by Gary Mintchell | Jun 12, 2026 | Commentary, Generative AI
Secularism, scientism, rationalist Richard Dawkins wants to end any influence of “religion.” In doing so, he actually tries to start a new religion. This new secular religion most likely began with French philosopher and mathematician René Descartes. The coterie of Silicon Valley Generative AI leaders follow those unfortunate footsteps.
Pope Leo XIV unhesitatingly issued a 42,000-word encyclical, ”Magnifica Humanitas,” in response to the challenges of artificial intelligence.
Cultural technology critic and professor of computer science Cal Newport wrote, “Last week, Pope Leo XIV released I’m still digesting the full document, but early summaries indicate that the Pope is not ready to meekly acquiesce to the AI future that we’ve been told is inevitable.”
Leo wrote, “With the heart of a shepherd and a father, I ask everyone to abandon the construction of yet another Tower of Babel and to join forces in building up the common good, so that humanity will never lose its beauty, and the world once again will come to recognize the human heart as the place where God desires to dwell.”
I’ve been involved with automation for more than 40 years. Its value has always been as a tool to remove humans from dangerous jobs, enhance consistent quality, and eventually providing necessary data to feed business systems. They are best when used to build up the common good.
I wrote a longer philosophical piece last week on the subject. I continue to caution us not to be distracted by the hype. Do not become distracted or distraught by momentary whims in media or by “influencers.”
Just as I wrote on another blog last week about how I’d love to see a huge outbreak of humility amongst us.
Is there some hope in the discourse? Newport concludes his essay this way.
“Thankfully, in recent weeks, there has been a marked shift in how technology executives talk about AI. Nvidia CEO Jensen Huang called BS on executives claiming they’re laying people off due to AI, calling the excuse ‘lazy’ and ‘just a way for them to sound smart.’ Perhaps even more surprising, just last week, Sam Altman admitted he had been ‘pretty wrong’ about his previous predictions that AI would automate large numbers of jobs.”
by Gary Mintchell | Jun 9, 2026 | Data Management, Edge
When the three people I knew formed HighByte in the Industrial DataOps market, I thought they had a good thing going. Perhaps revenues have not rocketed as much as hoped, but they keep moving. They added work in unified data namespace. This partnership just announced with Siemens is a good deal for both companies.
In short:
- Partnership delivers unified data infrastructure for industrial operations, combining Siemens Industrial Edge, HighByte Intelligence Hub and Intelligence Center X
- Customers can seamlessly connect, contextualize and consume industrial data to build AI models, agents and applications at scale
- HighByte Intelligence Hub now available on Siemens Industrial Edge Marketplace
Siemens is expanding the capabilities of its Industrial Edge ecosystem through a partnership with industrial software company HighByte. The collaboration enables customers to seamlessly connect, contextualize and transform data from both operational technology (OT) and information technology (IT) sources, helping them to get value from industrial data.
HighByte Intelligence Hub is an industrial data operations software solution, designed specifically for data modeling, orchestration and governance. It is now available as an official application on the Siemens Industrial Edge Marketplace. Customers can efficiently consume and reuse industrial data sets from HighByte to build AI models, agents and applications at scale, using Siemens’ recently announced Intelligence Center X software.
HighByte Intelligence Hub runs natively on Industrial Edge, where application and configuration management is handled. The solution integrates directly with the Industrial Edge’s Connectivity Suite, enabling users to connect to a wide variety of OT data sources including PLCs, SCADA systems, and industrial protocols. HighByte’s DataOps functionalities extend this connectivity to IT data sources, creating a unified data infrastructure that spans the entire production operation.
A key capability of the integrated solution is data contextualization and pipelining. Using HighByte Intelligence Hub, users can apply flexible and scalable transformation rules to process data from multiple sources across IT and OT domains, adding business context and converting raw operational data into meaningful information. These contextualized datasets can then be made available to IT services in a transparent and scalable manner, with HighByte serving as a true Unified Namespace provider that standardizes data access across the organization. Beyond making OT data available to IT systems, HighByte Intelligence Hub can also be used to adjust machine setpoints in a secure and reliable way, by sending commands from IT data sources – such as manufacturing execution systems (MES) – back to PLCs via Industrial Edge’s Connectivity Suite.
by Gary Mintchell | Jun 5, 2026 | Software
Deepgram continues to roll out extensions to its real-time voice AI platform.
- Deepgram and Fortanix are the first to bring confidential computing to real-time voice AI, allowing organizations to protect sensitive conversations and AI models even while they are actively being used.
- Until now, you could protect data when it was stored and when it was moving. The hard part was protecting it while the AI was actually using it. That’s what we’re solving here for real-time voice AI.
