GPUs to develop an AI DFM decision-support tool to help designers optimize their models for manufacturability. Trained on a database of CAD models, the tool predicts non-manufacturability, identifies features that are the cause, and provides recommendations for improvement. Early results show the ISU tool can: accelerate design and manufacturing cycles by replacing manual iterative reviews; establish consistency by eliminating inter-expert variability; and speed a product’s time-to-market by >10x.
  44. 44. 44 DELIVERING FAMILY FRIENDLY CONTENT Growth in online video traffic means companies are monitoring more content than ever to filter inappropriate material. JD.com uses NVIDIA’s DeepStream SDK and TensorRT on Tesla P40 GPUs to identify and filter 1,000 channels of live-streamed full-HD videos. The company has increased throughput 20x in inference-based video content filtering and is simultaneously Inferencing 20 videos per Tesla-equipped server.
  45. 45. 45 SIGNED, SEALED DELIVERED BY AI JD X brings AI to logistics & delivery with intelligent machines powered by the NVIDIA Jetson supercomputer. The JDrone reduces logistics fees by 70%, while delivering fresh food & medicine to remote locations. The JDrover robot easily navigates through pedestrians & traffic to deliver packages to select locations. JD X opened the world’s first autonomous sorting center with Pick & Place Robots that sort up to 16,000 parcels/hour with 99.999% accuracy.
  46. 46. 46 SHOPPING SMARTER According to Forrester, the $390B E-Commerce market will double by 2024. Jet.com (acquired by Walmart) uses GPU-accelerated AI to drive its smart cart solution that fulfills orders at the lowest prices though the smart bundling of supplier offers. The platform finds the ideal merchant and warehouse combination to lower the total order cost. The bigger the shopping cart, the greater the savings.
  47. 47. 47 REAL-TIME ANOMALY DETECTION WITH MULTI- SENSOR ANALYTICS Frauds and intrusions in modern information systems can cause significant harm. KickView’s applied AI automates processing and anomaly detection using signal data, image data, and sensors such as video, radio frequency, and IoT devices. With the NVIDIA DGX Station, KickView reduced training time by 3x, while maintaining >90% detection and classifications accuracy with multi-sensor systems, all in real-time.
  48. 48. 48 The high cost of drug discovery is driving researchers and pharmaceutical companies to turn to AI as a faster, more efficient way to develop new drugs. Professor Okuno, Kyoto University and RIKEN, have formed the Life INtelligence Consortium (LINC) to build an AI drug discovery ecosystem in Japan. LINC uses the NVIDIA DGX-1 AI supercomputer―the DGX-1 delivers the extreme performance LINC needs to solve complex problems and speed drug discovery. DGX-1 POWERS FASTER, MORE EFFICIENT DRUG DISCOVERY
  49. 49. 49 IDENTIFYING THREATS Lawrence Livermore Labs (LLNL), a national AI project leader, is using AI to make the world safer. Understanding changing patterns of vehicles or other objects over time may help identify security concerns. Using NVIDIA GPUs, CUDA, and deep learning to analyze overhead imagery, LLNL has developed a “one-look” method that counts objects directly, bypassing the detection phase, while achieving over 90% accuracy.
  50. 50. 50 AN AI POWERED SUPPLY CHAIN IN THE CLOUD Machine Shop Services is a $43B industry according to IBISWorld, and MakeTime — an online platform where manufacturers in need of machining are matched with pre-qualified shops — is poised to disrupt the industry with a new data and cloud-driven approach to machining. MakeTime’s GPU-accelerated algorithms ensure orders get placed with the best machine shop, every time. With a nation-wide supplier network of 700+ computer numerical control (CNC) machine shops, MakeTime brokers new win-win relationships for manufacturers and their suppliers — shop owners fill gaps in machine schedules and manufacturers speed time to execution.
  51. 51. 51 AI DETECTS GROWTH PROBLEMS IN CHILDREN Detecting growth-related problems in children requires calculating their bone age. But it’s an antiquated process that requires radiologists to match X-rays with images in a 1950s textbook. Massachusetts General Hospital, which conducts the largest hospital-based research program in the United States, developed an automated bone-age analyzer built on the NVIDIA DGX-1 with CUDA. The system is 99% accurate and delivers test results in seconds versus days.
  52. 52. 52 NOT ENOUGH DATA? NOT A PROBLEM Deep Learning holds enormous promise to advance medical discoveries, but adequate training data can be a challenge. Scientists at the MGH & BWH Center for Clinical Data Science are using the NVIDIA DGX Station to train GANs that create and validate synthetic brain MRI images. Combining the manufactured images with real MRI images enables the team to train its neural network with 75% less data.
