by Gary Mintchell | Aug 22, 2022 | Commentary, News, Software, Technology
In Q2, VC investment in AI fell by 44%, while overall funding fell by 25%.
One of my few trusted news sites is Morning Brew newsletter and its companion Emerging Tech Brew.
Writer Hayden Field recently posted an article looking at venture investment in Artificial Intelligence. My inbox has swelled with AI this and AI that for some time now. Marketers evidently feel this is a magic word to drive sales while showing the world their company is cool with the latest tech. Of course, Artificial Intelligence (often called neither artificial or intelligent) has been around for decades. Much of the manufacturing software you’ve used for years has AI embedded. So, I’m not surprised at this.
Total VC deal count worldwide has maintained momentum from last year’s record highs, but so far in 2022, “deal value has declined rather significantly across all stages,” according to a PitchBook report—and AI funding in particular is falling faster than the market.
By the numbers:
In Q2 2022, global AI funding plummeted by more than 44% year over year, from $33.6 billion to $18.8 billion, per Pitchbook data shared with Emerging Tech Brew. Over the same period, overall global VC funding fell by 25%, from $176 billion to $131.7 billion. On a quarterly basis, global VC funding for AI and machine learning was down more than 26% between Q2 and Q1, a slightly larger margin than the 20% drop for global VC as a whole.
Same old tech story, how to turn hype to profits.
For years, many VCs believed AI companies would figure out the path to profitability down the road, Shahin Farshchi, a partner at Lux Capital, told us. Today, investors want to see founders give more thought to how, exactly, they’ll build a sustainable business model around AI.
by Gary Mintchell | Aug 18, 2022 | Cloud, Edge, Enterprise IT, Manufacturing IT, Open Source, Operations Management, Software
Much as some of its large industrial competitors, ABB is quickly building out industrial software solutions. A friend who is a financial analyst told me that Wall Street and other investors prize software right now. A company focused on instrumentation and automation platforms doesn’t evoke the same eyes full of longing and desire as when they add software.
In this announcement, ABB and Red Hat, the open source enterprise software company, are partnering to deliver ABB automation and industrial software solutions at the intersection of information technology (IT) and operational technology (OT), equipping the industrial ecosystem with extended deployment capabilities and greater agility. This is consistent with ABB’s vision of the evolution of process automation.
- ABB will deliver digital solutions to customers on-demand and at scale using Red HatOpenShift
- Customers will be better able to harness the potential of data-based decisions by using applications that can be deployed flexibly from the edge to the cloud
The partnership enables virtualization and containerization of automation software with Red Hat OpenShift to provide advanced flexibility in hardware deployment, optimized according to application needs. It also provides efficient system orchestration, enabling real-time, data-based decision making at the edge and further processing in the cloud.
Red Hat OpenShift, the industry’s leading enterprise Kubernetes platform, with Red Hat Enterprise Linux as its foundation, provides ABB with a single consistent application platform, from small single node systems to scaled-out hyperconverged clusters at the industrial edge, which simplifies development and management efforts for ABB’s customers.
“This exciting partnership with Red Hat demonstrates ABB’s commitment to meet customer needs by seeking alliances with other innovative market leaders,” said Bernhard Eschermann, Chief Technology Officer, ABB Process Automation. “The alliance with Red Hat will see ABB continue helping our customers improve their operations as they navigate a rapidly evolving digital landscape. It will give them access to the tools they need to integrate plantwide IT and OT, while reducing risks and optimizing performance.”
Red Hat OpenShift increases the deployment flexibility and scalability of ABB Ability Edgenius, a comprehensive edge platform for industrial software applications, together with ABB Ability Genix Industrial Analytics and AI Suite, an enterprise-grade platform and applications suite that leverages industrial AI to drive Industry 4.0 digital business outcomes for customers. ABB’s Edgenius and Genix can both be scaled seamlessly and securely across multiple deployments. With this partnership, ABB will have access to capabilities like zero-touch provisioning (remote configuration of networks) which can increase manageability and consistency across plant environments.
