Quantum ActiveScale Data Layer

Event: Tech Field Day 22

Appearance: Quantum Presents at Tech Field Day 22

Company: Quantum

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Personnel: Noemi Greyzdorf, Thomas Demoor

Thomas Demoor, ActiveScale Lead Architect, and Noemi Greyzdorf, Director of Product Marketing, discuss the data layer of Quantum ActiveScale. Unstructured data is growing rapidly, and customers require a new type of architecture to handle this influx of data. Quantum’s ActiveScale has the ideal architecture to solve customer problems. In this Tech Field Day 22 presentation, Demoor and Greyzdorf explore the data layer, which enables better data durability and optimal data placement. These features ensure customers will benefit from the highest performance at the lowest cost for storage, and durability to ensure that data is available when needed, even over a period of many years.


Quantum ActiveScale Layered Architecture

Event: Tech Field Day 22

Appearance: Quantum Presents at Tech Field Day 22

Company: Quantum

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Personnel: Noemi Greyzdorf, Thomas Demoor

Thomas Demoor, ActiveScale Lead Architect, and Noemi Greyzdorf, Director of Product Marketing, discuss the architecture of Quantum ActiveScale. Unstructured data is growing rapidly, and customers require a new type of architecture to handle this influx of data. Quantum’s ActiveScale has the ideal architecture to solve customer problems. In this Tech Field Day 22 presentation, Demoor and Greyzdorf explore the dual-layered architecture that enables enterprise scalability and performance to meet demanding applications. The architecture starts with the access and metadata layer and is the foundation for additional features not available in other architectures.


Quantum Object Storage and ActiveScale Introduction

Event: Tech Field Day 22

Appearance: Quantum Presents at Tech Field Day 22

Company: Quantum

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Personnel: Thomas Demoor

Thomas Demoor, ActiveScale Lead Architect, introduces Quantum’s object storage solution. Unstructured data is growing rapidly, and customers require a new type of architecture to handle this influx of data. Traditional storage systems optimized for file data cannot meet the scale and unique needs of unstructured data (e.g. media and entertainment, autonomous vehicles, life sciences or genomic data). Quantum’s ActiveScale offers a new architecture that solves the critical problems that customers have – ensuring performance and scalability for very large datasets. This Tech Field Day 22 presentation provides an overview of this industry segment plus a brief introduction to the ActiveScale line of unstructured storage products.


Quantum Company Overview

Event: Tech Field Day 22

Appearance: Quantum Presents at Tech Field Day 22

Company: Quantum

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Personnel: Ed Fiore

Ed Fiore, GM of Primary Storage, introduces the new Quantum in 2020. Quantum focuses on creating innovative technology and solutions to help customers get the most value from their data. With 40 years of storage know-how, Quantum’s technology, solutions, and services help customers capture, create, and share digital content – and preserve and protect it for decades. In this section of their Tech Field Day 22 presentation, Fiore provides an overview of Quantum’s portfolio and share insights on the company’s new direction. Quantum has made a series of recent announcements in a wide range of new product categories, and this is just the beginning. They have a unique product portfolio and key intellectual property to solve a range of customer problems for unstructured data.


Commvault HyperScale X Powered by Hedvig

Event: Tech Field Day 22

Appearance: Commvault Presents at Tech Field Day 22

Company: Commvault

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Personnel: Geeta Vaghela

Geeta Vaghela, Senior Director, Products, presents Commvault HyperScale X powered by Hedvig. Data is siloed in infrastructure silos, and Hedvig for HyperScale X is designed to solve this with performance, scalability, and resilience. Vaghela then demonstrates the HSX product, backing up a virtual machine and simulating a node failure.


Managing and Protecting Data in Kubernetes with Commvault

Event: Tech Field Day 22

Appearance: Commvault Presents at Tech Field Day 22

Company: Commvault

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Personnel: Mathew Ericson

Mathew Ericson, Senior Product Manager, discusses Commvault’s data protection offerings for Kubernetes. The adoption of containers presents new challenges for data management, and Commvault is addressing these with Hedvig distributed storage, Metallic backup, and Commvault Complete data protection. Commvault protects all Kubernetes data, from Dockerfile manifests and source code to the container registry to data on persistent volumes and object stores. Ericson then discusses data protection with the Tech Field Day delegates, presenting a reference architecture and demonstrating the solution in action.


Commvault Metallic: No-Comprise BaaS

Event: Tech Field Day 22

Appearance: Commvault Presents at Tech Field Day 22

Company: Commvault

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Personnel: David Ngo, Janet Giesen

Janet Giesen, VP, Operations & Programs, and David Ngo, CTO, introduce Metallic, a Commvault Venture. One year after introducing Metallic, Commvault is seeing customer adoption and accolades for the backup as a service product. Metallic is now available in 14 countries and has been expanded from core backup and recovery, Microsoft Office 365 data protection, and endpoint backup and recovery, to include VM and Kubernetes backup, database backup, file & object backup, and eDiscovery as well as a cloud storage service for Commvault customers. Ngo demonstrates Metallic Cloud Storage Services (MCSS), which provides a managed cloud storage solution in Microsoft Azure, and discusses how the Metallic as-a-service offerings work with the Tech Field Day delegates.