  53. 53. 53 AI HELPS PERSONALIZE IMMUNOTHERAPY Immunotherapy has a success rate of only 40% and a risk that it may attack healthy cells. Max Kelsen is using sophisticated AI approaches with NVIDIA V100 GPUs to integrate genomic, transcriptomic and patient information to identify a classifier and develop a test that can predict treatment response.
  54. 54. 54 AI SEES THE UNSEEN – COULD REDUCE THE NEED FOR BRAIN BIOPSIES Brain tumors can be spotted by today’s MRIs, but determining the right way to treat them requires information about the tumor’s genomic makeup — data that can only come from highly invasive brain biopsies. Researchers at the Mayo Clinic may have found another way. Using AI, Mayo discovered that the same genomic data can be found in the MRIs themselves, hidden from traditional analysis methods. Mayo used GPU-accelerated deep learning with CUDA to train its systems where to look and how to extract the information. The new system has greater than 90% accuracy and has the potential to greatly reduce the need for brain biopsies.
  55. 55. 55 Arctic sea ice is melting as the Earth warms, but instead of making seafaring safer, melting ice can unexpectedly block channels, damage vessels and cargo, or completely trap ships. To make seafaring safer, scientists at Memorial University Newfoundland are using GPU-powered AI with CUDA to predict when and where sea ice is likely to melt and refreeze. Unlike current forecast methods, which look ahead 7-10 days, the team is working to predict conditions up to 6 weeks ahead for ice, and 6 months ahead for icebergs. In addition to safeguarding lives and livelihoods, the AI forecasting tool will help shippers make the most of the short season. ON THIN ICE: HOW AI PREDICTS MELTING OF SEA ICE
  56. 56. 56 AI TOOL LETS YOU APPLY BEFORE YOU BUY Testing different types of makeup can take hours and be a frustrating experience. ModiFace is using GPUs with CUDA and facial modeling technology to help consumers explore and select the ideal products. ModiFace developed the ‘Sephora Virtual Artist’, an online tool that allows consumers to virtually experiment with new makeup without having to leave their computer screen. With technology on skin analysis and facial visualization, ModiFace and its AI features have introduced a more efficient way to style oneself.
  57. 57. 57 SUPER DRUGS TO COMBAT SUPER BUGS New Robot Arm from ARC Image: One of Dr Matt Belousoff and Professor Trevor Lithgow ribosome structures illustrating complicated details that can be determined using MASSIVE and the Titan Krios at the Ramaciotti Centre for Cryo Electron Microscopy. In the race to design more effective drugs and new treatments for diseases, Australian scientists are using HPC and advanced imaging to visualize changes in ribosomes that occur in response to antibiotics. With MASSIVE’s M3 supercomputer powered by >160 NVIDIA GPUs and 2 DGX-1V’s to accelerate data processing, the team strives to identify new drugs that are lethal to bacteria despite structural changes in ribosomes.
  58. 58. 58 AN AI MONITOR OF EARTH’S VITALS The Earth’s climate has changed throughout history, but in recent years there have been record increases in temperature, glacial retreat and rising sea levels. NASA Ames is using satellite imagery to measure the effects of carbon and greenhouse gas emissions on the planet. To do so, they developed DeepSat―a deep learning framework for satellite image classification trained on a GPU-powered supercomputer. The enhanced satellite imagery will help scientists plan to protect ecosystems and farmers improve crop production. NASA: Late summer 2016, forest fires in Africa produce plumes of CO2 Left: CO2 - 10/14/2016 / Right: CO2 - 12/24/2016 Source: https://climate.nasa.gov/climate_resources/142/
  59. 59. 59 DEFENDING THE PLANET The U.S. government’s Asteroid Grand Challenge seeks to identify asteroid threats to human populations. The team at NASA Frontier Development Labs picked up the challenge by employing GPU deep learning with CUDA to identify threats and their unique characteristics. The resulting “Deflector Selector” achieved a 98% success rate in determining which technology produced the most successful deflection.
  60. 60. 60 “SEEING” GRAVITY FOR THE FIRST TIME In September 2015, 100 years after Einstein predicted them, gravitational waves were observed for the first time. Astronomers at the Laser Interferometer Gravitational-wave Observatory have since used GPU-powered deep learning to process gravitational wave data 100x faster than previous methods, making real-time analysis possible and putting us one step closer to understanding the universe’s oldest secrets. Physics Letters B - Deep learning for real-time gravitational wave detection and parameter estimation: Results with advanced LIGO data Daniel George, E.A. Huerta
  61. 61. 61 A RADIOLOGY LIBRARY FOR THE WORLD AI holds enormous promise for advancing medical imaging, but well-annotated datasets are hard to come by. Researchers at the National Institutes of Health have created an auto-annotation system leveraging deep learning, NVIDIA GPUs and the CUDA programming model. The NIH research could lead to the creation of a global library of datasets for medical researchers.
