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:

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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.

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SOURCE Honeywell

The science section of our news blog STM Daily News provides readers with captivating and up-to-date information on the latest scientific discoveries, breakthroughs, and innovations across various fields. We offer engaging and accessible content, ensuring that readers with different levels of scientific knowledge can stay informed. Whether it’s exploring advancements in medicine, astronomy, technology, or environmental sciences, our science section strives to shed light on the intriguing world of scientific exploration and its profound impact on our daily lives. From thought-provoking articles to informative interviews with experts in the field, STM Daily News Science offers a harmonious blend of factual reporting, analysis, and exploration, making it a go-to source for science enthusiasts and curious minds alike. https://stmdailynews.com/category/science/

Rizwan Virk, Arizona State University

ChatGPT

In May 2024, OpenAI CEO Sam Altman sparked a firestorm by referencing the 2013 movie “Her” to highlight the novelty of the latest iteration of ChatGPT.

Within days, actor Scarlett Johansson, who played the voice of Samantha, the AI girlfriend of the protagonist in the movie “Her,” accused the company of improperly using her voice after she had spurned their offer to make her the voice of ChatGPT’s new virtual assistant. Johansson ended up suing OpenAI and has been invited to testify before Congress.

This tiff highlights a broader interchange between Hollywood and Silicon Valley that’s called the “sci-fi feedback loop.” The subject of my doctoral research, the sci-fi feedback loop explores how science fiction and technological innovation feed off each other. This dynamic is bidirectional and can sometimes play out over many decades, resulting in an ongoing loop.

Fiction sparks dreams of Moon travel

One of the most famous examples of this loop is Moon travel.

Jules Verne’s 1865 novel “From the Earth to the Moon” and the fiction of H.G. Wells inspired one of the first films to visualize such a journey, 1902’s “A Trip to the Moon.”

The fiction of Verne and Wells also influenced future rocket scientists such as Robert Goddard, Hermann Oberth and Oberth’s better-known protégé, Wernher von Braun. The innovations of these men – including the V-2 rocket built by von Braun during World War II – inspired works of science fiction, such as the 1950 film “Destination Moon,” which included a rocket that looked just like the V-2.

Films like “Destination Moon” would then go on to bolster public support for lavish government spending on the space program. https://www.youtube.com/embed/xLVChRVfZ74?wmode=transparent&start=0 The 1902 silent short ‘A Trip to the Moon.’

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Creative symbiosis

The sci-fi feedback loop generally follows the same cycle.

First, the technological climate of a given era will shape that period’s science fiction. For example, the personal computing revolution of the 1970s and 1980s directly inspired the works of cyberpunk writers Neal Stephenson and William Gibson.

Then the sci-fi that emerges will go on to inspire real-world technological innovation. In his 1992 classic “Snow Crash,” Stephenson coined the term “metaverse” to describe a 3-D, video game-like world accessed through virtual reality goggles.

Silicon Valley entrepreneurs and innovators have been trying to build a version of this metaverse ever since. The virtual world of the video game Second Life, released in 2003, took a stab at this: Players lived in virtual homes, went to virtual dance clubs and virtual concerts with virtual girlfriends and boyfriends, and were even paid virtual dollars for showing up at virtual jobs.

This technology seeded yet more fiction; in my research, I discovered that sci-fi novelist Ernest Cline had spent a lot of time playing Second Life, and it inspired the metaverse of his bestselling novel “Ready Player One.”

The cycle continued: Employees of Oculus VR – now known as Meta Reality Labs – were given copies of “Ready Player One” to read as they developed the company’s virtual reality headsets. When Facebook changed its name to Meta in 2021, it did so in the hopes of being at the forefront of building the metaverse, though the company’s grand ambitions have tempered somewhat.

Another sci-fi franchise that has its fingerprints all over this loop is “Star Trek,” which first aired in 1966, right in the middle of the space race.

Steve Perlman, the inventor of Apple’s QuickTime media format and player, said he was inspired by an episode of “Star Trek: The Next Generation,” in which Lt. Commander Data, an android, sifts through multiple streams of audio and video files. And Rob Haitani, the designer of the Palm Pilot’s operating system, has said that the bridge on the Enterprise influenced its interface.

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In my research, I also discovered that the show’s Holodeck – a room that could simulate any environment – influenced both the name and the development of Microsoft’s HoloLens augmented reality glasses.

From ALICE to ‘Her’

Which brings us back to OpenAI and “Her.”

In the movie, the protagonist, Theodore, played by Joaquin Phoenix, acquires an AI assistant, “Samantha,” voiced by Johansson. He begins to develop feelings for Samantha – so much so that he starts to consider her his girlfriend.

ChatGPT-4o, the latest version of the generative AI software, seems to be able to cultivate a similar relationship between user and machine. Not only can ChatGPT-4o speak to you and “understand” you, but it can also do so sympathetically, as a romantic partner would.

There’s little doubt that the depiction of AI in “Her” influenced OpenAI’s developers. In addition to Altman’s tweet, the company’s promotional videos for ChatGPT-4o feature a chatbot speaking with a job candidate before his interview, propping him up and encouraging him – as, well, an AI girlfriend would. The AI featured in the clips, Ars Technica observed, was “disarmingly lifelike,” and willing “to laugh at your jokes and your dumb hat.”

But you might be surprised to learn that a previous generation of chatbots inspired Spike Jonze, the director and screenwriter of “Her,” to write the screenplay in the first place. Nearly a decade before the film’s release, Jonze had interacted with a version of the ALICE chatbot, which was one of the first chatbots to have a defined personality – in ALICE’s case, that of a young woman.

