Often the most incredible computing breakthroughs aren't the result of one technology but the combination of several. Today, we're fortunate enough to live in a time when Edge Computing is bringing data center-level power to more locations. And AI is poised to capitalize on it, thanks to modern data management.
The scope and definition of AI are constantly changing. New use cases are being put into practice every day. For example, sensors attached to machines, facilities, and personnel feed data from modern assembly lines into AI to improve demand forecasting, monitor security and safety, and improve efficiency and quality. And that's just in manufacturing. Other AIs are used to prevent retail fraud and hasten medical discoveries. Therefore, to say the applications of AI are limitless is not an understatement.
While AI continues its exponential leaps, the computing landscape is also changing. Inspired by the demand for mobility, Edge Computing has grown steadily in importance over the last few years. No longer is the Edge only about improving access to in-office systems. Instead, changing where processing takes place is changing what is possible. Here are some industries that are creating value at the Edge:
Automotive - Edge devices enable autonomous navigation, traffic and parking management, and taxi services.
Energy - Edge Computing brings demand forecasting, smart grids, and smarter rig operation to the marketplace, from the farthest remote oil rigs to the densest power grids.
Retail - Thanks to Edge servers, retailers can better manage inventory, prevent theft, manage store traffic, and improve the point-of-sale experience.
Healthcare - Edge technology supports better medical decision-making and care delivery in conjunction with diagnostic, surgical, and telehealth equipment.
Construction - By leveraging Edge Computing, builders can adjust to changing weather conditions, manage projects, machinery, and people, and ensure build quality.
Financial Services -The Edge is responsible for bringing banking to your car window with a growing list of ATM services. At the same time, it enables safer mobile payments and retail transactions with real-time fraud detection.
Edge Computing provides the power for AI to prosper in more places and situations than ever. Moreover, in every above example of Edge Computing, AI can enhance service offerings. Therefore, the two technologies are working hand-in-hand to provide better user and customer experiences than ever.
The growth of data sources like sensors and mobile devices has created an unprecedented opportunity for AI, which thrives on large, rich datasets to generate valuable business insights. According to IDC, 175 Zettabytes of data will be generated worldwide by 2025, with 30% processed in real-time. At the same time, Gartner predicted that more than 50% of enterprise-generated data would be created and processed outside the data center or cloud.
Instead of a single destination, Dell Technologies sees data management as a journey every organization embarks on. They describe it in the following steps:
- **Identify Business Need** - Understanding what challenges can be solved with better data.
- **Accelerate Relevant Discovery** - Connect value creation and its relevant data sources.
- **Simplify Data Exploration and Access** - Standardize your organization's methods for accessing the correct data.
- **Optimize Analytics and ML Experimentation and Modeling** - Develop better ML models with accelerated experimentation.
- **Scale Data and Analytics Productization** - Building a production environment and process for data intake to decrease time-to-insights.
- **Automate Data Management and Governance** - Create systems to generate a high-level view of data and performance.
- **Evaluate Business Outcomes** - Empower the organization and its customers with new value derived from data management.
- **Essential Questions** - Evaluate the success of the organization's data management initiatives and set new goals for future iterations.
While many organizations have no shortage of data, not all have it in a form that is immediately usable for insights. Data management makes it possible to get to the right data at scale, which makes decision-making easier. At the same time, the ubiquitous, better-tuned architecture enables the consistent running of workloads across multiple platforms. Finally, with better data being processed more widely and consistently, data scientists and analysts can receive and respond faster to insights, which leads to better business results.
As mentioned, Edge Computing offers organizations a platform for better data management and accelerated AI insights. It's a way to reap the benefits of better data at a larger scale than ever. And with the right integration partner, it's easy to get started.
Look to UNICOM Engineering to provide your Edge Computing, AI, and systems integration expertise. As an Intel Technology Provider and Dell Technologies OEM Partner, they can supply, build, and support the best hardware to meet or exceed the needs of your application and help you bring it to market faster. Schedule a consultation today to learn how UNICOM Engineering can keep you progressing on your AI journey.