Dell AI Telecom Webinar
- 1. 1 Digital Transformation Through Analytics AI and Telecom Transformation Bill Wong Artificial Intelligence and Big Data Practice Leader Dell Technologies
- 2. 2 Telecom – Key Business and Innovation Drivers Improve Network Operations Monitoring and Management to deliver efficient, timely and reliable management operations Grow revenue by enhancing the customer experience and improving fraud mitigation Improve cybersecurity capabilities to reduce threats to the network and services Lower costs of operations using predictive maintenance
- 3. 3 AI Opportunities Customer Experience Chatbots can use advanced image recognition and social data to personalize sales conversation Customer Acquisition Classify customer wallets into micro- segments to establish finely-tuned marketing campaigns and provide AI-driven insights on the next best offers Network Intrusion / Detection Analyze data such as IP addresses, geographic data, email domains, mobile device types, operating systems, browser agents, phone prefixes, and more to prevent or remediate account takeovers Fraud Mitigation Real-time analysis to identify and detect and prevent fraud in all avenues of commerce including online and in-person transactions Industry Application Examples Analyze Consumers’ Behavior Campaign And Conversion Analysis Credit Card Application Approval Customer service chatbots/routing Claim Fraud Detection Evaluate Create Worthiness Fraud And Credit Risk Analysis Fraud Detection and more… Predictive Maintenance Proactive and predictive maintenance IOT Analytics Detect interference in cell towers and reconfigure to optimize performance
- 4. 4 Telecommunications Data Lake Supporting Digital Transformation through Advanced Analytics Consumption Zone / Data Analytics Raw / Landing/ Secure Zone/ Data Ingestion Documents and Emails Web logs, Click Streams, Newsfeeds, IOT/Sensor data Self-Service Dashboards Advanced Analytics Sales Analysts Consumer Dashboards Operational Analytics Data Scientists Customers Marketing Analysts Data Governance | Security and Compliance Enriched / Discovery Zone / Data Transformation Data Sources Common Services Optimized Infrastructure for Advanced Analytics Chat data Personas Tools / Applications Data Lake Capabilities • Provide support for a variety of analytical applications, including self-service, operational, and data science analytics • Data preparation and integration capabilities to ingest structured and unstructured data, move and transform raw data to enriched data, and enable data access to for the target user base • An infrastructure platform optimized for advanced analytics that can perform and scale OLTP, ERP, CRP Data Social Networks Machine Generated Data
- 5. 5 Expectations Plateau of Productivity Peak of Slope of EnlightenmentInnovationTrigger Trough of Disillusionment Inflated Expectations Hype Cycle for Artificial Intelligence “Narrow" AI is becoming better than humans at defined tasks. "General" AI is still a long way off.” Time Plateau will be reached less than 2 years 2 to 5 years 5 to 10 years more than 10 years Deep Learning Infrastructure Transformation Autonomous Vehicles “AI, one of the most disruptive classes of technologies, will become more widely available due to cloud computing, open source and the “maker” (developers, data scientists and AI architects) community. While early adopters will benefit from continued evolution of the technology, the notable change will be its availability to the masses. As of July 2019 AI PaaS Artificial General Intelligence Machine Learning NLP FPGA Accelerators GPU Accelerators DNN ASICs Quantum Computing Neuromorphic Hardware Computer Vision Speech Recognition
- 6. 6 Top 10 Types of Hardware for AI Delivery* 1. Processors (CPU, GPU, FPGA, ASIC) 2. HPC / Supercomputer Infrastructure 3. Communication Network 4. Personal Devices 5. Connected Home Devices 6. AR / VR Head-Mounted Displays (HMD) 7. Drones 8. Robotics 9. Automotive 10.Sensors and Application Components (audio, camera, LiDAR, etc.) *The Business Impact and Use Cases for Artificial Intelligence, Gartner, 2017 Accelerate computational performance AI-enabled endpoints AI-enabled autonomous endpoints
- 7. 7 AI Accelerators Flexibility Efficiency and many more…
- 8. 8 Deep Learning Analytics – GPU, Graphcore Dell Technologies – AI Compute Platforms Performance Inference Data Analytics Multi-App HPC / ML / DL C6420pC6420p R840 DS8440 8+ 4 2 - 3 1 Solution price $ C4140C4140 GPU DB Acceleration, AI/ML R940xa SDS/VDI R740XDR740XD 1:1 CPU/GPU ratio Highest density of CPU and memory with 2 GPUs GRAPHCORE IPU XILINUX FPGA INTEL FPGA NVIDIA GPU INTEL CPU AMD CPU GRAPHCORE IPU XILINUX FPGA INTEL FPGA NVIDIA GPU INTEL CPU AMD CPU
