In this role, Satish and his team are responsible for driving and transforming services for Dell’s APEX, Multicloud and Telecom Services business across Product, Strategy, Engineering, SRE and Delivery. Satish is the Vice President for Emerging Services at Dell Technologies. Meanwhile, connect with your Dell Technologies representative or learn more here.ġ IDC, Cloud’s Next Stage: The Foundation of Digital Business, Doc #DR2023_GS3_RV , March 2023Ģ IDC PaaSView and the Developer 2022: Executive Summary 2022 ,ģ McKinsey & Company, “Operationalizing Machine Learning in Processes” by Rohit Panikkar, Tamim Saleh, Maxime Szybowski and Rob Whiteman, September 27, 2021. Want to know more? Connect with us at Dell Technologies World where you can join breakout sessions, broadcasts and demos. Dell’s growing portfolio of managed services leverages modern, easy-to-consume and increasingly automated solutions that drive business value from technology investments. These solutions empower IT teams to focus on productivity and innovation, while Dell manages the rest. New partnerships with colocation service providers enable Dell to provide more choice and flexibility. Colocation with Dell Technologies Services: Colocation with Dell Technologies Services streamlines cloud integration, simplifies deployment and makes operations more efficient.This gets models to production faster by reducing the complexity of deploying and maintaining AI/ML systems. Dell Managed Services for ML Ops: A fit-for-purpose platform for ML model development with integrated lifecycle management based on Dell validated designs.This accelerates innovation by freeing developers from managing infrastructure so they can spend more time coding. Dell Managed Developer Cloud: Self-service virtual machines and containers in an API-based cloud environment, with built-in infrastructure-as-code infrastructure management.To assist organizations with these challenges and rapidly scale their digital business, Dell Technologies is announcing three new managed services: But when organizations build a private cloud to address these concerns, they often find they have a shortage of cloud skills to drive solutions at the speed they need. This raises cost and privacy concerns – driving even more businesses to own their AI/ML operations and management. Additionally, the rise of large language models (e.g., ChatGPT, Bard, etc.) necessitates increased compute power and big data sets for AI/ML training. The first impulse of many AI/ML model builders and application developers is to turn to easy-to-consume public cloud services, but there may be cost and integration challenges with existing systems and data. Similarly, only about 36% have deployed machine learning beyond the model stage³ and many ML projects never make it to production. IDC estimates that 310 million new applications were built in 2022 and 750 million new applications are expected in 2025.¹ For data scientists and application developers, coding and building AI/ML models is how they drive the business forward.Ĭontemporary developers spend less than 20% of their time coding.² The rest of the time is spent waiting for IT resources and approvals or managing underlying infrastructure. Energy, Climate Action & Sustainabilityĭigital business growth and success are directly proportional to the speed of generating new data insights and developing new digital products and services.
0 Comments
Leave a Reply. |