Tech
Honeywell and Google Cloud to Accelerate Autonomous Operations with AI Agents for the Industrial Sector
Google Cloud AI to enhance Honeywell’s product offerings
and help upskill the industrial workforce
New solutions will connect to enterprise-wide industrial data from Honeywell Forge,
a leading IoT platform for industrials
CHARLOTTE, N.C. and SUNNYVALE, Calif. /PRNewswire/ — Honeywell (NASDAQ: HON) and Google Cloud announced a unique collaboration connecting artificial intelligence (AI) agents with assets, people and processes to accelerate safer, autonomous operations for the industrial sector.
This partnership will bring together the multimodality and natural language capabilities of Gemini on Vertex AI – Google Cloud’s AI platform – and the massive data set on Honeywell Forge, a leading Internet of Things (IoT) platform for industrials. This will unleash easy-to-understand, enterprise-wide insights across a multitude of use cases. Honeywell’s customers across the industrial sector will benefit from opportunities to reduce maintenance costs, increase operational productivity and upskill employees. The first solutions built with Google Cloud AI will be available to Honeywell’s customers in 2025.
“The path to autonomy requires assets working harder, people working smarter and processes working more efficiently,” said Vimal Kapur, Chairman and CEO of Honeywell. “By combining Google Cloud’s AI technology with our deep domain expertise–including valuable data on our Honeywell Forge platform–customers will receive unparalleled, actionable insights bridging the physical and digital worlds to accelerate autonomous operations, a key driver of Honeywell’s growth.”
“Our partnership with Honeywell represents a significant step forward in bringing the transformative power of AI to industrial operations,” said Thomas Kurian, CEO of Google Cloud. “With Gemini on Vertex AI, combined with Honeywell’s industrial data and expertise, we’re creating new opportunities to optimize processes, empower workforces and drive meaningful business outcomes for industrial organizations worldwide.”
With the mass retirement of workers from the baby boomer generation, the industrial sector faces both labor and skills shortages, and AI can be part of the solution – as a revenue generator, not job eliminator. More than two-thirds (82%) of Industrial AI leaders believe their companies are early adopters of AI, but only 17% have fully launched their initial AI plans, according to Honeywell’s 2024 Industrial AI Insights report. This partnership will provide AI agents that augment the existing operations and workforce to help drive AI adoption and enable companies across the sector to benefit from expanding automation.
Honeywell and Google Cloud will co-innovate solutions around:
Purpose-Built, Industrial AI Agents
Built on Google Cloud’s Vertex AI Search and tailored to engineers’ specific needs, a new AI-powered agent will help automate tasks and reduce project design cycles, enabling users to focus on driving innovation and delivering exceptional customer experiences.
Additional agents will utilize Google’s large language models (LLMs) to help technicians to more quickly resolve maintenance issues (e.g., “How did a unit perform last night?” “How do I replace the input/output module?” or “Why is my system making this sound?”). By leveraging Gemini’s multimodality capabilities, users will be able to process various data types such as images, videos, text and sensor readings, which will help its engineers get the answers they need quickly – going beyond simple chat and predictions.
Enhanced Cybersecurity
Google Threat Intelligence – featuring frontline insight from Mandiant – will be integrated into current Honeywell cybersecurity products, including Global Analysis, Research and Defense (GARD) Threat Intelligence and Secure Media Exchange (SMX), to help enhance threat detection and protect global infrastructure for industrial customers.
On-the-Edge Device Advances
Looking ahead, Honeywell will explore using Google’s Gemini Nano model to enhance Honeywell edge AI devices’ intelligence multiple use cases across verticals, ranging from scanning performance to voice-based guided workflow, maintenance, operational and alarm assist without the need to connect to the internet and cloud. This is the beginning of a new wave of more intelligent devices and solutions, which will be the subject of future Honeywell announcements.
