Adapdix appointed Jean Lau as its chief technology officer to head up its technology team, driving architecture, technology strategy and development of the EdgeOps platform. Before joining Adapdix, Lau was vice president and head of engineering at Hitachi Vantara’s Software Digital business unit, where she was responsible for turning a multi-million-dollar product portfolio into a software-as-a-service (SaaS) delivery model to solve Industrial IoT (IIoT) challenges.
Lau has led product management and engineering teams to transform the edge-to-cloud initiative from vision to successful customer deployment. Her success was driven by her ability to guide the product strategy, vision, go-to-market, architecture, operation model and team structure. With more than 25 years of engineering experience, Lau has developed a passion for building product and engineering teams who deliver products that enable customer success.
What are three key things that a machine builder, system integrator or manufacturer should know about your organization?
Jean Lau, chief technology officer, Adapdix: Adapdix was founded in 2015 with the vision to help enterprises to drive performance improvement through AI-enabled adaptive software. Adapdix has a growing portfolio of Fortune 500 customers, with technology that delivers AI-enabled performance optimizations for companies in the semiconductor, high-tech, assembly, discrete- and precision-manufacturing industries.
Adapdix EdgeOps is our adaptive AI software platform that accelerates digital transformation at the edge through intelligent analytics, real-time asset optimization and adaptive motion control. With EdgeOps, we help customers to improve yield and throughput, while minimizing unplanned downtime and maintenance costs.
The EdgeOps platform merges the advantages of edge computing with edge-optimized AI/ML edge inferencing, execution and control, offering three progressive tiers of value that build upon one another as we partner with enterprises to harness the power of edge data and accelerate the customer’s digital journey: split-second data virtualization and analysis with EdgeOps DataMesh; rapid, scalable deployment of intelligent models and applications; and adaptive control that enables machines to develop self-corrective and self-optimizing capabilities.
What new technologies are driving product development and why?
Jean Lau, chief technology officer, Adapdix: EdgeOps was built upon a scalable and extensible microservice, containerized architecture, combined with advanced artificial-intelligence and machine-learning technologies. With an open and modern architecture, we can easily integrate with other technologies and products already in the market, so our engineering team and customers can continuously innovate in areas like data virtualization, unsupervised learning on the edge and transfer learning between edge nodes, machines and manufacturing lines.
How does the Industrial Internet of Things figure into business strategy?
Jean Lau, chief technology officer, Adapdix: Our vision is to focus where our customers generate data—at their edge. Every customer we engage with is moving along its own distinct digital transformation journey and looking to gain performance improvements by rapidly digitalizing systems and processes. We find many customers are rich in data, but poor in actionable insights and producing tangible business outcomes. Using AI and ML to uncover, understand and generate value from the data has proven overwhelming for many companies grappling with challenges of technical complexity, high costs, slow implementation, cloud inefficiency and skilled-labor shortages. Organizations and service providers spend valuable resources building bespoke solutions that encounter technical complications, implementation delays and unplanned costs.
We believe that an edge-optimized platform overcomes these challenges, enabling customers to manage their businesses closer to where data is created in real time. In this way, IIoT is a big part of our product and strategy. Adapdix’ EdgeOps is designed and built to solve IIoT challenges. EdgeOps has become the first ultra-low-latency platform to ingest, pre-process and analyze data using advanced AI/ML and also provide control intelligence for self-correcting and self-optimizing actions.
How will machine automation and controls alter the way companies staff their operations in the future?
Jean Lau, chief technology officer, Adapdix: We believe that machine automation and control is about bringing together the best of human judgment and expertise, combined with AI-enabled software precision. This revolution will empower organizations and their staffs to do their jobs more efficiently and safely. For example, Adapdix’s EdgeOps platform uses machine learning to analyze the data collected from machines in real time and provide intelligence to machine operators and process engineers about why a machine is not operating at the expected throughput, rather than simply indicating an anomaly with an unidentified cause.
Based on those insights, operators armed with Adapdix’ EdgeOps software can confidently allow the software to make the right decision on how to improve the machine’s throughput in milliseconds, in situ to meet their production targets. With the support of our EdgeOps software that detects the failure before it happens, process engineers can also use this data to immediately optimize the machine’s operation instead of spending the time to troubleshoot or de-bug an unexpected failure.
How is the development of software solutions impacting requirements for hardware?
Jean Lau, chief technology officer, Adapdix: The evolution of software and technology will impact requirements for hardware in two areas: functionality and cost. With more data being collected and analyzed, there is a need for more processing compute, storage, and networking (5G) to run advanced machine learning algorithms at the right speed and to support more advanced applications. The hardware design needs to be more modular, like LEGO blocks, which needs to be easily scaled, down and out, based on the use case and software needs, and also within the customer’s budget requirement.
As engineering and IT continue their convergence, which one is and/or will be leading the direction of future automation and technology?
Jean Lau, chief technology officer, Adapdix: Adapdix’s EdgeOps platform is focused on solving operational challenges across a variety of industries and use cases. The EdgeOps DataMesh is built to handle the increased interconnectedness of IT and OT data streams, by stitching together and time synchronizing these previously disconnected environments. Intelligent applications can then be built to not just analyze but automate. We believe that 2022 will mark the first significant rise in IT/OT convergence at scale.
Looking into the future, how will technology change your organization or other organizations over the next five years?
Jean Lau, chief technology officer, Adapdix: A few years ago, there was a notion that edge computing was going to be a conduit and everything was going to be connected into the cloud and all the computing and processing was going to happen in the cloud. The past 18 months in particular have been a very exciting time to be in technology. We have seen edge computing come to life to help business adapt during the pandemic. In the next five years, I think edge computing will continue to grow and will adapt with technological advances such as 5G and augmented reality. A flexible product and architecture need to be ready to adapt and integrate with those new technologies and standards. We need to be flexible in our solution deployment model, with ready solutions that can be deployed on the hybrid edge, edge-to-multi-cloud and hybrid cloud. We also need to be flexible in business model, as well, since industrial applications are increasingly moving toward a SaaS model.