How can we prevent project management from falling into the AI darkness?

whitePaper | January 12, 2020

“The services market for artificial intelligence technologies is rapidly maturing on the back of several years of learning and a realization—delivering AI is unlike delivering any other technology thus far. Delivering on the promise of AI calls for far more collaboration between service providers, tech vendors, and enterprise clients.” The biggest differentiator in enterprise AI services, as described by most of the customer leaders, is the quality of people—not just the quantity available for a specific skill. Domain understanding and data engineering capabilities are top priorities. A culture of innovation, experimentation, collaboration, and co creation with customers is the key winning formula here.”

whitePaper | June 29, 2023

Generative artificial intelligence (AI) is impacting many aspects of the business community. ChatGPT and other similar large language models (LLMs) have captured attention for their amazing ability to create human-like prose.1,2 Additionally, generative AI can create visually captivating artistic content, encompassing images, videos, and audio. Langevin diffusion deep learning models are primarily employed to generate this content, with open-source image generation models, such as Stable Diffusion, being the most popular approach.

whitePaper | April 16, 2020

A well-built store—one that is consistent with others under a retailer’s umbrella—is a powerful tool for communicating a brand. In fact, arguably nothing (beyond the product itself) is a more tangible signifier of the brand than the store environment. This puts the store planning team in the position of acting as brand managers and means that for the construction manager, whether he/she is employed in house by the retail company or as a contractor specializing in retail construction, understanding the brand (the retailer’s goals, visions, and marketing strategies) is a cornerstone of day-to-day work.

whitePaper | January 5, 2020

Machine learning (ML) is an application of artificial intelligence (AI) that allows systems to automatically learn and improve from exposure to more data without being explicitly programmed. ML focuses on the development of computer programs that can access data and use it to learn for themselves.1 While AI represents the broader concept of machines being able to carry out tasks in an intelligent way, machine learning is a current application of AI based on the idea that we can give machines access to data, and they can use that data to learn for themselves.

whitePaper | October 17, 2022

The NVIDIA DGX family of systems is made up of the world’s first integrated artificial intelligence (AI)-based systems that are purpose-built for enterprise AI. NetApp AFF storage systems deliver extreme performance and industry-leading hybrid cloud data-management capabilities. NetApp and NVIDIA have partnered to create the NetApp ONTAP AI reference architecture, a turnkey solution for AI and machine learning (ML) workloads that provides enterprise-class performance, reliability, and support.

whitePaper | October 18, 2022

Tachyum Prodigy is the industry’s first universal processor, unifying the functionality of CPU, GPU, and TPU into a single monolithic package. Prodigy’s revolutionary new architecture provides 6x more raw performance on AI training and inference workloads than the industry’s highest performing GPU, and up to 10x performance at the same power.