“Red Hat is excited to work with ABB to bring operational and information technology closer together to form the industrial edge. Together, we intend to streamline the transition from automated to autonomous operations and address current and future manufacturing needs using open-source technologies,” said Matt Hicks, executive vice president, Products and Technologies, Red Hat. “As we work to break down barriers between IT and the plant level, we look to drive limitless innovation and mark a paradigm shift in operational technology based on open source.”
by Gary Mintchell | Jul 19, 2022 | Cloud, Manufacturing IT, Operations Management, Software
Current trends in software product management mandate new platforms to bring disparate applications together into some semblance of coherence. A few years back the term was “breaking down silos.” That term continues to pop up at times. As well as collaboration and cross-functional.
If any readers of this blog including the tens of thousands in Europe and Asia are still struggling with silos or figuring out how to get people to work together, you’re behind. Get with it. Astute managers have figured out how to get IT and OT to work together for several years.
I say this as context for another reason companies construct these platforms—acquisitions. Hexagon has filled its shopping cart recently with many companies. It is now up to management to find a way to bring coherence to the portfolio. Hexagon’s solution introduced at it’s user conference in Las Vegas in June is dubbed Nexus.
• The platform will connect people, technology, and data across the design, production and manufacturing workflow
• It will empower cross-functional teams with the insights to collaborate instinctively in real time
• Cloud-based technologies, applications, and solutions accelerate new product development
I think cloud-based is the key. Open APIs and cloud technologies such as modern databases enable a new generation of software solutions for customers.
Hexagon’s Manufacturing Intelligence division has announced an open platform for smart manufacturing, Nexus, which will revolutionise how technology professionals collaborate and innovate.
Nexus is the foundation for Hexagon’s new solution offerings in the smart manufacturing space going forward. Today, it is capable of leveraging Hexagon data sources from across the portfolio. Visualisations and data management solutions such as HxGN Metrology Reporting and MaterialCenter have been built as cloud-native connected applications, and will be connected through Nexus.
by Gary Mintchell | Jul 8, 2022 | Manufacturing IT, Operations Management, Software
Many software companies I follow have switched from an annual huge update to a series of updates released when they are ready. Inductive Automation had released version 8.1.17 not long ago. Here we have version 8.1.18. Ignition 8.1.18 brings significant improvements to scripting in the designer, feature updates to the Perspective Module, and other improvements.
For many users, scripting is a big part of the Ignition platform. With the help of some key feedback from the Ignition community, Ignition 8.1.18 delivers significant improvements to the scripting editor. In fact, the Script Editing component has been completely replaced. The updated editor is smarter and more aware of DPI scaling, and it comes with some quality-of-life improvements.
First up is an inline find-and-replace feature when you press Ctrl+F (Cmd+F for MacOS). As a bonus, there are new data match options to refine your search even further. You can also use Ctrl+R to replace specific text, or Ctrl+G to jump to a particular line.
Two additional quality-of-life features are code folding and visible whitespace. Code folding gives you the ability to collapse class and function bodies in the editor, which helps you to focus on certain sections of code. Visible whitespace is particularly useful for Python. In Python, the use of indents has great significance as it defines blocks of code but keeping track of indentation within a script can sometimes be difficult. With 8.1.18, you can show whitespace by including an arrow that represents the indent, making confusing indentation errors a thing of the past.
In 8.1.18, variable and parameter types now have type (as in, datatype) awareness. In various contexts, such as extension functions, parameter types are suggested and inserted automatically. For example, in a script transform, when you type quality, the new feature is aware of the parameter type and displays methods and properties related to QualityCode.
As always, Perspective receives some fresh new updates. Perspective is getting a new container component called the Split Container. This new container is ideal for data-dense screens. As the name suggests, the container is split into two sections divided by a user-adjustable slider. The container can be oriented either horizontally or vertically, and items in either section of the container can be resized depending on the placement of the slider.
by Gary Mintchell | Jul 5, 2022 | Data Management, Manufacturing IT, Operations Management, Software
I’ve felt DataOps was destined to be an important data management tool since I was introduced to it a few years back. Hitachi Vantara is one of two companies I follow specifically bringing this technology to industrial applications. Here it introduces a new portfolio bringing IIoT specifically into the core working with digital twins, machine learning (ML), and user interface.