  62. 62. 62 GPU Job Management System AI CAMERA HELPS USERS TAKE BEAUTIFUL PHOTOS EVERY TIME PHOTO BACK-UP CLOUD RETRIEVES PHOTOS IN AN INSTANT NTT DOCOMO ACCELERATES DEVELOPMENT OF AI WITH NVIDIA DGX-1, TESLA GPUS, JETSON TX-1 AI CONCIERGE FINDS FASHION ITEMS TO SUIT YOU TAXI DEMAND AI FORECASTING TOOLTELLS DRIVERS WHERE THEY’RE NEEDED MOST
  63. 63. 63 AI ALARM SYSTEM SAFEGUARDS HONEYBEES Habitat loss and pesticides are the primary threats to bee populations, but the Varroa mite can devastate entire colonies. To combat the Varroa, student Jade Greenberg turned to AI. Her solution —NVIDIA’s Jetson TX2, DGX Station, TensorRT, Microsoft’s Cognitive Toolkit, Kinetica— uses sensors and cameras to feed a convolutional neural network that assess hive health in real-time and converts the data into a visual early warning system for beekeepers. Image courtesy of Piscigate AI detects a mite in frame 24
  64. 64. 64 THE NEW SCIENCE OF SPORTS Predictive analytics, commonly used in business to identify risks and opportunities, is increasingly used by the sports industry to tap into massive amounts of data. Scientists at NYU are applying deep learning and the NVIDIA DGX-1 AI super- computer to analyze unprecedented amounts of Major League Baseball data —four years-worth of every player’s every move— to help improve the game.
  65. 65. 65 A 21ST CENTURY PLANNING TOOL BUILT ON AI With the Earth's population at 7 billion and growing, understanding population distribution is essential to meeting societal needs for infrastructure, resources and vital services. Using GPUs and deep learning, Oak Ridge National Laboratory quickly processes high-resolution satellite imagery to map human settlements. With the ability to process a major city in minutes, ORNL can provide emergency response teams critical information that used to take days to create.
  66. 66. 66 AI IMPROVES THE CUSTOMER EXPERIENCE AI is dramatically changing the online shopping experience with tangible improvements to retailers and consumers. In 2016 online British grocery giant Ocado improved customer service with their AI- enhanced contact center, and is applying machine learning and NVIDIA GPUs with CUDA to develop humanoid robotics to assist maintenance technicians, and advanced computer vision for image classification and recognition to replace barcode systems. Computer vision will expedite the picking process and better ensure orders are filled correctly so customers receive exactly what they ordered.
  67. 67. 67 The phrase “Time is Brain” means every minute counts after a stroke. A typical patient loses almost 2 million neurons per minute in which a stroke is untreated. Immediate treatment minimizes brain damage. To help Radiologists diagnose the most urgent cases and enhance critical care, the OSU Department of Radiology used GPU-accelerated deep learning to develop an Automated Critical Test-Findings Identification and Online Notification System (ACTIONS). With GPUs, ACTIONS was trained in minutes vs. days. It identifies in seconds the most urgent cases of stroke, hydrocephalus, hemorrhage, and large tumors with an accuracy rate of 81% (stroke) and 91% (hydrocephalus, hemorrhage, large tumors), speeding time to critical care. AI SPEEDS TIME TO CRITICAL CARE Examples of head CT examinations containing critical findings. A) A patient with a recent stroke involving the left cerebral hemisphere (green arrows). B) A patient with a large left frontal tumor compressing adjacent structures (orange arrows). http://pubs.rsna.org/doi/pdf/10.1148/radiol.2017162664
  68. 68. 68 PERSONALIZING PRODUCTS Olay is arming consumers with knowledge to make informed purchase decisions. Its Olay Skin Advisor—a GPU-accelerated AI tool that works on any mobile device—assesses a user-provided selfie and advises how to improve trouble areas using a daily regime of recommended Olay products. After four weeks 94% of Skin Advisor users continued to use the products it recommended.
  69. 69. 69 B O X B A G D E N I M J A C K ET A VIATOR SUNGLASSES L O O K: S T REE T L O O S E F I T W A S H E D B R O W N S W E A T P A N TS B L A C K W H I T E S T R I P E L E A T H E R M E T A L L I C AI TAGGING API IS ON TREND Fashion moves and changes quickly. To help its B2B customers stay ahead of the fashion curve, Omnious offers an AI tagging API that reduces manual work. Powered by a DGX Station, the automated fashion image tagging tool is 100x faster than manual tagging, reduces 90% of operation costs, and is more accurate than human labelling by fashion experts.
