Webinar: Elevating analytics: Transformative strategies for modern data, AI and ML challenges by VentureBeat

About This VB Spotlight

As AI hurtles forward, persistent issues plague the analytics and data science pros behind it. It’s just daily life.

Exhaustive demands of data preparation. The hurdles of handling large complex data sets. The time sink of long-running queries and batch processes, while data quality must be protected at all costs. Innovation hampered by runaway hardware and cloud costs.

William Benton, Principal Product Architect at NVIDIA, sits at the center of this morass, helping orgs uncomplicate the complicated.

Together with Michael Li of Aerial and VentureBeat, and Deborah Leff from SQream, they’ll be diving into cutting-edge technologies and methodologies set to redefine the landscape of data analytics and science.

Don't miss out on this opportunity to reshape your data destiny!

Agenda

Democratizing Acceleration: The technologies being used by companies of all sizes to dramatically shorten the time-to-market for product innovation
Optimizing AI and ML Infrastructure: How those orgs leading the race are triumphing over the hefty demands and costs of AI and ML systems to increase efficiencies
Slashing Data Analytics Costs: The proven methods companies are using to reduce costs without compromising performance
Elevating the Practitioner Experience: How teams are ditching mundane processes with solutions designed to enhance data integrity, streamline workflows, and empower you to extract maximum value from your data assets
Strategic Toolbelt: What to expect by the end? An arsenal of strategic solutions that will transform the way you approach data analytics, stocked with innovations geared towards driving business outcomes and propelling you into the future.

William Benton

Principal Product Architect, NVIDIA

William Benton is passionate about making it easier for machine learning practitioners to benefit from advanced infrastructure and making it possible for organizations to manage machine learning systems. His recent roles have included defining product strategy and professional services offerings related to data science and machine learning, leading teams of data scientists and engineers, and contributing to many open source communities related to data, ML, and distributed systems. Will was an early advocate of building machine learning systems on Kubernetes and developed and popularized the “intelligent applications” idiom for machine learning systems in the cloud. He has also conducted research and development related to static program analysis, language runtimes, cluster configuration management, and music technology.

Deborah Leff

Chief Revenue Officer, SQream

Deborah Leff is a leading expert in outcome-driven business transformation. She is a proven advisor to senior executives on successfully identifying, prioritizing, and delivering on strategic AI initiatives that impact their most critical business objectives. Deborah joined SQream as Chief Revenue Officer in June 2023 and is responsible for leading the company's global sales and go-to-market teams including global partnerships and business development, particularly in the North American market. Ms. Leff leads the efforts to drive SQream's growth and help achieve the company’s goal of enabling organizations to gain maximum insights from their data/AI/ML sets at a fraction of the time and with minimum costs. Prior to joining SQream, Ms. Leff was Global Leader of IBM Business Analytics and an IBM Industry CTO for Data Science and AI.

Tianhui "Michael" Li

Technology Contributor, VentureBeat (Moderator)

Michael is the co-founder and chief technology officer at Aerial, a ML-powered SaaS platform that organizes the data essential to scaling and running a company (legal document management). Prior to Aerial, he founded The Data Incubator, a data science training and placement company. Previously, he worked at Foursquare, Google, Andreessen Horowitz, J.P. Morgan, D.E. Shaw, Bloomberg, and NASA.

Michael is very passionate about non-profit causes around education and writes regularly about data science and big data.

He did his PhD at Princeton as a Hertz Fellow and a National Science Foundation Fellow and read Part III of the Mathematics Tripos at Cambridge as a Marshall Scholar.