Background. Ultimately, most industrial IoT difficulties are rooted in data management shortcomings. However, these challenges are not the same as those faced in a purely IT setting. For example, operational technology (OT) data is high-velocity time series and event information that many times lacks the detailed metadata descriptors and features needed to leverage it outside of the operations organization. In comparison, business IT data comes across in batches or transaction records with different metadata descriptors where time-stamp references are not always correlated. Merging these datasets, in context, is not trivial work, but, if done right, yields new operational insights that can provide a competitive advantage.
Lumada Industrial DataOps automates the process of abstracting, tagging, and rationalizing IT and OT data and organizes it in the data lake or data warehouse so it is usable for analysis and building AI and ML solutions. Data pipelines are established, and multiple transformations and inferences can be calculated and orchestrated as part of the workflow. Industrial process engineers can work with data scientists, analysts, and applications consultants to unlock the combined value and make major operations improvements.
But reality hasn’t lived up to the promise, and industrial operations have had a mixed relationship with IoT technologies. While there has been considerable success at the project level, broad IIoT deployments and the resulting analytics capabilities have progressed in fits and starts. Enterprises will need to leverage IIoT as well as AI and ML technology across far more use cases to better support their existing workforce and overcome supply chain issues. It turns out that it is more complicated than developers anticipated to scale their IIoT proofs of concept to stretch across a company.
The Lumada Industrial DataOps portfolio adds IIoT Core software with IIoT platform framework capabilities. The new toolkit is delivered as IIoT Analytics to accelerate the convergence of traditional IT with expanding IIoT data sources and bring powerful new software-based capabilities to life. IIoT Analytics offers prepackaged modules that provide data integration and preconfigured functions that give you a faster start on your application so you can focus on fine-tuning it for your specific requirements. A typical IIoT Analytics toolkit includes:
- Digital twins for data and asset organization
- ML models for faster assembly
- Simulation software interfaces for greater accuracy
- ML services framework for deploying AI/ML applications
Lumada Industrial DataOps directly addresses the four key challenges that hinder the enterprise-wide expansion of IIoT applications.
Challenge 1: The Need for High-Level Data Management Organizations need solutions that make it possible to access data in motion and at rest from the widest array of sources, integrate all that data, transform the data, and perform analysis. While all that happens, data security must be maintained and policies enforced to adhere to compliance and governance requirements.
Challenge 2: Automating Data Organization To create an efficient production pipeline for AI models, data scientists and analysts need an environment within which they can organize data and build models to detect events. This requires a system that automates the data analysis function, rejecting noise and providing people with a rich data signal that can be predictive or prescriptive in context.
Challenge 3: Accelerate the Training of AI Models Starting every model from scratch is not practical, as this approach may introduce delays and costs that get in the way of meeting business objectives. Data science personnel instead need templates that provide a proven foundation that they can then refine and adapt to meet specific requirements in a timely manner.
Challenge 4: Shorten Application Delivery Time Engineers and developers also need ready-made application components that provide a starting point.
Using Lumada Industrial DataOps, organizations can accelerate their development of digital twins, which can be further combined with new AI and ML analytic templates that address a variety of critical industrial activities. These analytics include anomaly detection and prediction capabilities for maintenance and operations effectiveness. These data management and application building blocks support the many industry-specific solutions offered by Hitachi to speed cooperative deployment efforts for Hitachi clients and partner organizations.
Lumada Industrial DataOps embraces the synergistic srelationships between data management, AI applications, and the next-level decision-making required in modern industrial environments. With Lumada Industrial DataOps, Hitachi empowers industrial enterprises to move their IIoT-driven AI applications out of the endless pilot phase and more quickly develop and scale for enterprise-wide deployment.
by Gary Mintchell | Jul 1, 2022 | Manufacturing IT, News, Operations Management, Software
Even though Siemens PR seems to have lost track of me, several invitations to a big event crowded both business and personal inboxes. These were teasers for a two-hour presentation via the Web where CEO Roland Busch and other executives, partners, and customers introduced a platform and products under the banner of Siemens Xcelerator.