  70. 70. 70 TEACHING COMPUTERS TO SPEAK HUMAN Natural language processing, a research area of AI, will help bridge the worlds of humans and machines. OpenAI, a non-profit founded by Elon Musk to ensure AI is safe, is using the NVIDIA DGX-1 AI supercomputer with CUDA to advance its research, including developing an AI agent with natural language understanding. With DGX-1, OpenAI researchers can explore problems that they couldn't previously pursue and, ultimately, advance their mission to widely distribute the benefits of AI.
  71. 71. 71 AI HELPS DOCTORS DIAGNOSE BREAST CANCER Every day, pathologists are tasked with providing cancer diagnosis to guide patient treatment. However, sifting through millions of normal cells to identify a few malignant cells is extremely laborious using conventional methods. PathAI combines GPU deep learning with traditional pathology to improve accuracy, speed diagnosis, and reduce error rates by 85%.
  72. 72. 72 Understanding protein structural variability and disorder is paramount for advancements in protein applications and drug design. Researchers at Peptone recently unleashed the power of big data and AI to understand protein structural variability at the building block level through statistical analyses of protein NMR data. Peptone’s dSPP, is the world’s first interactive repository of structure features of proteins for the next generation machine learning problems with seamless integration for Keras and Tensorflow frameworks. Researchers harnessed the computational power of the DGX-1 with CUDA to unravel the sequence- dynamics relationships in 7200+ proteins of medical significance through Bayesian Deep Learning and Hybrid Statistical Thermodynamics. AI ACCELERATES PROTEIN RESEARCH
  73. 73. 73 DISCOVER MORE WITH DEEP LEARNING Online shopping can be convenient but searching through multiple websites can be arduous and time- consuming. Pinterest makes it easy for users to quickly discover things they love. Automatic object detection lets users search for products within a Pin’s image, and Shop the Look lets users buy items seen in fashion and home décor Pins. Scientists on Pinterest’s visual search team use GPU-accelerated deep learning with CUDA to teach their system to recognize image features using a dataset of billions of Pins and compute similarity scores to identify the best matches. One visual search study reports a 50% improvement in user engagement and traffic.
  74. 74. 74 AI IS SPEEDING THE PATH TO FUSION ENERGY Fusion is the future of energy on Earth. But it’s a highly sensitive process where even small environmental disruptions can stall reactions and damage multi-billion machines. Current models can predict the disruptions with 85% accuracy, but ITER will need something more precise. Researchers at Princeton University have developed the Fusion Recurrent Neural Network (FRNN) using deep learning and NVIDIA GPUs with CUDA to predict disruptions and make adjustments to minimize damage and downtime. Even a 1% improvement in the prediction accuracy can be transformative considering the immense scale and cost of fusion science. FRNN has achieved 90% accuracy and is on the path to achieving its goal of 95% accuracy for ITER’s tests. Visualization courtesy of Jamison Daniel, Oak Ridge Leadership Computing Facility
  75. 75. 75 AI-DRIVEN ASSET MANGEMENT AI has led to break-through innovations across all industries and the finance industry is no exception. qplum, an online asset management firm, uses quantitative trading techniques and invests using data and GPU-powered deep learning. qplum blends the mathematics of data-driven decision-making, the science of behavioral economics, and the art of effective communications. In the speed trade category, qplum has been an innovation leader having started with a $10,000 risk limit and, over the last 10 years, making more than $1.4B in profits.
  76. 76. 76 The Research Computing Centre (RCC) at UQ are using the Wiener supercomputer to expedite research in a diverse range of imaging-intensive sciences. Using deconvolution algorithms, machine learning and pattern recognition techniques, Wiener —with its NVIDIA Tesla V100 accelerators— provides near real-time outputs of deconvolved, tagged and appropriately characterized data, providing researchers with immediate feedback on data quality and allowing for faster interpretation of microscopy data. UQ's new Wiener supercomputer will add sharp detail to microscopic imagery FASTER INTEPRETATION OF MICROSCOPY DATA
  77. 77. 77 AI ROBOT WASTES NOT, WANTS NOT Humanity produces ~1.3B metric tons of waste a year. Most ends up in landfills. Much of it could be recycled, but the process of sorting and recycling waste material is often cost prohibitive for manufacturers. Sadako is turning trash into cash with its AI-powered robot. With NVIDIA GPUs powering machine learning, the Max-AI robot removes recyclable materials from the waste stream cost-effectively. Inset upper right corner: Max-AI combines computer vision and AI to identify recyclables
  78. 78. 78 IDC predicts that by 2021 AI will boost global business revenue by $1.1 trillion. Businesses are embracing AI to optimize processes, decrease costs, and remain competitive. SalesHero's AI assistant, Robin, performs tedious sales tasks that detract from productivity. Using GPUs for deep learning and inference, Robin learns from CRM systems, customer interactions, and SalesHero’s Account Graph database to automate sales processes such as updating sales records, prospect mining, and predicting close dates. With the time savings Robin delivers, sales teams can increase productivity up to 30%. AI SALES ASSISTANT INCREASES PRODUCTIVITY
  79. 79. 79 A NEW WAVE OF AI BUSINESS APPS Many companies sponsor televised events to promote their brands, yet ROI can take weeks, or even months, to measure. SAP Brand Impact, powered by NVIDIA deep learning, measures brand attributes in near real-time with superhuman accuracy. With deep neural networks trained on the NVIDIA DGX-1, and with the TensorRT inference engine, SAP improves performance by 40X, reduces hourly costs by 32X, and delivers immediate, accurate, and auditable results.