Introducing Commvault Recovery Readiness Solutions

Event: Tech Field Day 22

Appearance: Commvault Presents at Tech Field Day 22

Company: Commvault

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Personnel: Jeff Harbert

Jeff Harbert, Director, Technical Services Programs, presents Commvault’s recovery readiness solutions. Recovering from a catastrophic data loss or data-compromising event requires a plan, and Commvault’s Readiness Solutions help prepare companies to return to operations. Harbert discusses Commvault’s readiness approach and takes questions from the Tech Field Day delegates.


Commvault Disaster Recovery Updates

Event: Tech Field Day 22

Appearance: Commvault Presents at Tech Field Day 22

Company: Commvault

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Personnel: Rahul Pawar

Rahul Pawar, VP, Product Management, introduces the expanded Commvault portfolio of disaster recovery products. Disaster Recovery is a new product in the Commvault portfolio, providing a simple, flexible, powerful, scalable, and intelligent disaster recovery solution for businesses. It addresses the modern hybrid and multi-cloud enterprise, supporting common platforms like VMware and clouds like Azure, AWS, and GCP. Pawar then demonstrates the product and takes questions from the Tech Field Day delegates.


Don Foster Introduces the New Commvault

Event: Tech Field Day 22

Appearance: Commvault Presents at Tech Field Day 22

Company: Commvault

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Personnel: Don Foster

Don Foster, Global VP, Sales Engineering, introduces the new Commvault in 2020. Commvault has responded to multi-cloud, cloud-native, automation, DevOps, and changing IT economics to build an intelligent data management portfolio. The goal is to provide data awareness, agility, and automation through Commvault products, from backup & recovery and disaster recovery to file storage optimization, data governance, eDiscovery and compliance, and multi-protocol storage both on-premises and as SaaS.


Introduction to VAST Data LightSpeed: Storage Architecture for Machine Intelligence

Event: AI Field Day 1

Appearance: Intel Presents VAST Data at AI Field Day 1

Company: Intel, VAST Data

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Personnel: Howard Marks, Jeff Denworth

Jeff Denworth, CMO, introduces VAST Data LightSpeed, a storage platform for next-generation AI applications. The LightSpeed platform is designed to enable any platform to gain maximum performance via a single NFS mount point. NFS over RDMA can exceed multiple gigabyte per second performance using nconnect multipath. Denworth then discusses the need for high-speed NFS storage for AI applications and presents benchmarks for Nvidia DGX-A100 with VAST Data LightSpeed. He also presents a use case of AI imaging using LightSpeed. This session was sponsored by Intel.


Introduction to VAST Data Universal Storage

Event: AI Field Day 1

Appearance: Intel Presents VAST Data at AI Field Day 1

Company: Intel, VAST Data

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Personnel: Jeff Denworth

Jeff Denworth, CMO, introduces VAST Data’s universal storage product. It is designed to be a universal data platform for all applications, with all-NVMe performance, tier-5 cost efficiency, and exabyte scale for NAS and object storage. It is built on a modern foundation with disaggregated storage networking using NVMe-over-Fabrics, revolutionary flash economics using Intel QLC NAND SSDs, and persistent memory using Intel Optane SSDs. This session was sponsored by Intel.


Machine Learning Use Cases for MemVerge Memory Machine Software

Event: AI Field Day 1

Appearance: Intel Presents MemVerge at AI Field Day 1

Company: Intel, MemVerge

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Personnel: Yue Li

Yue Li, Co-Founder and CTO, presents AI applications for MemVerge Memory Machine software. He begins with training using large memory, showing that DRAM can be combined with Intel Optane Persistent Memory (PMEM) to provide large memory capacity with DRAM-like speed. He uses GraphSAGE as an example of machine learning on a large graph with MemVerge Transparent Memory Service. Next he presents inference with a large model and feature embeddings using Facebook’s DLRM as an example. He also uses image recognition as an example of leveraging MemVerge. Finally he discusses using persistent memory for instant model rollback or recovery.


Cisco AL and ML for Endpoint Analytics and Detecting Spoofing Attacks

Event: AI Field Day 1

Appearance: Cisco Presents at AI Field Day 1

Company: Cisco

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Personnel: JP Vasseur

JP Vasseur PhD, Cisco Fellow and head of ML and Data Science engineering, presents an advanced use case for machine learning in network security. He discusses clustering using machine learning and how Cisco can measure the efficacy of the results in terms of purity, percentage of unassigned, number of clusters, speed of unknowns resolution, and stability. He then gives a sneak peek at what comes next: Detecting spoofing attacks with ML/AI. ML is an excellent tool for detecting anomalies, and Vasseur presents a specific mechanism to accomplish this using ML instead of complex rules.


