Monthly Archives: May 2022

Strategic hires to extend company momentum and drive digital transformation in enterprise networks

SACRAMENTO, Calif., May 19, 2022 /PRNewswire/ --Gluware, the leader in intelligent network automation, today announced two new hires to company leadership: Traci Soward, as chief marketing officer, and John Alves, as chief financial officer. Amid a period of tremendous growth, Alves and Soward are key to furthering Gluware's expansion into new markets, addressing demand to de-risk complex networks, and accelerating enterprise hyperautomation and digital transformation strategies.

"The network is the platform for business growth, innovation and transformation. Enterprises are under constant pressure to keep complex networks secure and running optimally while simultaneously reducing OPEX, increasing scale and accelerating time-to-value. The industry needs pre-built intelligent automation and orchestration solutions that deliver these outcomes, and this is where Gluware wins. Our technology, solutions and NetDevOps capabilities are world-class, and our customers are our biggest advocates," said Traci Soward, chief marketing officer, Gluware. "Driving business growth and maintaining customer loyalty are key priorities. Gluware is building off serious momentum generated over the past year and is taking bold, calculated steps to meet the opportunities ahead."

Joining Gluware as Chief Marketing Officer, Soward will strengthen Gluware's brand as the leader in network automation and orchestration and share Gluware-led digital transformation strategies with new clients, industries and regions. She is a seasoned and award-winning marketing and business development executive with over 25 years of success in driving breakaway growth throughout the technology industry. Soward has held numerous key leadership positions with global industry leaders, such as Cisco, WebEx and Intel. She has pioneered new revenue models, invented partner programs that dramatically expanded addressable markets, and created marketing capabilities that achieved record-breaking results in revenue, adoption and retention.

"I am excited to join the Gluware team at such an exciting moment for both the business and the industry. Gluware offers a compelling suite of intelligent network automation applications and solutions, which run on a best-in-class, mission-critical and commercial-ready technology platform. With a highly experienced management team and an exceptional growth path, Gluware is primed to lead enterprise network automation and orchestration into a whole new era," said John Alves, chief financial officer, Gluware. "I believe the company is on the launch pad, well-positioned and sufficiently capitalized for hyper-growth and large-scale success."

As Chief Financial Officer, Alves will oversee Gluware's financial growth, including the $43 million in funding Gluware secured in October 2021 to accelerate the company's growth and increase the adoption of innovations that enhance network agility, security and performance at scale. Alves is an experienced CFO with over 25 years of finance and operational strategy experience serving both private and public companies. Prior to joining Gluware, he was a fractional CFO focused on advising and leading early-stage technology companies through periods of hyper-growth. Alves is a CPA with both B.S. and M.B.A. degrees in finance and accounting from California State University, East Bay.

Soward and Alves will join a quickly growing leadership team. In January, Gluware welcomed Ernest Lefner as chief product officer, Stanislav Miskovic as vice president of Artificial Intelligence, and Tim Silverline as vice president of Security. In February, Gluware added Jaime Wagner as vice president of Sales, North America, Colin Henry as vice president of Channel Sales, and Julie Keith as senior director of Customer Support. Gluware has experienced explosive growth recently as a result of its ease of use and ability to deliver rapid time to value by accelerating the adoption of strategic network automation efforts.

Enterprise networks are highly complex, riddled with large and sensitive attack surfaces and security vulnerabilities, and too often rely on manual processes executed by over-worked human beings. These complexities lead to risky misconfigurations, operational disruption, and ultimately, revenue loss. These problems are compounded by network growth and technological change. In the face of these complex challenges, Gluware's intelligent network automation simplifies how networks are discovered, analyzed, updated and maintained. The Gluware Intelligent Network Automation suite accelerates network automation with a commercial-off-the-shelf platform that offers no-code/low-code development with built-in applications for security and compliance. Gluware eliminates customers' need to develop software or retrain IT staff. Committed to improving and innovating suite offerings, Gluware recently released a Network Robotic Process Automation (RPA) solution and is building toward self-operating functionality and visualization features in the near term.

For more information on Gluware and the latest innovations in the Gluware Intelligent Network Automation suite, please visit http://www.gluware.com.

About GluwareGluware is the leading intelligent network automation suite for the cloud era, trusted by Global 2000 enterprises, across industries, from Pharma to Finance. Gluware automates the networks of the world's largest and most complex enterprises by simplifying how multi-domain enterprise networks are discovered, analyzed, and maintained. The company's code-free, intent-based approach to network automation reduces the business risk of unplanned outages and downtime while elevating the performance of people and systems.