  80. 80. 80 CONTROLLING AIR TRAFFIC WITH AI From autopilot systems to customer service to predicting weather, AI is transforming aviation. With Aimee—a GPU-powered framework for AI solutions from Searidge Technologies—Air Traffic Control no longer needs a direct sightline. Aimee analyzes video feeds from hundreds of cameras, enabling ATC to look past occlusions and “see” every runway, taxiway, tarmac, and gate without looking away from their workstations.
  81. 81. 81 AI HELPS CREATE BEAUTIFUL MUSIC Music plays an impactful role in the experience of interactive media, but it’s challenging for composers to produce music for dynamic, user driven situations. Researchers at SensiLab used the NVIDIA DGX-1 to develop a new deep learning framework for adaptively scoring interactive media that’s been successfully implemented in two video games.
  82. 82. 82 NAME THAT TUNE IN REAL-TIME Shazam maximizes music recognition with NVIDIA GPUs on Google Cloud for intensive calculations and fast throughput. Each time someone Shazams a song, they send an acoustic fingerprint of the audio that their device recorded. Shazam uses that fingerprint and GPUs for the intensive operation of searching for and instantly matching songs in its catalog of >11 million songs.
  83. 83. 83 ACCELERATING IVA FOR SMART CITIES Intelligent video analysis (IVA) can safeguard citizens and property and is a key element of smart cities but analyzing data from millions of cameras in real-time requires deep learning and intensive computing power. SK Telecom uses NVIDIA GPUs to power T View, its AI VSaaS (Video Surveillance as a Service) solution. With Tesla GPUs, SKT speeds training 5x, and with TensorRT to scale its inference engine, SKT achieves cost-efficiencies without sacrificing accuracy.
  84. 84. 84 AI SHEDS LIGHT ON MYSTERIES OF THE UNIVERSE Gravitational Lensing generates an image of a distant light source that is distorted by the gravity of a massive object, such as a galaxy cluster. The distortions provide clues about how mass is distributed in space―and how that distribution changes over time―to measure properties of dark matter, galaxy size, and the expansion of the universe. Today there are roughly 200 known gravitational lenses and scientists expect to uncover another 200,000 over the next decade. Analyzing a single lens image with traditional approaches can take 2 days to 3 months. Scientists at SLAC are using GPU-powered artificial neural networks to analyze gravitational lenses in just 10 milliseconds. This speed up provides researchers with opportunities for new discoveries to shed light on the mysteries of our universe.
  85. 85. 85 The human retina contains diagnostic markers for many diseases, but testing requires the skills of specialists who are in short supply. Built on GPU deep learning with CUDA, the Mobile Autonomous Retinal Evaluation (MARVIN), from SocialEyes, can help transform healthcare systems worldwide. With MARVIN, tens of millions of community healthcare workers and physicians can diagnose a wide range of conditions immediately with low-cost mobile devices for timely and effective intervention. AI-POWERED HEALTHCARE AT SCALE
  86. 86. 86 With over 1B people living in extreme poverty, ending poverty tops the list of the UN’s sustainable development goals. But data that identifies impoverished areas is scarce. Researchers at Stanford University’s AI Lab used GPU deep learning with CUDA and satellite imagery to map areas of extreme poverty. Not only is the approach effective, scalable and cost efficient, the poverty maps will help world organizations locate those most in need of relief. MAPPING AN END TO POVERTY WITH AI
  87. 87. 87 Skin cancer is the most common form of all cancers. The 5-year survival rate of melanoma is ~98% when detected early, but drops to <20% when the disease is detected in its later stages. Scientists at Stanford University’s AI lab are using dermatology photos to help diagnose skin cancer. Using GPU-powered deep learning and 130K images representing >2K skin diseases, the team trained a convolutional neural network to recognize cancerous lesions. When tested, the AI tool was 90% accurate in its diagnosis and could help clinicians speed detection and diagnosis—key to a skin cancer patient’s outcome. AI TOOL HELPS DIAGNOSE SKIN CANCER Image credit: Matt Young
  88. 88. 88 In fashion, styles change quickly but the fundamental customer experience—brick-and-mortar stores and traditional online shopping sites—hasn’t changed much in the past decade. Stitch Fix broke that mold with a fashion styling service that combines the art of personal styling with data analytics insights powered by GPU-accelerated deep learning. Backed by a team of 70+ data scientists, Stitch Fix builds style recommendation algorithms to make its clients look their best. Take the Stitch Fix algorithms tour: http://algorithms-tour.stitchfix.com/ REINVENTING RETAIL BY COMBINING ART AND AI
  89. 89. 89 AI UNLOCKS SCIENTIFIC MYSTERIES Gravitationally lensed galaxies ―a prediction of the General Theory of Relativity― are rare and lie amongst billions of galaxies. Swinburne used astrophysical simulations to train a GPU-powered CNN to recognize gravitational lenses in astronomical image data, then applied those CNNs to the Dark Energy Survey image data to discover dozens of new gravitational lenses.