Advanced Endpoint Visibility with Cisco AI Endpoint Analytics

Event: AI Field Day 1

Appearance: Cisco Presents at AI Field Day 1

Company: Cisco

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Personnel: Krishnan Thiruvengadam

Krishnan Thiruvengadam, Technical Marketing Engineer, discusses advanced endpoint visibility using Cisco’s AI Endpoint Analytics. After discussing the benefits and challenges of network visibility, Thiruvengadam presents Cisco’s next-generation endpoint visibility capability with AI-driven analytics and deep packet inspection. It provides high-fidelity profiling, improved classification, and better workflows with integration with third-party products.


Cisco’s AI/ML Networking Journey

Event: AI Field Day 1

Appearance: Cisco Presents at AI Field Day 1

Company: Cisco

Video Links:

Personnel: JP Vasseur

In this presentation, JP Vasseur PhD, Cisco Fellow and head of ML and Data Science engineering, presents the journey of Cisco’s AI applications from 2013 to 2020. This journey began with self-learning networks, then proceeded to AI network analytics for wireless automated detection and root cause analysis, and now to ML-based security classification and behavioral spoofing detection. He also demonstrates Cisco AI Endpoint Analytics on Cisco ISE.


Building Big Data AI Applications on Intel Analytics Zoo

Event: AI Field Day 1

Appearance: Intel Presents Analytics Zoo at AI Field Day 1

Company: Intel

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Personnel: Jason Dai

Jason Dai, Senior Principal Engineer, discusses practical applications of Intel’s Analytics Zoo, an open source software platform for big data AI. This presentation focuses on four applications: Recommendation, time series analysis, computer vision, and natural language processing. His first example is the food recommendation engine used by Burger King, which uses a transformer cross transformer (TxT) model leveraging HDFS, Apache Spark and MXNet, and Ray. Next, Dai discusses how SK Telecom’s time series based network quality prediction solution is able to run up to 6x faster using Analytics Zoo on Intel Xeon and presents a similar use case of wind power prediction using Analytics Zoo by GoldWind, which improved accuracy to 79% with a 4x training speedup. When it comes to computer vision, Dai presents industrial inspection by Midea and KUKA and AI-assisted radiology with Dell EMC. Finally, natural language processing (NLP) is presented, using a chatbot in Microsoft Azure and job recommendation engine in Talroo as examples.


Intel Analytics Zoo Technical Overview and Case Studies

Event: AI Field Day 1

Appearance: Intel Presents Analytics Zoo at AI Field Day 1

Company: Intel

Video Links:

Personnel: Jason Dai

Jason Dai, Senior Principal Engineer, gives a deeper technical overview of Intel’s Analytics Zoo, an open source software platform for big data AI. Analytics Zoo uses distributed TensorFlow/PyTorch on Apache Spark, and Dai discusses how it is used in network quality prediction by SK Telecom. Next he focuses on RayOnSpark to run Ray programs directly on the big data platform, giving the example of Burger King’s fast food recommendation engine which leverages an end-to-end training pipeline with RayOnSpark. Turning to the ML workflow question, Dai discusses how a scalable AutoML allows time series prediction, using the example of Tencent Cloud’s TI-One ML platform. Finally, Dai presents the Zouwu open source time series framework on Analytics Zoo.


Intel Analytics Zoo: Software Platform for Big Data AI

Event: AI Field Day 1

Appearance: Intel Presents Analytics Zoo at AI Field Day 1

Company: Intel

Video Links:

Personnel: Jason Dai

Jason Dai, Senior Principal Engineer, presents Intel’s Analytics Zoo, a software platform for big data AI. Just as BigDL enables distributed, high-performance deep learning, Analytics Zoo is a unified big data AI platform for TensorFlow, PyTorch, Keras, BigDL, OpenVINO, Ray, and Apache Spark. This open source project reflects the transformation of big data, which now includes AI. After a brief case study, Dai presents the overall architecture of Analytics Zoo and discusses seamless scaling of analytics and AI from laptop to distributed big data.


Intel’s Transformation for the Intelligence Era

Event: AI Field Day 1

Appearance: Intel Presents Analytics Zoo at AI Field Day 1

Company: Intel

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Personnel: Fadi Zuhayri

Fadi Zuhayri, Sr. Director, Big Data AI, introduces Intel’s transformation for the the intelligence era. He begins with some background, as compute democratization has brought technology to the exascale era. He also presents the drivers for transformation, 5G, artificial intelligence (AI), and the intelligent edge, and how these have driven the technology pillars addressed by Intel. Intel’s analytics and AI strategy focuses on diverse hardware, software, and ecosystems from edge to cloud, providing a foundation for AI workloads. Next, he looks at Intel’s oneAPI which provides an abstraction layer to support any application or middleware on any hardware, and Intel DevCloud, which makes it easier to learn and develop software.


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