NTT DATA, the global systems integrator division of Japan’s NTT Group, has announced a new edge AI platform that “integrates and synthesizes” data from sensors, devices and systems across an enterprise and feeds it into task-specific industrial AI models. This is offered as a managed service alongside a broader enterprise edge portfolio consisting of edge-based sensing (IoT), computing, connectivity (private 5G) and devices. It is pitched to the Industry 4.0 market as the leading AI platform for combining and leveraging IT/OT data on new fast and reliable edge infrastructure.
The London-based company suggested that industrial edge environments are not the right place for trendy generative AI applications. “While there has been a lot of attention on generative AI and large-scale language models, these technologies are not practical for industries that require real-time, local decision-making,” it said in a statement. In contrast, the company seems to argue that domain-specific industrial machine learning (ML) applications can be tailored to deliver “mission-critical” insights and decisions using new on-premise private edge 5G and private edge computing architectures that NTT Data also offers.
Meanwhile, the continued deployment of various kinds of IoT sensing devices in factories and plants is bringing new industrial telematics measures and also creating ways to connect traditional OT machines, enabling ML-based AI applications to work with more data in more applications. NTT DATA states, “By processing data when and where it is generated, and integrating various IoT devices, systems and data, the solution enables real-time decision-making, improved operational efficiency and secure deployment of AI applications across industries, advancing advanced Industry 4.0 technologies.”
But ring-fenced edge systems don’t consume the same (remote) computing power as cloud-based computing engines, and are employed in part to avoid data transfers and decision-making having to happen in both directions between far-flung data centers. Instead, local data processing at the edge must be efficient and optimized. “We provide real-time AI insights using smaller, more efficient ML models on a compact computing platform,” NTT Data said. The company’s new platform handles data discovery, collection, integration, computation, connectivity and AI model management.
It explains:[The platform] Addressing Shadow IoT challenges and AI infrastructure requirements… by automatically discovering, integrating and processing data from IoT devices and IT assets. [an] Organization, [and] Simplify AI deployment and management… [It] Leverage lighter, more cost-effective AI models and run them in a small computing box. [It] They perform specific tasks such as supporting safety and operational efficiency by collecting data from various devices across your network environment. [to enable fast] It enables secure data processing and analysis.”
This software is “auto-detect” [enterprise] assets [a] NTT DATA has proposed several AI use case scenarios for predictive machine maintenance and energy usage optimization. The platform will be offered with a managed edge bundle to provide businesses with IoT-related technologies as a service along with a managed support team.
The company also offers businesses a free 30-day “discovery and diagnosis” assessment of their IT and OT environments. NTT Data said its consulting business has “1,000 industry experts, hundreds of use cases, and more than 500 sales professionals.” The company cited analyst firm IDC’s forecast that global spending on edge computing will reach $232 billion in 2024, up 15% from 2023. “Due to the growing number of connected IoT devices worldwide, it is expected to exceed 41 billion by 2025,” the company said.
“Our Edge AI platform represents a major leap forward in securely and cost-effectively powering AI at the edge,” said Shahid Ahmed, group executive vice president, Edge Services, NTT DATA. “By harmonizing data from a variety of sensors and devices with lightweight AI models to power a full range of automation use cases, [it] is pioneering the adoption of Industrial AI as the industry’s first fully managed service, helping organizations modernize with customized, industry-specific solutions.”
Alejandro Cadenas, vice president, Telecom Mobility and IoT Research, IDC Europe, said: “A key challenge for enterprises is to securely and reliably collect, aggregate and turn operational data into actionable insights across a fragmented environment of devices, platforms and data sources. NTT DATA’s ultra-lightweight Edge AI addresses these issues, simplifying the rollout and adoption of data-driven enterprise strategies, reducing risk and timelines, and optimizing total cost of ownership and value for enterprises.”
“AI is a game changer,” said Pablo Tomasi, principal analyst for private networks at Omdia. [it creates] “The data that is most valuable to an enterprise is often where it is generated. By ingesting IT/OT data and leveraging AI to produce use-case specific results, NTT DATA’s solution takes it another step towards realizing the Industry 4.0 vision. Additionally, the use of small, task-specific AI models makes it easier for enterprises to deploy AI where and when it is needed, without having to massively overhaul their entire infrastructure, helping to drive the democratization of AI.”