  90. 90. 90 AI: THE TICKET TO DELIVERING WORLD- CLASS LOGISTICS The Swiss Federal Railway (SBB) system connects all European railways with 300+ tunnels, 6,000 bridges, 80+ trains, and 30,000 switches. To ensure seamless logistics, SBB turned to simulation. Powered by the NVIDIA DGX-1 and its integrated software stack, SBB now simulates the physics of all train traffic in Switzerland for one day in just 0.3 seconds.
  91. 91. 91 AI IS ON TRACK TO SAFEGUARD RAILWAY INTEGRITY To maintain the integrity of its 3,232 km of tracks, the Swiss Federal Railways (SBB) runs diagnostics trains to photograph and monitor tracks in real- time. But traditional data processing methods produce false positives/negatives. To remedy this, SBB and CSEM (Swiss Research and Development Center) launched the Railcheck project which applies deep learning, powered by the NVIDIA DGX Station, to improve the automatic detection and classification of faults.
  92. 92. 92 In 2003 the Human Genome Project successfully decoded the human genome and unlocked the door to new genetic discoveries. With 3 billion nucleotide pairs in the human DNA, genome analysis is computationally intensive. The Tohoku Medical Megabank Organization (ToMMo) is using the power of its DGX-1 AI supercomputer cluster to accelerate understanding the complicated correlations between human genotype and phenotype. And, to further deep learning based genomics research, ToMMo will open its DGX-1 supercomputer cluster to external contracted researchers. DGX 3 NODE CLUSTER TO ADVANCE GENOMIC RESEARCH
  93. 93. 93 According to the World Health Organization, TB is one of the top 10 causes of death worldwide. 1.7M people died from the disease in 2016 with 95% of those deaths occurring in developing countries where access to radiological expertise is limited. Armed with >1,000 TB images, NVIDIA GPUs, Caffe, CUDA, and cuDNN, scientists at Philadelphia’s Thomas Jefferson University trained a deep learning model to read chest x-rays. With GPUs delivering a 40x increase in speed up over CPUs, the research could expand to include other lung diseases and possibly lead to the development of a centralized global chest x-ray library for healthcare providers in developing countries to use to accurately diagnose anomalies. FIGHTING TB WITH GPU-POWERED AI Image credit: Yale Rosen. Licensed via Creative Commons 2.0
  94. 94. 94 It takes an average of 12 years and >$2B to bring a new drug to market. Molecular dynamics (MD) simulation is a powerful tool to calculate potential efficacy. One key to accelerating drug discovery is the ability to run more MD simulations but this requires substantial computing power. Tokyo Tech’s Smart Drug Discovery Research Unit is using its GPU-powered TSUBAME supercomputer to accelerate drug discovery through massive MD simulation. With GPUs, Tokyo Tech has achieved a >50x speedup as compared to CPU-powered simulations, and they’ve already discovered a new drug candidate for Chagas disease, one of the Neglected Tropical Diseases. ACCELERATING DRUG DISCOVERIES, IMPROVING LIVES Tokyo Institute of Technology TSUBAME3.0 Supercomputer
  95. 95. 95 OPTIMIZED LOGISTICS MANAGEMENT The United States Post Office delivers >1.5 billion pieces of mail each year. To analyze and optimize routes of 200,000+ mail carriers in real-time the USPS turned to Kinetica and its GPU-accelerated data analytics platform. The USPS can now modify routes for optimal efficiencies—it’s using fewer trucks, handling more deliveries, and narrowing delivery windows.