Contact Dex Polizzi Lumina Communications for Gluware [emailprotected]

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Gluware Adds New Financial and Marketing Executives as Company Scales Leadership in Intelligent Network Automation - PR Newswire

Automation. Robotics. The pivot to contactless engagements. In foodservice, after the disruption of the last two years, and now with prices on the rise and labor challenged, leaning in to these seems to make senseuntil remembering that foodservice is part of the hospitality industry.

The cornerstone of hospitality is the warm, friendly interaction between people that results in a pleasant experience. In the case of foodservice, that interaction is between staff and patrons and is generally labeled as customer service. Its something operators and consumers have embraced for decades upon decades. At least until 2020, that is, when the foodservice industry came to screeching halt and human contact was taboo.

This pause in business as usual turned hospitality on its head. In a quest to find a profitable path forward, many operators began reducing and nearly eliminating staff and, as a matter of course, that human touch. Consumers began embracing the speed and efficiency of meal delivery and take out and the near risk-free dining experiences they offer.

Though born out of necessity, the big question now is whether or not this Jetson-like world can, will or should last. Georgia-Pacifics GP PRO sought answers by conducting proprietary research among consumers and foodservice workers. The responses provide compelling learnings for operators looking to not only survive the pandemic but to evolve and pivot in order to succeed.

Find the Sweet Spot

Every person has a different appreciation for and acceptance of technology, and it comes as no surprise that age is a defining factor. GP PROs research found that the majority (53 percent) of the Silent Generation and nearly half (48 percent) of Baby Boomers welcome some attention when dining out by way of engaging but non-disruptive customer service; and roughly one-third of Gen Xers (31 percent), Millennials (32 percent) and Gen Zers (31 percent) prefer to engage with staff only as needed. Only slightly fewer Gen Zers (27 percent) consider themselves DIY diners who want a completely self-service dining experience from start to finish.

Across all age demographics combined, 34 percent of diners welcome staff attention, 25 percent want someone available if needed, 22 percent appreciate small talk with staff, 11 percent want complete independence, and 8 percent seek engaging conversation with staff.

Invest Where it Matters to Consumers

Its pretty rare for operators to actually seek insights from consumers on where investments are needed to improve the establishments overall business. Some might argue that these insights arent needed because the answer lies in technology. Theres certainly some truth in that. But what kind of technology in particular? Margins are thin, perhaps more so now than ever before, so giving consumers a voice and then investing in what they see as most important is critical to helping secure repeat business, build loyalty, and secure brand advocacy.

When asked to pick two areas of investment for operators to focus on, 42 percent of consumers said order accuracy, 36 percent said speed of service, and 29 percent said face-to-face customer service. Only 10 percent of consumers want to see operators invest in app development for mobile ordering, and just 6 percent in automation to minimize contact with employees.

Invest Where it Matters to Employees

Its been said repeatedly that the last two years have been among the most trying two years ever for the foodservice industry. Closure mandates, mask mandates, supply chain issues, inflation, food shortages, and the list goes on. Emotions are up, and revenue is down.

But dont forget that foodservice workers have been on this rollercoaster, too. Most lost their jobs through no fault of their own for at least some part of the pandemic. Many couldnt return when the opportunity presented itself, others wouldnt, and some came back only to leave soon after.

Its easy to point the finger at what some might call fickle hourly employees. But GP PROs research shows that foodservice workers who were employed for some or all of the past two years believe there is a way throughvia higher wages (62 percent), stronger leadership (42 percent), and being valued by management (40 percent). Even without those investments, 83 percent of foodservice workers said they are very or somewhat likely to continue working in the industry. Why? For more than half of them (56 percent, they enjoy interacting with customers.

Cindy Egnarski owns a Figaro Pizza and Cousins Subs in Pulaski, Wisconsin. With 18 years of experience in the foodservice industry, she believes these research findings are on the mark. The best part of working in foodservice is creating a great experience for my staff and my customers, and great experiences are generally built on human relations. Automation that empowers that kind of interaction and that enhances the experience for staff and patrons is the kind of automation I find most valuable.

Human connection. Hospitality. Technology. If the research is any indicator, the delicate balance may just lie in automation that improves operational efficiency and supports an enhanced experience for consumers and staff alike.

Alec Frisch is vice president and general manager of Foodservice with GP PRO, a division of Georgia-Pacific. GP PRO and its Dixie brand solutions are helping operators innovate and build business with touchless dispensing systems and foodservice disposables that empower productivity and hygiene. Contact Alec at Alec.Frisch@gapac.com.