- 9. 9 Bitfusion Hypervisor 50% vGPU 30% vGPU 20% vGPU GPU Vsphere User Defined Virtualization VSphere Network Attached AI Abstract Pooling, Sharing and Automating GPUGPU GPU GPU GPU GPU GPUGPU GPU GPU GPU GPU GPU GPUGPU GPUGPU GPU GPUGPU GPU GPU GPU GPU GPUGPU GPU GPU GPU GPU GPU GPUGPU GPUGPU GPU NETWORK GPUGPU GPU GPU GPU GPU GPUGPU CLOUD GPU GPU GPU GPU GPU GPU GPU GPU GPUGPU GPU GPU GPUGPU GPU GPU GPU Maximize UtilizationMaximize Efficiency GPU Virtualization Economics
- 10. 10 Dell EMC Data Science Platform Nauta ClaraAI KubeFlow NVIDIA EGX Domino Cassandra HPCaaS Metropolis Spark Jupyter Bright Cluster Manger Dell-curated Ansible/ Terraform playbooks CNI MetalLB CoreDNS Prometheus NFS provisioner Helm Kubernetes Linux (RHEL/CentOS) + CRI (Docker/containers) 1 https://infohub.delltechnologies.com/section-assets/h18136-tco-analysis-dell-emc-hpc-ra-for-ai-da-sb On-premises system for HPC, AI and Data Analytics AI / Machine learning / Deep learning PowerSwitch S3148-ON S5232F-ON cluster switch PowerEdge R740 management and compute nodes PowerEdge C4140 acceleration nodes DSS 8440 dense acceleration nodes Dell EMC Isilon Dell EMC Ready Solution for HPC BeeGFS Storage Dell EMC Ready Solution for HPC NFS Storage © Copyright 2020 Dell Inc. HPC AI Ready Architecture One Platform for AI, Data Analytics, and Simulation Workloads • Simplified operations and lower cost while enabling new use cases for users at the lowest TCO1 • Allow HPC, DA & AI workloads to execute on the same cluster; reducing data movements for faster results • Run simulation & modeling, analytics, visualization, and AI workloads on a common HPC infrastructure Software ecosystem
- 11. 11 AI Magic Quadrants Data Science and Machine Learning Platforms Cloud AI Developer Services Data science and machine-learning platforms are defined as: • A cohesive software application that offers a mixture of basic building blocks essential both for creating many kinds of data science solution and incorporating such solutions into business processes, surrounding infrastructure and products. Cloud AI developer services are defined as: • Cloud-hosted services/models that allow development teams to leverage AI models via APIs without requiring deep data science expertise The Marketplace Continues To Evolve
- 12. 12 Data Analytics and AI Use Cases – Partner Solutions IOT / Streaming / Machine Data Analytics Deliver Near Real-Time Analytics • Analyze IOT / Streaming data • Improve IT operations and security leveraging Machine Data • Computer vision applications Machine / Deep Learning Transform the business with analytical insights • Data Science / Machine Learning Platform • Industry-focused AI platforms Data Lake/Unstructured Data Infrastructure Improving Data Access and Agility • Create an enterprise data platform for structured and unstructured data • ETL offload to lower costs • On-demand deployment of container-based environments Augmented Analytics and Data Warehouse Improve Decision Making • Support augmented business analytics • Create an enterprise data platform to support analytics • Data integration and Master Data Management
- 13. 13 H2O.ai DataRobot AutoML offerings H2O Driverless AI (commercial) and H2O-3 (open source) • Good adoption of its open source offering • Machine Learning Interpretability generates the constructs for the data scientist to use and explain the results of the models AutoML offerings enables business users and the Citizen Data Scientist • Easy to use, you do not need to be a data scientist • Prediction Explanation: Highlights the features that impact each model’s decision
- 14. 14 Accelerate Time From Research To Production With An AI ML Platform • Micro-services based and full stack data science platform. Decouple infrastructure from the data pipeline microservices. A code-first platform ready to integrate any containerized tools and open source • Accelerate AI development with reusable ML components, and production-ready infrastructure with native Kubernetes cluster orchestration and meta-scheduler. Iguazio Open and High Performance Data Science PaaS • Managed & hardened open-source plus 3rd party services and apps • Secure real-time data sharing enabling collaboration & parallelism • Minimize CPU, mem, and ops overhead Cnvrg.io