By leveraging AI to enable growth and productivity, the integration of Google Cloud technology also further supports Honeywell’s alignment of its portfolio to three compelling megatrends, including automation.
About Honeywell
Honeywell is an integrated operating company serving a broad range of industries and geographies around the world. Our business is aligned with three powerful megatrends – automation, the future of aviation and energy transition – underpinned by our Honeywell Accelerator operating system and Honeywell Forge IoT platform. As a trusted partner, we help organizations solve the world’s toughest, most complex challenges, providing actionable solutions and innovations through our Aerospace Technologies, Industrial Automation, Building Automation and Energy and Sustainability Solutions business segments that help make the world smarter and safer as well as more secure and sustainable. For more news and information on Honeywell, please visit www.honeywell.com/newsroom.
About Google Cloud
Google Cloud is the new way to the cloud, providing AI, infrastructure, developer, data, security, and collaboration tools built for today and tomorrow. Google Cloud offers a powerful, fully integrated, and optimized AI stack with its own planet-scale infrastructure, custom-built chips, generative AI models, and development platform, as well as AI-powered applications, to help organizations transform. Customers in more than 200 countries and territories turn to Google Cloud as their trusted technology partner.
SOURCE Honeywell
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Tech
When ‘Head in the Clouds’ Means Staying Ahead
Head in the Clouds: Cloud is no longer just storage—it’s the intelligent core of modern business. Explore how “cognitive cloud” blends AI and cloud infrastructure to enable real-time, self-optimizing operations, improve customer experiences, and accelerate enterprise modernization.
Last Updated on February 7, 2026 by Daily News Staff
When ‘Head in the Clouds’ Means Staying Ahead
(Family Features) You approve a mortgage in minutes, your medical claim is processed without a phone call and an order that left the warehouse this morning lands at your door by dinner. These moments define the rhythm of an economy powered by intelligent cloud infrastructure. Once seen as remote storage, the cloud has become the operational core where data, AI models and autonomous systems converge to make business faster, safer and more human. In this new reality, the smartest companies aren’t looking up to the cloud; they’re operating within it. Public cloud spending is projected to reach $723 billion in 2025, according to Gartner research, reflecting a 21% increase year over year. At the same time, 90% of organizations are expected to adopt hybrid cloud by 2027. As cloud becomes the universal infrastructure for enterprise operations, the systems being built today aren’t just hosted in the cloud, they’re learning from it and adapting to it. Any cloud strategy that doesn’t account for AI workloads as native risks falling behind, holding the business back from delivering the experiences consumers rely on every day. After more than a decade of experimentation, most enterprises are still only partway up the curve. Based on Cognizant’s experience, roughly 1 in 5 enterprise workloads has moved to the cloud, while many of the most critical, including core banking, health care claims and enterprise resource planning, remain tied to legacy systems. These older environments were never designed for the scale or intelligence the modern economy demands. The next wave of progress – AI-driven products, predictive operations and autonomous decision-making – depends on cloud architectures designed to support intelligence natively. This means cloud and AI will advance together or not at all.The Cognitive Cloud: Cloud and AI as One System
For years, many organizations treated migration as a finish line. Applications were lifted and shifted into the cloud with little redesign, trading one set of constraints for another. The result, in many cases, has been higher costs, fragmented data and limited room for innovation. “Cognitive cloud” represents a new phase of evolution. Imagine every process, from customer service to supply-chain management, powered by AI models that learn, reason and act within secure cloud environments. These systems store and interpret data, detect patterns, anticipate demand and automate decisions at a scale humans simply cannot match. In this architecture, AI and cloud operate in concert. The cloud provides computing power, scale and governance while AI adds autonomy, context and insight. Together, they form an integrated platform where cloud foundations and AI intelligence combine to enable collaboration between people and systems. This marks the rise of the responsive enterprise; one that senses change, adjusts instantly and builds trust through reliability. Cognitive cloud platforms combine data fabric, observability, FinOps and SecOps into an intelligent core that regulates itself in real time. The result is invisible to consumers but felt in every interaction: fewer errors, faster responses and consistent experiences.Consumer Impact is Growing
