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Artificial Intelligence (AI): Solution Development

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Some Enterprises are already using AI for data analytics in the datacenter, the cloud, and at the edge but wider deployment of these applications and implementation at scale comes with its own challenges. Intel is building a broad range of technologies that help drive the adoption and deployment of AI across the institutions for more businesses and researchers. In this session we will discuss respective technology that helps address these challenges with a special focus on how to enable successful development of AI solutions in the datacenter. We will touch various levels such as Tools , Frameworks, Libraries and Hardware including a view on optimization to get performance. We also show some of the exciting applications that these technologies are enabling.

Speaker:
Stephan Gillich
Ian Godfrey

Publié dans : Technologie
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Artificial Intelligence (AI): Solution Development

  1. 1. Human Centric Innovation Co-creation for Success © 2018 FUJITSU Fujitsu Forum 2018 #fujitsuforum
  2. 2. © 2018 FUJITSU Artificial Intelligence: Technology and Development towards Solutions Stephan Gillich Director AI GTM EMEA, Intel Deutschland GmbH Ian Godfrey Director Solution Business, Fujitsu Systems Europe
  3. 3. 2 © 2018 FUJITSU Customer Story: Healsy
  4. 4. 3 © 2018 FUJITSU The Need To evaluate sugar or insulin needs, all events and information impacting glycemia must be processed – blood glucose readings, insulin injections, meal intakes, physical activities, emotional states, stress or fatigue, etc. This complexity leads to errors and severe consequences. Each patient with diabetes is different, and so requires a personalized approach to help manage their blood glucose
  5. 5. 4 © 2018 FUJITSU The Solution – Personalised Glycemia Prediction  In 2015 there were over 415 million diabetic patients worldwide** with 223 million diagnosed  Healthcare cost of hyperglycemia (persistently high blood glucose levels) and hypoglycemia (low) estimated at $730B***, with 2/3 concerning complications  Healsy is a startup aiming to develop a completely personalised approach that takes dynamic account of the environment and reactions of the individual patient  As every patient is different this predictive mobile service continuously monitors glucose levels and other data from wearable devices, and provides information adapted to their specific physiology and habits  Healsy‘s AI solution is specific to each patient, and can be trained with only 10 days of data per patient **International Diabetes Federation *** FID @ 2017
  6. 6. 5 © 2018 FUJITSU Working with “Small Data” The problem is essentially one of “small data” – the data from the patient as an individual, requiring different models and various time-horizon predictions Healsy’s solution is in a fully automated process that creates many personalised models (features selection, parameters tuning …) yet is general enough to adapt and work for each patient.
  7. 7. 6 © 2018 FUJITSU Small data, many models  Starting from a different “small-data” principle means Healsy must completely develop their own machine learning models, sometimes using neural network algorithms  Finding optimal models means continuously testing diverse data combinations against a multiple candidates algorithms  Healsy primarily code in R, Python and Tensorflow and use both mainstream and specific processing technologies  Lowest latency at all points along the pipeline are needed to make Healsy’s solution viable – from data-centre to end-point  Intel technology assists at all points across this spectrum, helping businesses bring practical AI solutions to market Synchronize • Continuous Glucose Monitoring • Insulin Delivery Devices • Activity Tracker Learn • Behavioral Analysis • Physiological Responses Analysis • Continuous System Improvement Anticipate • Glycaemia real-time prediction • Patient-specific solution • Hypo & hyperglycaemia anticipation
  8. 8. 7 © 2018 FUJITSU Transforming lives with personalized decision support “The first predictive mobile service for continuous glucose levels monitoring that adapts to every patient”
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