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Automation, Hospitality, and Employee Retention: It's All About Balance - QSR magazine

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Automation in the Age of IT-OT ConvergenceCompanies are constantly looking for better ways to augment their existing operational workloads, optimize production processes, and reduce overall Carbon Dioxide (CO2) emissions. The use of Operational Technology (OT) and Information Technology (IT) has helped enterprises better control their operations by monitoring valuable assets, reducing repetitive and routine tasks, and enhancing quality control. However, IT and OT have been traditionally developed separately with no ability to exploit operations and production data to make more informed decisions for more optimized workflow and well-planned production and maintenance processes.

The emergence of the Internet of Things (IoT) in recent years blurs the boundaries between the two systems, leading to a more convergent solution. IoT devices belonging to the IT domain can collect operational and production data from the field and communicate them to the OT systems.

The convergence of IT and OT will allow workers to do more and go further with their improvements, striking the right balance between the cost of business and strategic technology investment. Furthermore, this convergence will enable enterprises to accelerate their digital transformation and optimize their existing workflows, all without needing to scale up rapidly.

Graphics Processing Units (GPUs) have proven ideal for executing the data processing based on Machine Learning (ML) algorithms, allowing robots to perform object recognition and sensor fusion. Further advances have come from developing Application-Specific Integrated Circuit (ASIC) that excel in specific ML applications, such as video processing and speech recognition.

Robotics AutomationOne of the technologies that best represent IT-OT convergence is operations management through robotics automation. With automated processes, companies can analyze data, obtain valuable insights, and gain improved visibility of their production sites performance, helping them make data-driven decisions. However, robotics development has traditionally been very complex and challenging. As demand for robots is expected to increase rapidly, the current rate of innovation can be accelerated with the proper hardware and software offerings.

The Rise of RoboticsIn general, the deployment of robots has led these devices to host new functions aiming to increase workforce safety, reduce strenuous and hazardous tasks for human employees, accelerate e-commerce fulfillment and delivery, and enhance business flexibility and resilience. These new functions require the implementation of high-accuracy sensors that fulfill functional safety and risk prevention requirements, cameras for detection, localization, and navigation, and robotics middleware for application onboarding. In recent years, key advancements in robotics hardware allow robotics Original Equipment Manufacturers (OEMs) to develop robots that can see and sense their environments:

At the same time, advancements in software and services also deserve much attention:

Through these key advancements, robots can now work alongside a human safely and reliably. Apart from industrial robotics arms, more form factors have emerged in recent years, such as Collaborative Robots (cobots), AGVs, AMRs, Automated Storage and Retrieval Systems (ASRS), and Unmanned Aerial Vehicles (UAVs).

A common denominator across all these robots is their ability to perceive and make sense of their surrounding environment. This autonomy is enabled through several ML models found in the robots, such as object detection and segmentation, localization and collision avoidance, motion planning for navigation and manipulation, pose estimation, and sensor integration.

Edge ML enables robotics users to make sense of the mountain of data they collect from their assets and make much better business decisions based on daily operation, usage trends, and customer behaviors.

Edge ML in RoboticsRobotics OEMs have embedded edge ML into their robots to help with performing critical functions, including sensor processing, odometry, localization and mapping, vision and perception, and path planning. These ML models hosted inside robots automatically process data collected by the robots and generate an output that dictates the robots actions. Edge ML holds several key advantages over its cloud counterpart:

Edge ML enables robotics users to make sense of the mountain of data they collect from their assets and make much better business decisions based on daily operation, usage trends, and customer behaviors. To achieve seamless edge ML deployment, robotics OEMs require the right type of processors to resolve concerns around data privacy, power efficiency, and low latency, while providing strong on-device computing performance. In addition, OEMs rely on edge ML software support from these processor suppliers to accelerate edge ML deployment. A comprehensive edge ML solution from established vendors can reduce complexity, and accelerate edge ML design and operations, while also providing workload orchestration, training and testing simulation, and model retraining support.

That said, edge ML deployment in robots remains complex. Higher computational capability alone is not sufficient. Companies need pre-trained models, application development and optimization, and ML applications for more hands-on end users.

Tools and Services Speeding Robotics DevelopmentAdvanced industrial robotics are packed with multiple features capable of executing a number of mission-critical functions. The execution and the orchestration of these functions require highly sophisticated, densified, and scalable processing solutions that can process multiple concurrent applications, workloads, and AI inference pipelines without the constant reliance on cloud computing resources. These solutions should also support high-speed interfaces to handle the multiple sensors featured in modern industrial robots.

NVIDIA is one of the key processor platform suppliers to dedicate particular attention to this area. At GTC 2022, NVIDIA launched the Jetson AGX Orin developer kit and System-on-Module (SOM) based on the Ampere GPU architecture with up to 2,048 parallel CUDA cores, up to 64 Tensor Cores, and up to 2 Deep Learning Accelerator (DLA) engines. This solution is designed to handle the ever-increasing workload and multi-concurrency demands by enabling up to 275 Tera Operations per Second (TOPS) of processing power, 8X higher than Jetson AGX Xavier, its predecessor.