They began with “open”, and I thought “here we go again, more of what I’ve heard from a few other control and automation companies.” But no, this was much more like Mindsphere taken to an entirely new level. This brings together the vision of digital factory I first heard from a Siemens executive at an ARC Industry Forum in 2006 fleshed out in 2007 when we discussed the acquisition of UGS. I voiced a bit of skepticism. Kudos to Siemens management for pulling it all off.
Siemens Xcelerator comprises a curated portfolio, a growing partner ecosystem and an evolving marketplace to speed up value creation across industry, buildings, grids and mobility.
The key components:
- Curated portfolio of IoT-enabled hardware, software and digital services following key design principles of interoperability, flexibility, openness and as-a-service
- Launch of new Building X end-to-end smart building Software-as-a-Service (SaaS) suite
- Planned acquisition of Brightly Software will accelerate growth in digital buildings complementing Siemens’ smart building portfolio
- Partner ecosystem grows through industrial metaverse partnership with NVIDIA for physics-based, immersive digital twin development
- Reaffirms Siemens’ ten percent compound annual growth targets for digital business
Siemens Xcelerator is an open digital business platform — consisting of a curated portfolio, ecosystem and marketplace — to accelerate digital transformation and value creation for our customers. A business platform creates value by facilitating interactions and fostering innovation between multiple parties (customers, partners, developers etc.). It enables digital transformation easy, fast and at scale.
Roland Busch, President and CEO of Siemens AG, said: “Siemens Xcelerator will make it easier than ever before for companies to navigate digital transformation – faster and at scale. By combining the real and the digital worlds across operational and information technology, we empower customers and partners to boost productivity, competitiveness and scale up innovations.”
“Today’s launch of Siemens Xcelerator, this week’s acquisition of Brightly Software and our expanded partnership with NVIDIA are major milestones in implementing our strategy to accelerate high-value growth,” Busch concluded.
Xcelerator becomes the consolidating focal point for Siemens’ array of products and services.
With the launch of Siemens Xcelerator, step-by-step, Siemens will transform its entire portfolio of hardware and software to become modular, cloud-connected and built on standard application programming interfaces (APIs). The highest standards and value for all parties will be ensured by strong technical and commercial governance principles. Siemens and third-party offerings will adhere to the design principles of interoperability, flexibility, openness and as-a-service.
New SaaS launch – Building X
Facility automation has not been forgotten. Siemens announced Building X. The Building CEO must have used the phrase “single pane of glass” a dozen times in his presentation describing the new offering.
Siemens announced today the first new SaaS offering as part of Siemens Xcelerator. Building X is a new smart building suite to create a single source of truth (SSOT) that takes complexity out of digitalization and supports customers to achieve their net zero goals. It is an end-to-end data and analytics suite breaking down data silos across domains such as energy management, security and building maintenance. Building X is a modular, fully cloud-based open software suite, with AI enabled applications, strong connectivity and built-in cybersecurity.
On Monday, June 27, 2022, Siemens announced the agreement to purchase Brightly Software, a leading U.S.-based asset and maintenance management software company. The acquisition will add Brightly‘s well-established capabilities across key sectors to Siemens’ digital and software know-how in buildings. It will be a core element of the Siemens Xcelerator for Buildings portfolio.
Industrial is not forgotten
Siemens also plans to integrate its industrial internet of things (IIoT) solutions for industry as Industrial Operations X, which brings together solutions and applications from sensor to edge to cloud, IoT as-a-service and low code development capabilities, as well as a wide range of ready-to-use-apps. It enables the fusion of data from the real world of automation with the digital world of information technology, enriched by Siemens’ comprehensive vertical IT/ OT integration knowledge and capabilities. Breaking down data silos will help companies to increase their performance, productivity, flexibility and sustainability.