The ALICE chatbot won the Loebner Prize three times, which was awarded annually until 2019 to the AI software that came closest to passing the Turing Test, long seen as a threshold for determining whether artificial intelligence has become indistinguishable from human intelligence.

The sci-fi feedback loop has no expiration date. AI’s ability to form relationships with humans is a theme that continues to be explored in fiction and real life.

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A few years after “Her,” “Blade Runner 2049” featured a virtual girlfriend, Joi, with a holographic body. Well before the latest drama with OpenAI, companies had started developing and pitching virtual girlfriends, a process that will no doubt continue. As science fiction writer and social media critic Cory Doctorow wrote in 2017, “Science fiction does something better than predict the future: It influences it.”

Rizwan Virk, Faculty Associate, PhD Candidate in Human and Social Dimensions of Science and Technology, Arizona State University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

The science section of our news blog STM Daily News provides readers with captivating and up-to-date information on the latest scientific discoveries, breakthroughs, and innovations across various fields. We offer engaging and accessible content, ensuring that readers with different levels of scientific knowledge can stay informed. Whether it’s exploring advancements in medicine, astronomy, technology, or environmental sciences, our science section strives to shed light on the intriguing world of scientific exploration and its profound impact on our daily lives. From thought-provoking articles to informative interviews with experts in the field, STM Daily News Science offers a harmonious blend of factual reporting, analysis, and exploration, making it a go-to source for science enthusiasts and curious minds alike. https://stmdailynews.com/category/science/

Mahshid Ahmadi, University of Tennessee

Many human activities release pollutants into the air, water and soil. These harmful chemicals threaten the health of both people and the ecosystem. According to the World Health Organization, air pollution causes an estimated 4.2 million deaths annually.

Scientists are looking into solutions, and one potential avenue is a class of materials called photocatalysts. When triggered by light, these materials undergo chemical reactions that initial studies have shown can break down common toxic pollutants.

I am a materials science and engineering researcher at the University of Tennessee. With the help of robots and artificial intelligence, my colleagues and I are making and testing new photocatalysts with the goal of mitigating air pollution.

Breaking down pollutants

The photocatalysts work by generating charged carriers in the presence of light. These charged carriers are tiny particles that can move around and cause chemical reactions. When they come into contact with water and oxygen in the environment, they produce substances called reactive oxygen species. These highly active reactive oxygen species can bond to parts of the pollutants and then either decompose the pollutants or turn them into harmless – or even useful – products.

But some materials used in the photocatalytic process have limitations. For example, they can’t start the reaction unless the light has enough energy – infrared rays with lower energy light, or visible light, won’t trigger the reaction.

Another problem is that the charged particles involved in the reaction can recombine too quickly, which means they join back together before finishing the job. In these cases, the pollutants either do not decompose completely or the process takes a long time to accomplish.

Additionally, the surface of these photocatalysts can sometimes change during or after the photocatalytic reaction, which affects how they work and how efficient they are.

To overcome these limitations, scientists on my team are trying to develop new photocatalytic materials that work efficiently to break down pollutants. We also focus on making sure these materials are nontoxic so that our pollution-cleaning materials aren’t causing further pollution.

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Teeny tiny crystals

Scientists on my team use automated experimentation and artificial intelligence to figure out which photocatalytic materials could be the best candidates to quickly break down pollutants. We’re making and testing materials called hybrid perovskites, which are tiny crystals – they’re about a 10th the thickness of a strand of hair.

These nanocrystals are made of a blend of organic (carbon-based) and inorganic (non-carbon-based) components.

They have a few unique qualities, like their excellent light-absorbing properties, which come from how they’re structured at the atomic level. They’re tiny, but mighty. Optically, they’re amazing too – they interact with light in fascinating ways to generate a large number of tiny charge carriers and trigger photocatalytic reactions.

These materials efficiently transport electrical charges, which allows them to transport light energy and drive the chemical reactions. They’re also used to make solar panels more efficient and in LED lights, which create the vibrant displays you see on TV screens.

There are thousands of potential types of hybrid nanocrystals. So, my team wanted to figure out how to make and test as many as we can quickly, to see which are the best candidates for cleaning up toxic pollutants.

Bringing in robots

Instead of making and testing samples by hand – which takes weeks or months – we’re using smart robots, which can produce and test at least 100 different materials within an hour. These small liquid-handling robots can precisely move, mix and transfer tiny amounts of liquid from one place to another. They’re controlled by a computer that guides their acceleration and accuracy.

We also use machine learning to guide this process. Machine learning algorithms can analyze test data quickly and then learn from that data for the next set of experiments executed by the robots. These machine learning algorithms can quickly identify patterns and insights in collected data that would normally take much longer for a human eye to catch.

Our approach aims to simplify and better understand complex photocatalytic systems, helping to create new strategies and materials. By using automated experimentation guided by machine learning, we can now make these systems easier to analyze and interpret, overcoming challenges that were difficult with traditional methods.

Mahshid Ahmadi, Assistant Professor of Materials Science and Engineering, University of Tennessee

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This article is republished from The Conversation under a Creative Commons license. Read the original article.

The science section of our news blog STM Daily News provides readers with captivating and up-to-date information on the latest scientific discoveries, breakthroughs, and innovations across various fields. We offer engaging and accessible content, ensuring that readers with different levels of scientific knowledge can stay informed. Whether it’s exploring advancements in medicine, astronomy, technology, or environmental sciences, our science section strives to shed light on the intriguing world of scientific exploration and its profound impact on our daily lives. From thought-provoking articles to informative interviews with experts in the field, STM Daily News Science offers a harmonious blend of factual reporting, analysis, and exploration, making it a go-to source for science enthusiasts and curious minds alike. https://stmdailynews.com/category/science/