- Sensitive enterprise data and proprietary model IP remain private during active inference, with no exposure to underlying infrastructure
From the press release:
Deepgram and Fortanix announced a partnership that will enable enterprises to run voice AI in their own environment on their own terms while ensuring their most sensitive data is securely protected. Under terms of the agreement, Deepgram can leverage Fortanix Confidential AI and NVIDIA Confidential Computing to add an additional layer of advanced security to self-hosted environments to ensure that its proprietary model weights, built on business-critical intellectual property, can be deployed while protecting against model theft or inappropriate use.
For enterprises, especially those in highly regulated industries, security requirements continue to tighten. Organizations handling patient conversations, financial transactions, or classified information increasingly require that sensitive audio and AI model weights remain protected not only at rest and in transit, but also during active processing in their own environments. This level of protection enables organizations to build highly-secure real-time voice applications without sacrificing on performance.
The on-premises solution runs Deepgram’s voice AI models with Fortanix Confidential AI on NVIDIA Confidential Computing-enabled GPUs, creating a hardware-isolated environment where both audio data and model weights remain encrypted and protected throughout active use. NVIDIA GPUs with Confidential Computing enable AI workloads to process sensitive data inside a trusted execution environment — a capability traditional infrastructure cannot provide. By bringing together best-in-class voice AI models, hardware-rooted isolation, and a jointly engineered, pre-integrated stack, the partnership delivers a level of in-use data protection that, until now, has not been practical to deploy at enterprise scale.
by Gary Mintchell | Jun 4, 2026 | Manufacturing IT, Software
Here is a new service—operational decision intelligence. Also a company new to me—SteelTree. They define an operational decision intelligence service as something designed to help industrial teams improve awareness, reduce friction, and coordinate action across fast-moving operations.
The information I could gather combined was very sparse. Not sure why it’s better or worth than anything out there already (unless the “.ai” means something new in AI. It could be worth checking just in case.
The company seeks to help teams move beyond disconnected dashboards, spreadsheets, reports, and silos to improve visibility, coordination, and execution across day-to-day operations. SteelTree enables teams to quickly identify changes, recurring issues, performance drift, coordination gaps, and priorities requiring attention.
The model consists of:
See → Decide → Execute → Learn
SteelTree helps industrial teams:
- See what’s happening
- Decide what matters most
- Coordinate and execute actions faster
- Continuously learn before small issues become larger problems
“Most teams are not lacking systems or data,” said Kanwar Arora, Founder of SteelTree. “What they’re lacking is continuous operational awareness across fast-moving environments. Teams still spend too much time moving between dashboards, spreadsheets, reports, and silos just to understand what requires attention. SteelTree reduces the friction between operational signals, decisions, and action.”
Unlike traditional BI, dashboarding, and reporting tools that often depend on analysts, dashboard development, and delayed reporting cycles, SteelTree is focused on helping teams maintain awareness and coordination without adding overhead.
The company believes many organizations still struggle with operational visibility and coordination despite significant investments in business systems and reporting tools.
“As the software industry races to embed AI across enterprise applications, many teams still struggle with a more fundamental challenge: maintaining awareness across fast-moving operations and coordinating action effectively,” said Peter Price, Founder of SteelTree. “SteelTree starts by helping teams see clearly, but visibility alone is not enough. The real value comes from helping teams decide faster, execute more effectively, and continuously learn across day-to-day operations.”
SteelTree’s launch is focused on industrial teams looking to improve operational awareness, decision-making, and coordination without the complexity typically associated with traditional enterprise analytics and reporting tools.
The service is available immediately with free access.
by Gary Mintchell | Jun 2, 2026 | Robots, Software, Technology
Manufacturers have lots of data. Every day brings new technologies for gathering and storing it. The right question probes into what specific problem can be solved. I sat in the world’s shortest press conference (not complaining, even though they blew off my question) with a company I don’t know who asked the question—how can we better integrate the myriad details required to build the best robotic workcell.
The company is called Robotiq. Based in Quebec City, Canada, introduced IQ, an AI-enabled platform designed to make robotic Workcell integration faster, more predictable, and easier to scale. IQ captures unstructured automation project data, coordinates engineering workflows, and helps partners generate validated Workcell designs based on real customer inputs and historical deployment data from thousands of previous factory installations.
“AI” can be a generic marketing buzzword. I asked for a definition, but the press conference closed before they got to it. Reading through the press release, the definition apparently involves machine learning algorithms. Fair enough.
“Automation does not scale when integration remains manual,” said Samuel Bouchard, CEO of Robotiq. “With IQ, we are moving from manually engineering robotic systems one project at a time to automatically generating Workcells from real customer inputs, Robotiq components, AI, and proven know-how from thousands of past projects. For manufacturers, this means a clearer path to automation: fewer surprises, faster decisions, more predictable performance, and better financial justification, including in many 1-shift operations.”