  96. 96. 96 TEACHING A ROBOT TO STAND UP FOR ITSELF New approaches to AI promise to help scientists build machines with greater autonomy. Researchers at UC Berkeley are tapping into the processing power and integrated software of NVIDIA’s DGX-1 to advance robotics using reinforcement learning. DGX-1 with the CUDA programming model allows them to iterate faster and ultimately build robots that are able to understand and navigate a diverse and changing world on their own.
  97. 97. 97 ACCELERATING AI WITH GAME-BASED VIRTUAL WORLDS Deep Learning speeds up autonomous driving research, but the human task of keeping up with the image data can slow it down. Inspired by Grand Theft Auto V, scientists at the University of Michigan are replacing the tedious process with a simulation engine that rapidly generates annotated data in a game-based virtual world. The technique is powered by NVIDIA DGX-1 with CUDA and blows the doors off traditional approaches. Deep learning projects that took weeks now take days, and Michigan’s scientists can now focus less on note-taking and more on breakthroughs in self-driving car technology. Image courtesy of Les Nuits Photographiques
  98. 98. 98 Molecular energetics studies can lead to breakthroughs in drug discovery and materials science, but traditional computing approaches are time-consuming and expensive. Researchers at the University of Florida and the University of North Carolina leveraged GPU deep learning and CUDA to develop ANAKIN-ME, which can reproduce molecular energy surfaces with super speed, extremely high accuracy, and at 1-10/millionth the cost of current computational methods. AN AI QUANTUM BREAKTHROUGH
  99. 99. 99 AI PRODUCES THE 5TH STATE OF MATTER Bose-Einstein Condensate (BEC) is a state of matter formed by cooling a gas to near-zero absolute temperatures. BEC matter creation has proven useful in exploring superconductive material breakthroughs and creating extremely precise measurements of the Earth’s gravity. Researchers at the University of New South Wales used GPU-powered AI to create BEC matter 14x faster than conventional methods.
  100. 100. 100 AI ACCELERATES ASTEROSEISMOLOGY Light years away, aging stars are blazing into a fiery stage of life as red giants. Classifying the evolutionary stage of red giants was a slow manual process, so scientists from Australia and Denmark trained a GPU-powered convolutional neural network to learn visual features of red giants and predict a star’s age. Tests showed the AI system classified 7,655 red giants in real-time and achieved 99% accuracy.
  101. 101. 101 AI ACCELERATES DRUG DISCOVERY The discovery phase of drug development involves exploring different possible combinations of protein molecules (targets) and drug chemical compounds to ensure the drug will do what it’s designed to do. Classic Molecular Dynamics simulations are time-consuming and expensive. Machine Learning models help predict probability of the target molecules interacting with the drug chemical compounds, but still require significantly greater performance to deliver improved accuracy. Researchers at the University of Pittsburgh are improving model performance and prediction accuracy. Their convolutional neural network, accelerated with NVIDIA GPU’s and CUDA, improved prediction accuracy from ~52% to 70% compared to other machine learning-based models.
  102. 102. 102 Studying the size, shape, age and location of moon craters provides insight into the history of our solar system. Counting and determining characteristics of craters was a manual process until researchers at the University of Toronto and Penn State University developed a convolutional neural network, powered by NVIDIA Tesla P100 GPUs on the SciNet P8 supercomputer, to detect and classify characteristics of craters from Lunar digital elevation maps. Upon implementation, the AI system identified 6,000 new craters in just a few hours—orders of magnitude faster than human counting—and is now being applied to study craters on Mercury. MAPPING THE MOON’S CRATERS Image courtesy of NASA
  103. 103. 103 AI-enabled transformations such as autonomous vehicles, personal assistants, and medical breakthroughs can greatly benefit society, but demand for applied AI is growing faster than the talent pool. UnternehmerTUM is on a mission through its Applied.AI Initiative to accelerate the delivery of AI solutions by educating and connecting talent with state-of-the-art technology & industry companies. The government-backed initiative—which expects 3,000 participants and >30 new AI startups its first year—has selected the NVIDIA DGX-1V and DGX Station with CUDA, and the Deep Learning Institute to realize its vision for the Applied.AI Initiative as the leading innovation hub for AI in Germany and one of the top three centers in the world. ACCELERATING THE DELIVERY OF AI SOLUTIONS
  104. 104. 104 EXTRACTING NEW VALUE FROM VIDEO Imagine being able to quickly find any scene in any video. Valossa AI provides unparalleled capabilities to capture new value from video with advanced audio-visual content search and recognition. Powered by the NVIDIA GPU hardware and software stack for deep learning and inference, Valossa cut training time from weeks to hours and processes videos 30X faster and more accurately than CPU-based methods, enabling a new generation of video analytics and monetization.
