Ten Steps for Successful Application Platforming in the Cloud

whitePaper | August 30, 2022

In late 2019, then newly elected European Commission President Ursula von der Leyen announced her intent to make regulating the use of artificial intelligence (AI) a top priority for Europe. She promised to “put forward legislation for a coordinated European approach on the human and ethical implications of Artificial Intelligence” within her first 100 days in office.

whitePaper | June 24, 2022

This new technology guide from DDN shows how optimized storage has a unique opportunity to become much more than a siloed repository for the deluge of data constantly generated in today’s hyper-connected world, but rather a platform that shares and delivers data to create competitive business value. The intended audience for this important new technology guide includes enterprise thought leaders (CIOs, director level IT, etc.), along with data scientists and data engineers who are a seeking guidance in terms of infrastructure for AI and DL in terms of specialized hardware. The emphasis of the guide is “real world” applications, workloads, and present day challenges.

whitePaper | September 2, 2022

The past several years brought about an abundance of change in how we as individuals, organizations, and a society approach daily life. Our views on ethics are evolving and our sense of acting with purpose is increasing – and as part of that, diversity, equity, and inclusion have become top corporate and personal objectives. Consumers are asking the brands they engage with for more transparency and are tasking them to act in ways that are fair and respectful to all stakeholders: suppliers, employees, prospects, and anyone else who interacts with the brand.

whitePaper | December 22, 2022

Machine learning, one of the key building blocks of AI, has been a part of the technological world since the 1950s, when the earliest programmers asked computers to make sense of large sets of data. Programmers have increasingly refined the ability of machines to study data in order to detect patterns that allow computers to then organise information, identify relationships, make predictions and detect anomalies. Today, modern applications of AI have already given us self-driving cars and virtual assistants and have helped us detect fraud and manage resources like electricity more efficiently. Sectors as diverse as retail, sports, banking, manufacturing and healthcare have all found applications for machine learning and AI.

whitePaper | August 26, 2022

Started in 2013, Arya.ai is the first deep learning (DL) startup in India and has been one of the very early adopters to use DL in Financial Institutions. AryaXAI by Arya.ai, a full stack ML Observability platform, offers multiple components - AI explainability, ML monitoring, ML audit and Policy controls, which organisations require beyond simple ML monitoring tools.

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.”