Robotic Workcell integration depends on thousands of small details. Customer requirements, production constraints, factory floor layouts, site measurements, throughput targets, product variants, and local installation realities all affect whether a project succeeds. When that data is incomplete, fragmented or siloed, engineering teams experience project delays during the discovery and design revision phases.
The IQ solution includes:
- Automated data capture: Extract technical requirements via voice notes, legacy file uploads, and 3D site scanning.
- AI-enabled project coordination: Machine-learning models align manufacturer specifications, partner capabilities, and Robotiq application engineering expertise.
- Simulation and design validation: 3D environment scans are converted into digital twin models, matching customer cycle times and application data against standardized engineering rules to validate Workcell performance before physical deployment.
IQ is available today for robotic palletizing applications, where Robotiq has already standardized the hardware components, software workflows, and deployment knowledge needed to generate validated Workcell designs. Over time, Robotiq plans to extend the same Automatic Integration model to additional robotic applications.
To commission robotic systems successfully, manufacturers need local system integration support, application expertise, and reliable service. Robotiq partners play that role. IQ provides partners with a repeatable digital workflow to capture project information, apply Robotiq deployment expertise, collaborate with customers and Robotiq experts, and support Workcells more consistently after installation.
“IQ does not replace partner expertise,” Bouchard added. “It amplifies this expertise to accelerate and scale projects. Manufacturers need local partners who understand their production reality and can provide the installation capacity and support needed to keep lines running. IQ gives those partners better information, better coordination, and a clearer path from opportunity to running system.”
by Gary Mintchell | May 27, 2026 | Generative AI
I’ve spent too many hours on AI. I notice statistics indicating that more people are interested in data interoperability than in AI. But this is timely. I thought I’d share this item from John Ellis News Items. It’s one of my favorite sources for a quick update on the news.
You may or may not realize that much of the media shouts from Silicon Valley are really religious in nature. Many out there subscribe to a “scientism.” Shunning traditional religion, they espouse radical rationalism fashioning a religion from reason and science.
First, no less a person than the Pope takes on the Silicone Valley religion head on.
When Pope Leo XIV presented a 42,300-word open letter to the world’s 1.4 billion Catholics on Monday, calling for protections against the rise of artificial intelligence, he was joined by Christopher Olah, a co-founder of Anthropic, which is one of the tech industry’s leading A.I. companies.
As Leo urged corporate executives, government regulators and other citizens of the world to safeguard humanity from the dangers of A.I., he included Mr. Olah as a symbol of the dialogue he hopes to foster between the leaders of the spiritual and technological worlds.
Was this really a discussion?
But for Jeremy Nixon, Monday’s gathering at the Vatican showed that those two worlds are far from aligned. While the pope said that A.I. was fundamentally not human, Mr. Nixon, a well-connected figure in the Bay Area’s frenetic A.I. scene, argued that Mr. Olah’s remarks seemed to hint at the opposite.
“They are not in dialogue,” Mr. Nixon said during an interview at A.G.I. House, a San Francisco “hacker house” with deep ties to many of the people who helped create the A.I. technologies discussed in the pope’s encyclical. “Their perspectives are distinct.”
Ah, the news reports drag in another philosophy—humanism.
The difference between the humanist’s view of A.I.’s risks and the technologist’s dream of what it could become is something that has long been discussed in Mr. Nixon’s community. “It is the reason the community exists,” Mr. Nixon said. “It is its underlying purpose.”
I listen to a podcast called Robot or Not, where podcaster and engineer John Siracusa answers listeners’ questions on definitions. In this case, looks like the question is “AI, Human or Not.”
Mr. Nixon, 33, is one of the founders of A.G.I. House, which is named for Silicon Valley’s headlong pursuit of “artificial general intelligence,” a hypothetical machine that can do anything the human brain can do.
Mr. Nixon said the papal encyclical might mean something to the world’s Catholics, but he doubted that it would have an effect on Silicon Valley. The only reason that Silicon Valley even paid attention to the event, he said, was that Leo invited Mr. Olah to speak.
Mr. Nixon is now founder and chief executive of a start-up called the Infinity Artificial Intelligence Institute, which is trying to automate the creation of A.I.
Even more grandiose that Human or Not, is it God or Not?
Mr. Nixon said he has met a generation of scientists who shunned traditional religion in favor of technology. After growing up with books like “The God Delusion” — in which the evolutionary biologist Richard Dawkins painted God as a false belief contradicted by empirical evidence — he and his peers saw A.I. as an alternative that was more real and far more powerful.
A.I. has started to crack math problems that humans struggled with for decades, he said, and it will soon cure diseases in the same way. “Practically speaking, it will achieve the outcomes that many religions claim their deities would be able to achieve,” he said.
This is an increasingly common belief among researchers in Silicon Valley. They insist they are on their way to building a more powerful species — or even a new God.
As a contemplative, my view of God comes from practice and experience, rather than logical argument. If you are on the rational argument side of things, go for it!