The impact of cognitive cloud is already visible. In health care, 65% of U.S. insurance claims run through modernized, cloud-enabled platforms designed to reduce errors and speed up reimbursement. In the life sciences industry, a pharmaceuticals and diagnostics firm used cloud-native automation to increase clinical trial investigations by 20%, helping get treatments to patients sooner. In food service, intelligent cloud systems have reduced peak staffing needs by 35%, in part through real-time demand forecasting and automated kitchen operation. In insurance, modernization has produced multi-million-dollar savings and faster policy issuance, improving both customer experience and financial performance. Beneath these outcomes is the same principle: architecture that learns and responds in real time. AI-driven cloud systems process vast volumes of data, identify patterns as they emerge and automate routines so people can focus on innovation, care and service. For businesses, this means fewer bottlenecks and more predictive operations. For consumers, it means smarter, faster, more reliable services, quietly shaping everyday life. While cloud engineering and AI disciplines remain distinct, their outcomes are increasingly intertwined. The most advanced architectures now treat intelligence and infrastructure as complementary forces, each amplifying the other.Looking Ahead
This transformation is already underway. Self-correcting systems predict disruptions before they happen, AI models adapt to market shifts in real time and operations learn from every transaction. The organizations mastering this convergence are quietly redefining themselves and the competitive landscape. Cloud and AI have become interdependent priorities within a shared ecosystem that moves data, decisions and experiences at the speed customers expect. Companies that modernize around this reality and treat intelligence as infrastructure will likely be empowered to reinvent continuously. Those that don’t may spend more time maintaining the systems of yesterday than building the businesses of tomorrow. Learn more at cognizant.com. Photo courtesy of ShutterstockCulver’s Thank You Farmers® Project Hits $8 Million Donation MilestoneLink: https://stmdailynews.com/culvers-thank-you-farmers-project-hits-8-million-donation-milestone/
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The Knowledge
Beneath the Waves: The Global Push to Build Undersea Railways
Undersea railways are transforming transportation, turning oceans from barriers into gateways. Proven by tunnels like the Channel and Seikan, these innovations offer cleaner, reliable connections for passengers and freight. Ongoing projects in China and Europe, alongside future proposals, signal a new era of global mobility beneath the waves.
For most of modern history, oceans have acted as natural barriers—dividing nations, slowing trade, and shaping how cities grow. But beneath the waves, a quiet transportation revolution is underway. Infrastructure once limited by geography is now being reimagined through undersea railways.
Undersea rail tunnels—like the Channel Tunnel and Japan’s Seikan Tunnel—proved decades ago that trains could reliably travel beneath the ocean floor. Today, new projects are expanding that vision even further.
Around the world, engineers and governments are investing in undersea railways—tunnels that allow high-speed trains to travel beneath oceans and seas. Once considered science fiction, these projects are now operational, under construction, or actively being planned.
Undersea Rail Is Already a Reality
Japan’s Seikan Tunnel and the Channel Tunnel between the United Kingdom and France proved decades ago that undersea railways are not only possible, but reliable. These tunnels carry passengers and freight beneath the sea every day, reshaping regional connectivity.
Undersea railways are cleaner than short-haul flights, more resilient than bridges, and capable of lasting more than a century. As climate pressures and congestion increase, rail beneath the sea is emerging as a practical solution for future mobility.
What’s Being Built Right Now
China is currently constructing the Jintang Undersea Railway Tunnel as part of the Ningbo–Zhoushan high-speed rail line, while Europe’s Fehmarnbelt Fixed Link will soon connect Denmark and Germany beneath the Baltic Sea. These projects highlight how transportation and technology are converging to solve modern mobility challenges.
