Enterprise AI flywheel effect drives scalable use cases – News

The “flywheel effect” has taken hold in the rapidly evolving world of enterprise AI, and it is driving collaboration among major industry players to build scale and resilience.

The “flywheel” business concept, first popularized by the author Jim Collins in his book, “Good to Great,” describes how consistent, small efforts to build momentum over time can lead to breakthroughs and sustained growth. In the AI world, this measure of progress can be seen more fully through initiatives, such as the collaboration involving Hewlett Packard Enterprise Co., SHI International Corp. and their partners.

TheCUBE, News Media’s livestreaming studio, spoke with leaders from HPE, SHI and their partners during the recent SHI Fall Summit to highlight how strategies designed for resilience, trust and long-term impact will be essential for deploying AI at scale and generating meaningful outcomes. Use cases for AI applications are beginning to emerge as enterprises embed AI into infrastructure to unify data, reduce risk and build governance into system design. The “flywheel effect” is generating results in ways that will become more apparent over time, according to Tyler Webb, director of AI sales at SHI.

“A lot of customers are asking, ‘What are the industry use cases that we’re seeing success in, and where are other companies focusing their time and efforts?” Webb told theCUBE. “We’re talking about full stack development, full stack design, container, everything below, everything above, and bringing a solution to life. A lot of the results on the surface will be tangible ROI from day one, but a lot of the benefits of these AI initiatives could be seen further down the road.”

This feature is part of News Media’s ongoing exploration into the evolution of AI innovation and cybersecurity resilience. (* Disclosure below.)

Enterprise AI framework for the full-stack

SHI employs a structured framework to help customers identify the business challenges and envision the ways that AI can create new opportunities. The goal is to prototype AI solutions using full-stack development and testing for impact and measurable ROI.

“It’s a framework called ‘Imagine, Experiment, Adopt,’” Webb explained. “We really start with that imagination phase where it’s understanding the business problems that our customers are running into and how AI could create some of those improvements or efficiencies that they’re looking to achieve.”

This leads to use cases that will actually impact specific processes or workflows. In June, SHI launched its Digital AI Ambassador Development Platform, in collaboration with Nvidia Corp. and HPE, to accelerate this process. The platform is designed to provide enterprises with expert-driven capability to quickly build and deploy custom AI-powered solutions. It is based on a combination of SHI’s AI & Cyber Labs services, pre-validated Nvidia AI Blueprints and HPE’s Private Cloud AI.

“Digital AI Ambassador is really transforming the customer experience,” Webb said. “If you think about any setting, whether you’re going into a retail store or you’re walking into a bank, you’re dealing with a customer service agent. It creates that human-like experience, but does it through an AI-powered avatar.”

Reliable repository for medical data

As AI use cases begin to grow, applications of the technology are extending into critical areas such as patient health. Sickbay, software used by hospitals to collect and deliver physiologic data at scale, is an example of how AI is steadily working its way into the critical centers of public life.

An offering from Medical Informatics Corp., Sickbay was developed in partnership with HPE to better manage data generated by devices hooked up to a patient. This can include vital information such as EKG tests or arterial blood pressure readings, data that can be difficult to find when needed in the hectic world of today’s hospitals.

HPE’s infrastructure feeds AI models with troves of medical data, creating a reliable repository capable of delivering more accurate results.

“This sub-second granularity of understanding of the patient’s physiology leads to greater and greater insight,” said Raajen Patel, executive vice president of innovation for Medical Informatics’ Sickbay, during a discussion with theCUBE. “The wide-scale, sort of at-scale collection and access and frictionless delivery of this data enables [researchers] to get the subset of data that they want, run the analytics that they’re interested in and find interesting things about their patient population.”

That kind of insight can lead to improvement in how medical facilities deliver care. By bringing a new standard of integrated data and monitoring to hospitals, care teams can leverage AI to improve operational processes across the patient population.

“This is a dataset, or this is a data stream that’s previously unavailable at scale,” Patel noted. “We’re seeing all these patients that have a particular physiology, or we’re seeing this particular type of patients in this geographic area, and these patients have these specific conditions, you can start looking into does our policy and practice reflect the best care that we can provide.”

Deploying smart city solutions

Along with advances in the medical field, there are signs that AI is making an impact in managing city services as well. City governments are often confronted with the challenge of modernizing infrastructure and providing more digital services while navigating disconnected systems, tight budgets and compliance demands.

HPE’s Agentic Smart City Solution is an outcome of the company’s Unleash AI Partner Program, with support from SHI, Nvidia and ProHawk Technology Group. A combination of ProHawk’s advanced AI-enabled computer vision and Nvidia’s Metropolis stack allows users to deploy low-latency solutions at the edge or on HPE’s Private Cloud AI.

“The use cases just go on and on,” said Brent Willis, co-founder and chief operating officer of ProHawk, during an interview with theCUBE. “And that’s the challenge and the benefit. It’s part of that HPE Unleashed ecosystem underpinned by HPE infrastructure and Nvidia infrastructure to make it all work in a turnkey solution.”

ProHawk’s computer vision management system includes an AI self-training element that highlights the growing flywheel effect. The company’s technology restores pixels, essentially retraining AI models to become smarter in image recognition. This also allows cities to use ProHawk without needing massive reinvestment.

“The Achilles’ heel for all of AI is quality of data; that’s the first thing we fix,” Willis said. “We restore that incoming data so that all of the other AI models and AI components are going to work and work better and work more efficiently. But, what we also do now is we have what we call the AI flywheel, so we restore that incoming video. We cycle back again every three milliseconds and teach the models and teach the sensors and learn the model such that we can do all of the identification.”

AppDev teams think holistically

Companies such as ProHawk and Medical Informatics are working with HPE and SHI to create a tighter coupling between infrastructure decisions and how applications are designed and delivered. This is reshaping the application development or AppDev approach to delivering enterprise outcomes in today’s IT world.

“With HPE’s focus on hybrid cloud, GreenLake, and platform-led services, combined with SHI’s integration and sourcing strengths, AppDev teams are thinking more holistically about portability (our research shows this as 20% of respondents view this as critical), scalability and lifecycle management from day one,” said Paul Nashawaty, principal analyst at theCUBE Research. “This can be a positive change, but it does require closer collaboration between AppDev, platform and infra teams than we’ve traditionally had.”

Nashawaty also noted that there’s an opportunity to accelerate development and operations and platform engineering practices on the delivery side. If AppDev is brought into the conversation early and treated as a design partner, more than just a consumer of platforms, HPE and SHI can help improve speed, reliability and alignment with business goals.

“If leveraged well, HPE/SHI can help provide more self-service capabilities, consistent environments and better integration with CI/CD pipelines,” according to Nashawaty. “That said, AppDev teams will need time and enablement to adapt, especially if they’re moving from bespoke setups to more standardized platforms.”

Behind the partnerships established by HPE and SHI is a central goal: Create an easy way for customers to move from AI experiments to tangible outcomes. Use cases are just the first wave of what will likely become an established process for customers to build and deploy AI applications rapidly and safely on reliable infrastructure.

“The goal is to make generative AI adoption repeatable and predictable,” said Fidelma Russo, HPE’s chief technology officer and general manager of hybrid cloud. “With curated use cases and tested frameworks, we’re taking the guesswork out of AI.”

(* Disclosure: TheCUBE is a paid media partner for the SHI Fall Summit. Neither HPE, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or News.)

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