To accelerate time-to-market, NVIDIA also offers Isaac Nova Orin, which features two Jetson AGX Orin SOMs that provide up to 550 TOPS of AI compute, and a sensor suite consisting of up to six cameras, three LiDAR sensors, and eight ultrasonic sensors. This provides a reference design for companies that want their robots to leverage the full capabilities of Jetson AGX Orin.

That said, edge ML deployment in robots remains complex. Higher computational capability alone is not sufficient. Companies need pre-trained models, application development and optimization, and ML applications for more hands-on end users. First launched in 2018, NVIDIA Isaac was designed to support robotics development through an application framework, software packages with ML algorithms, an upgraded robotics simulation platform, and various reference designs. In September 2021, NVIDIA and Open Robotics, the developer of ROS, entered into an agreement enabling interoperability between Open Robotics Ignition Gazebo and NVIDIA Isaac Sim. In addition, for developers that look at existing models to simplify their model development process, the NVIDIA TAO Transfer Learning Toolkit makes it easier for them to further adapt pre-trained ML models by NVIDIA for specific use cases.

With the software support from NVIDIA, robotics OEMs and end users train and optimize robots for a breadth of tasks virtually. Isaac Sim provides a realistic environment to train navigation and manipulation models. In the cases where real-world data are rare and hard to obtain, accurate data can be augmented with synthetic data to reduce the time for model training. Companies operating a large fleet of AMRs at production sites can use the NVIDIA DeepMap platforms cloud-based Software Development Kit (SDK) to speed robot mapping of extensive facilities from weeks to days, NVIDIA cuOpt Application Programming Interface (API) to enable near real-time routing optimizations, and NVIDIA Metropolis platform to integrate off-the-shelf video cameras and sensors with AI-enabled video analytics.

In addition, NVIDIA has built a growing ecosystem that possesses domain expertise in building robots with the Jetson platform. This includes 105 companies specializing in AI software, hardware and application design services, sensors and peripherals, developer tools, development systems, and more, providing complementary and value-added solutions and services. Leading partners include SICK, LIPS, FRAMOS, Universal Robots, and e-con Systems. Through this ecosystem, robotics OEMs and end users can expect end-to-end, integrated, and tailored experiences based on a deep understanding of their needs.

The intralogistics market for mobile robots is expected to grow from US$9 billion in 2022 to top US$36 billion by 2030. Both AGVs and AMRs are deployed in brownfield and greenfield warehouses for material handling.

Commercial Opportunities AboundWhile still heavily centralized in the industry, technological innovations across hardware, software, and business models accelerate robotic deployment across all major market verticals. As a result, the intralogistics market for mobile robots is expected to grow from US$9 billion in 2022 to top US$36 billion by 2030. Both AGVs and AMRs are deployed in brownfield and greenfield warehouses for material handling.

Now, AMRs and forklifts are used for material handling and mobile manipulation in manufacturing, which is expected to go from US$2.3 billion in 2022 to US$36.4 billion by 2030. Moving forward, AMRs and quadruped robots are expected to become more prominent in delivery, data collection, security, and cleaning. The last-mile delivery and retail robotics market are expected to grow from less than US$1 billion and US$1.3 billion in 2022 to US$16.2 billion and US$8.4 billion by 2030, respectively.

Robotics and MLAs companies continue to digitalize and automate their current workflows, they should not overlook the importance of robotics and ML-based automation. The emergence of a data-driven business environment, edge ML technologies, dedicated robotics development platform, and robust partner ecosystem is creating new opportunities for accepting and adopting robots across various markets.

Undoubtedly, current and immediate robotics adoption is heavily weighted toward larger companies. Still, emerging technologies present an opportunity for robotics providers to successfully lower the adoption barrier for small and medium businesses. A comprehensive hardware and software solution, like the one offered by NVIDIA, makes these technologies more accessible to both robotics OEMs and end users. Furthermore, partnering with an experienced company with a suitable robotics ecosystem, i.e., from the edge ML chipset layer to the software and applications layer, allows robotics OEMs to focus on perfecting their hardware design and expanding their market presence.

About the AuthorLian Jye Su, Principal Analyst at ABI Research, is responsible for orchestrating research related to robotics, Artificial Intelligence (AI), and Machine Learning (ML). He leads research in emerging and key trends in these industries, diving deeply into advancements in key components, regional dynamics in robotics and AI adoptions, and their future impacts and implications.

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