- 15. 15 Customer and Employee Health and Safety Solutions • Detection of persons/objects • Display showing temperature differences accurate to 0.1°C • Alarm in case of exceeding or falling below defined temperature ranges • Event Triggers (alarm, network message, activation of a switching output) • Temperature range from -40 to +550 °C •Face Redaction for privacy Dell Workstation with NVIDIA Dell Technologies Surveillance Solutions - Open Data Lake Platform - Scalable Infrastructure - Analytics-ready Image, Video and Thermal-based AI Applications Applications - Fraud Detection - Loss Prevention - Workplace Accident Reduction - Customer Insight - Public Safety - Counter Terrorism
- 16. 16 • Eliminate inefficient islands of storage – Infrastructure consolidation for both clinical and non-clinical workloads • Scales as data growth and number of instruments, modalities, and digital clinical applications increases • Enable better information sharing • Accelerate data analytics to gain new insight • Extends into the cloud • Prepared for next generation analytics Dell EMC Data Lake Caffe2 Data Lake Storage Platform
- 17. 17 The Digital Future Demands a New Perspective Cloud First Data First Infrastructure-centric Business-centric Takes into consideration: • Data gravity • Data velocity • Data control • Data privacy and compliance Driven by: • Lower infrastructure CapEx • Offload infrastructure maintenance • Improve time to market (deployment time for infrastructure) Evolve to a Data-Driven Business
- 18. 18 Decision Criteria for AI Infrastructure/Solutions Data Scientist Perspective IDC 2018
- 19. 19 • Design and build systems for HPC and Deep Learning workloads • Systems include compute, storage, network, software, services, support • Integration with factory, software, services • Power and performance analysis, tuning, best practices, trade-offs • Focus on application performance • Vertical solutions • Research and proof of concept studies • Publish white papers, blogs, conference papers • Access to the systems in the lab delltechnologies.com/innovationlab Dell Technologies HPC and AI Innovation Lab
- 20. 20 The Value of Dell for AI Infrastructure - Comprehensive and Scalable AI/Analytics Platform Portfolio - Workstations, Servers, Clusters, Storage, Networking - Infrastructure and Data Science and Analytics Expertise - HPC and AI Innovation Lab - IoT / Intelligent Video Analytics Lab - Solution-based Offerings - Pre-configured AI Ready Offerings - IoT / Safety and Security and Thermal Vision Solutions - GPU Virtualization - ML Platforms Infrastructure Scalability Reduce Complexity Address Demand Partner Ecosystem Cost Effective
- 21. 21 - Appendix - Dell Technologies AI and Data Analytics Solutions
- 22. 22 Dell Technologies AI and Data Analytics Solutions AI / Machine Learning / Deep Learning • Domino Data Science Platform Design Document • HPC for AI and Data Analytics Ready Architecture • Retail Loss Prevention Ready Solutions • DataRobot Reference Architecture • H2O AI Reference Architecture • Kubeflow Reference Architecture • OneConvergence Dkube Reference Architecture • Iguazio Reference Architecture • Deep Learning with NVIDIA Ready Solutions • Isilon with NVIDIA DGX-1 Reference Architecture • Isilon with NVIDIA DGX-2 Reference Architecture • Isilon with Dell Precision 7920 Data Science Workstation Reference Architecture • Isilon with Dell EMC DSS8440 Reference Architecture • Noodle.ai (OEM) Solution Bundle IoT / Streaming / Machine Data Analytics • IntelliSite (OEM) Thermal Detection Solution • Retail Loss Prevention Ready Solutions • Dell IoT Safety and Security Portfolio • Real-Time Data Streaming Ready Architecture • Splunk Enterprise on Dell EMC Infrastructure • Streaming Data Platform • ElasticSearch (OEM) Solution Bundle © Copyright 2020 Dell Inc. Augmented Analytics and Data Warehouse • Spark on Kubernetes • Kinetica (OEM) Solution Bundle • ThoughtSpot (OEM) Solution Bundle • Pivotal Greenplum • Dell Boomi Data Lake / Unstructured Data Infrastructure • Microsoft SQL Server 2019: Big Data Cluster Ready Solution • Cloudera Hadoop Ready Architecture • Hortonworks Hadoop Ready Architecture • Kubernetes Containers with Diamanti (OEM) Solution Bundle • Grid Dynamics Reference Architecture • Red Hat OpenShift Reference Architecture HPC Ready Solutions • HPC Digital Manufacturing • HPC Life Sciences • HPC Research • HPC BeeGFS Storage • HPC Lustre Storage • HPC NFS Storage • HPC PixStor Storage *Note, some products can deliver capabilities that address multiple use cases Product Offerings and Technical Collateral for Analytical Use Cases