Machine Learning (ML) and Artificial Intelligence (AI) continue to increase in importance for Enterprise customers, whether for competitive advantage or increased operational efficiencies. Based on the 2019 vSphere Core Metrics survey, it’s clear that those Enterprises which run ML workloads do so in multiple locations and that about 55% of those workloads run in virtual environments on either public or private clouds. In addition, the data tell us that only about 17% of respondents (as of 2019) were running ML workloads, indicating that we are just at the start of the adoption of these technologies in the Enterprise.

Percentage of ML workloads running in each of four locations as reported by respondents to the 2019 vSphere Core Metrics Survey.

To help customers navigate this new space at VMworld 2020, the Machine Learning Program Office, from VMware Office of the CTO, created a dedicated track within the Vision & Innovation Track. These talks are intended for IT practitioners responsible for planning and deploying infrastructure to support these new and very resource-intensive workloads. You don’t need a degree in data science to enjoy the talks, but you will learn about your organization’s data scientists’ specific needs and how those needs can be met with VMware virtualized infrastructure. In addition to the AI/ML track sessions, there is an even larger number of ML-related talks spread across the entire VMworld program, a testament to the fact that these techniques are being spliced into our DNA as we evolve towards being the leading provider of intelligent IT infrastructure. Here is a guide to all the AI/ML content at VMworld 2020:

An overview of VMware’s ML/AI point of view:

[OCTO3010] The Three Pillars of Machine Learning at VMware

Partner and co-presented AI/ML track sessions:

[ETML1364] Scaling Distributed Machine Learning Using GPUs and RDMA on VMware vSphere

[ETML1443] Best Practices to Run ML and Compute Workflows with NVIDIA vGPU on vSphere

[ETML1696] Advanced Analytics for Enterprise AI

[ETML1848] Dynamic Optimization of Mixed VDI and Artificial Intelligence Workloads

[ETML1962] VMware and Intel Offer Enhanced Data Analytics Solution for Hybrid Cloud

[ETML2260] DevOps for Machine Learning: Enabling Successful ML for Your Organization

[ETML2467] Powering Intelligent Video Analytics with NVIDIA AI Using VMware Horizon

[ETML3134S] Scaling Analytics via Multi-cloud for Business Advantage

VMware AI/ML track sessions:

[ETML1110] Choosing the Best GPU Accelerator Approach for Machine Learning

[ETML1446] Next-Generation Machine Learning Architecture

[ETML1531] From BI to AI Using a Virtualized, Open-Source Data Platform

[ETML1575] ML for Transformative Disruption to Drive Customer Experience and Success

[ETML1739] Rapid Deployment of GPU Accelerated Machine Learning Environments

[ETML1760] VMware vRealize AI and the ML Drivers of the Self-Driving Data Center

[ETML1895] DeepThought: Power Your AI with VMware Tanzu

[ETML2143] Accelerate Data-Driven Innovation with VMware Tanzu

[ETML2517] Deep Dive into Machine Learning Architectures

[ETML2706] Expert Roundtable: Machine Learning and GPUs on VMware vSphere with Justin Murray

ML for Security:

[ISNS2794] The promise and peril of AI for cybersecurity

[ISNS1921] Deep Security Automation – Using ML to Secure Web Applications

[ISNS1144] NSX Intelligence: Visibility and Security for the Modern Data Center – Pt1

[ISWS1607] Leveraging Risk Analytics and ML to Detect Anomalies Based on User Behavior

[ISWS2927] Expert Roundtable: Leveraging Workspace ONE Intelligence Risk Analytics for Improved Security with Andreano Lanusse and Steve DeJarnett

[ISWL1084] Security Transformation: Fundamental Approaches to Combat the Changing Threat Landscape

[HCPS2626] Consuming Security/Firewall Services from a Cloud Provider

ML in Telco:

[TLCG2765] Put AI into Action in the Radio Access Network – A Technical Overview

[TLCG2763] 5G Ready Microservices for Assurance – a Technical Overview

Tanzu and ML:

[HCP1545] Modernize & optimize ML/AI/HPC applications with vSphere Tanzu

[HCP2097] Simplify and Boost Apache Spark with vSphere with Tanzu

[HCP1266] Using Kubernetes and vSphere Bitfusion for ML Workloads

Base platform ML:

[HCMB3046S] Accelerating the Hybrid Cloud for AI and Analytics

[HCP1246] What’s New with DRS and vMotion in vSphere 7

[HCP1190] How vSphere Bitfusion Can Help Customers in Their AI/ML Journey

Management and ML:

[HCI1458] Capacity Management Optimizations for vSAN and VMware Cloud Foundation

[VCNE2384] Seeing Is Believing: AIOps, Monitoring and Intelligence for WAN and LAN

[HCMB1518] What’s New in vRealize Operations

[HCMB2339] VMware Skyline and vRealize: Integrating Management and Support

Other ML-related Office of the CTO sessions:

[OCTO3029] Rapid Deployment of GPU Accelerated Machine Learning Environments With Chris Gully

[OCTO3028] Dell Technologies Multi-Cloud Strategy with Susan Yeager

[OCTO3032] Expert Roundtable: Inventing the Future: Technologies from VMware Research

[OCTO3031] Expert Roundtable: Emerging Technical Frontiers: Insights from VMware’s Academic Partners

[OCTO2406] Inside xLabs and Off-Roadmap Innovation in the VMware Office of the CTO

[OCTO2478] Edge Analytics: Computational Storage, Tanzu Greenplum, vSphere Bitfusion

[OCTO1668] Quantum Computing: How Will It Impact the IT Industry?

ML-related demos:

[DWHV2820] The Nerdfest VDI Demo: VDI*(AI + ML + Deep learning + GPU)

[DEM3302] Hands-on with an End-to-End Machine Learning Solution

[DEM3241] vSphere Bitfusion

[DEM3248] vRealize Network Insight Cloud 6.0 Innovations

[DEM3263] Hybrid Cloud Analytics Solution by Intel and VMware

[DEM3295] Leverage Risk Analytics for Zero Trust Security in Your Digital Workspace

[DEM3319] VMware Skyline and vRealize Operations Overview