The Mega-Projects Still on the Drawing Board
Looking ahead, proposals such as the Helsinki–Tallinn Tunnel and the long-studied Strait of Gibraltar rail tunnel could reshape global affairs by linking regions—and even continents—once separated by water.
Why Undersea Rail Matters
The future of transportation may not rise above the ocean—but run quietly beneath it.
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CES 2026
Inside the Computing Power Behind Spatial Filmmaking: Hugh Hou Goes Hands-On at GIGABYTE Suite During CES 2026
Inside the Computing Power Behind Spatial Filmmaking: Hugh Hou Goes Hands-On at GIGABYTE Suite During CES 2026
Spatial filmmaking is having a moment—but at CES 2026, the more interesting story wasn’t a glossy trailer or a perfectly controlled demo. It was the workflow.
According to a recent GIGABYTE press release, VR filmmaker and educator Hugh Hou ran a live spatial computing demonstration inside the GIGABYTE suite, walking attendees through how immersive video is actually produced in real-world conditions—capture to post to playback—without leaning on pre-rendered “best case scenario” content. In other words: not theory, not a lab. A production pipeline, running live, on a show floor.
A full spatial pipeline—executed live
The demo gave attendees a front-row view of a complete spatial filmmaking pipeline:
- Capture
- Post-production
- Final playback across multiple devices
And the key detail here is that the workflow was executed live at CES—mirroring the same processes used in commercial XR projects. That matters because spatial video isn’t forgiving. Once you’re working in 360-degree environments (and pushing into 8K), you’re no longer just chasing “fast.” You’re chasing:
- System stability
- Performance consistency
- Thermal reliability
Those are the unsexy requirements that make or break actual production days.
Playback across Meta Quest, Apple Vision Pro, and Galaxy XR
The session culminated with attendees watching a two-minute spatial film trailer across:
- Meta Quest
- Apple Vision Pro
- Newly launched Galaxy XR headsets
- Plus a 3D tablet display offering an additional 180-degree viewing option
That multi-device playback is a quiet flex. Spatial content doesn’t live in one ecosystem anymore—creators are being pulled toward cross-platform deliverables, which adds even more pressure on the pipeline to stay clean and consistent.
Where AI fits (when it’s not the headline)
One of the better notes in the release: AI wasn’t positioned as a shiny feature. It was framed as what it’s becoming for a lot of editors—an embedded toolset that speeds up the grind without hijacking the creative process.
In the demo, AI-assisted processes supported tasks like:
- Enhancement
- Tracking
- Preview workflows
The footage moved through industry-standard software—Adobe Premiere Pro and DaVinci Resolve—with AI-based:
- Upscaling
- Noise reduction
- Detail refinement
And in immersive VR, those steps aren’t optional polish. Any artifact, softness, or weird noise pattern becomes painfully obvious when the viewer can look anywhere.
Why the hardware platform matters for spatial workloads
Underneath the demo was a custom-built GIGABYTE AI PC designed for sustained spatial video workloads. Per the release, the system included:
- AMD Ryzen 7 9800X3D processor
- Radeon AI PRO R9700 AI TOP GPU
- X870E AORUS MASTER X3D ICE motherboard
The point GIGABYTE is making is less “look at these parts” and more: spatial computing workloads demand a platform that can run hard continuously—real-time 8K playback and rendering—without throttling, crashing, or drifting into inconsistent performance.
That’s the difference between “cool demo” and “reliable production machine.”
The bigger takeaway: spatial filmmaking is moving from experiment to repeatable process
By running a demanding spatial filmmaking workflow live—and repeatedly—at CES 2026, GIGABYTE is positioning spatial production as something creators can depend on, not just test-drive.
And that’s the shift worth watching in 2026: spatial filmmaking isn’t just about headsets getting better. It’s about the behind-the-scenes pipeline becoming stable enough that creators can treat immersive production like a real, repeatable craft—because the tools finally hold up under pressure.
Source:PRNewswire – GIGABYTE press release
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