  105. 105. 105 BETTER DATA, SMARTER BUILDINGS Verdigris is on a mission to help businesses eliminate wasteful energy spend. By harnessing the power of data and GPU-powered deep learning, Verdigris’ Smart Building optimization solutions continually audit and analyze electronic signatures of individual devices to learn what's normal and what’s energy waste. Furthermore, with real-time monitoring and alerts, operations teams can proactively respond before a situation becomes problematic.
  106. 106. 106 THE BRAINS BEHIND SMART CITIES Verizon’s Smart Communities Group is on a mission to make cities safer, smarter and greener. Using NVIDIA Metropolis, an edge- to-cloud video platform for building smarter, faster AI-powered applications, Verizon is working to collect and analyze multiple streams of video data to improve traffic flow, enhance pedestrian safety, optimize parking and more.
  107. 107. 107 REAL-TIME SPEECH SERVICES AT SCALE WeChat, a leading Chinese social media platform with ~1B users, wanted to improve its speech to context services. But as the company deployed its new acoustic model, its CPU-only servers were unable to effectively run the new version. WeChat deployed servers equipped with Tesla P4 GPU inference accelerators and increased speech inference throughput by 2.5X and in-model accuracy by 20%—all while staying within its low latency budget.
  108. 108. 108 Autonomous vehicles can reduce accidents, improve the productivity of trucks and taxis, and enable new mobility services — transforming the $10 trillion transportation industry. WEpods is piloting an autonomous shuttle that leverages GPUs to compute data and build a complete picture of the environment, enabling it to safely navigate traffic and other obstacles. It’s a revolutionary new kind of transportation that offers the convenience of a personal vehicle, without the hassles of car ownership. REVOLUTIONIZING TRANSPORTATION WITH AI
  109. 109. 109 Wildbook is protecting endangered animals by blending wildlife research with AI, citizen science, computer vision, and data analytics to speed population analysis and develop new insights. Wildbook harnesses publicly shared videos, photos, text and audio, and with the power of GPUs speeds up the task of identifying animals of all kinds. GPUs reduce the time it takes to not only detect species but each individual animal, from a few seconds per image to a fraction of a second—a significant time savings as Wildbook deals with thousands of images per species. USING AI TO COMBAT EXTINCTION
  110. 110. 110 AI DEMOCRATIZES MOTION CAPTURE Motion capture has revolutionized the entertainment industry, but traditionally has required specialized equipment and expertise. wrnch democratizes motion capture with AI that makes any camera capable of digitizing human movement. wrnch’s GPU-powered deep learning software recognizes human motion in 2D RGB video, then creates 3D motion data. With NVIDIA TensorRT, wrnch’s AI performs 2x faster during inference—it Delivers results in real-time and Creates endless possibilities for new applications.
  111. 111. 111 AI-BASED NEXT GEN WEATHER FORECASTS Improving the speed and accuracy of weather forecasts is big business, with the potential to save billions across global supply chains, commercial air travel, agriculture and more. To create the world’s first widely available ‘nowcasting’ service, researchers at Russia’s online search engine Yandex created a prediction model trained on more than 800,000 sequences of Russian radar data and satellite images. Applying NVIDIA GPUs with CUDA to its convolutional neural network sped its system’s learning by more than 40% - the speed they needed to alert users to sudden rainstorms just 10 minutes away.
  112. 112. 112 MODERNIZING THE WAREHOUSE Worldwide retail e-commerce sales are expected to reach $2 trillion in 2016, according to eMarketer. With thousands of orders placed every hour, data scientists at Zalando, Europe’s leading online fashion retailer, applied deep learning and GPUs with CUDA to develop the Optimal Cart Pick algorithm. Applying the algorithm resulted in an 11% decrease in workers’ travel time per item picked. The work is a good example of the efficiencies that AI can discover for e-commerce, manufacturing and other large-systems-based industries.
  113. 113. 113 The demand for medical imaging services is continuously increasing, outpacing the supply of qualified radiologists and stretching them to produce more output, without compromising patient care. It’s not atypical for hospitals to have a large backlog of x-rays waiting to be routed. Zebra is using GPU-powered AI to augment the capabilities of radiologists. Its low-cost AI1 assistant instantly detects diseases of the lung, breast, liver, cardiovascular system, and bones to help radiologists manage the ever increasing workload while continuing to deliver quality care. AI TRANSFORMS PATIENT CARE
  114. 114. 114 DEVELOPING THE VEHICLES OF THE FUTURE Zenuity, a joint venture of Volvo and Veoneer, aims to build autonomous driving software for production vehicles by 2021. They chose to build their deep learning infrastructure with NVIDIA DGX-1 servers and Pure FlashBlade systems to accelerate their AI initiative.

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