Role of simulation in the digital twin for energy and process industries

Fallmann further explained DToCs are created by connecting scattered data from different silos, departments and data sources, which includes consolidating unstructured and structured information. The enhanced experiences driven by DToCs can extend across the physical and digital worlds. For example, DToCs can assist with the design and planning of retail stores and other physical spaces.

Physics-based simulation models, at varied length scales, allow engineers to capture this complexity and use it to explore design and operating spaces to find optimum conditions. Finally, in the long term, the Gartner report indicated brands should create the digital twin of a team of customer experience specialists that will be used to discuss the implications and merits of DToC on operational processes and the overall brand business model. Privacy regulations and laws should be discussed regularly, and the team should work on tracking dynamic personas and the stages of their relationships. “One key innovation making DToC possible is the availability of cloud-scale computing resources combined with modern AI and ML technologies,” Jones explained.

AI can help HR act on the massive amount of data it collects daily by planning and testing new processes and services in the virtual world long before they see actual daylight. Such a contextual model can drive key decisions which could have been missed, overlooked or not readily visible otherwise. Imagine a digital representation of a process or machine with all current operational parameters and predictions against future orders for material availability, tool life and maintenance schedules. A planner can see how many orders they can schedule with current on-hand inventory and machine supplies. A plant manager can visualize the production rate with potential bottlenecks, and a maintenance manager can determine the remaining tool life and plan the next maintenance. Data from MES is essential for creating a comprehensive digital twin throughout a manufactured product’s life cycle, especially in operational stages beyond engineering and design.

Digital Twins Of The Customer: The Future Of Data Collection

• It isn’t always easy to determine the nature of an issue based on a phone call or chat conversation alone, especially as products and services continue to become more and more complex.
• This includes simulating, and even anticipating a customer’s behaviour, wants, needs and preferences, as well as the ability to test these in different scenarios.
• Entire stores can be replicated via digital twins, and virtual customers walking on the shop floor can be analyzed based on their behavior and the interactions they have on the floor.
• This enables them to better understand what a specific customer purchases, how frequently they buy, how much money they spend and how often they frequent the brand’s website.
• By bridging the gap between the physical world and the digital world, digital twins can enable a brand’s customer service to provide this differentiated level of service through the data they provide.

DToCs can simulate how specific cohorts will respond before a customer journey is defined, saving time and money spent on testing underperforming journey interventions. Forty-one percent of respondents who’ve achieved full customer data integration indicated they were still unable to prove the value of marketing, according to Gartner’s 2022 Marketing Data & Analytics Survey. Developing a 360-degree view requires multiple tools and partners to collect a variety of data types, including behavioral and attribute data. Because of the added complexity and expense, only 14% of organizations have actually achieved a 360-degree view, according to our research. A 360-degree view of the customer is the output of a consolidated, integrated, exhaustive set of data relevant to a company’s relationship with its customers or prospects.

How Digital Twins In HR Can Help Predict Problems And Lead To Organizational Change

At the same time, enterprises have been busy finding ways to get the most value from their investment using various marketing analytics tools. Our sister community, Reworked, gathers the world’s leading employee experience and digital workplace professionals. And our newest community, VKTR, is home for AI practitioners and forward thinking leaders focused on the business of enterprise AI.

Subha Tatavarti, CTO, Wipro, told VentureBeat there have been several important milestones in using tools for simulating customers to improve experiences. The most notable have been the ability to define customer experience transformation objectives, including the capability to identify and assess data assets, personas and processes and tools for building and testing behavior models. New ModelOps approaches for integrating monitoring and enhancing the models are also advancing the field. An important consideration when employing a digital twin is that organizations are recording data and transferring it via cloud technology. This data may be sensitive and contain intellectual property, which puts the organization at risk of a breach. To avoid this, security should be considered a priority from the start for organizations integrating digital twin technology into their customer experience.

How Is a Digital Twin of a Customer Created?

The Infrastructure Cloud will also carry benefits beyond a single project, acting as a source of infrastructure schema and data that can be used on future projects. “Unlike traditional, reactive approaches such as basic customer segmentation or analytics, digital twins go beyond static profiles and actively simulate customer behaviour, wants, needs, and preferences,” he said. In today’s disruptive economy, taking a commodity area of the business, such as cleaning, back in-house is a challenging conversation for business leaders. However, as CIO Emiliano Sorrenti reveals, data enables the organization to believe in a change of course, take control of areas typically outsourced and show how it benefits the customer and ultimately the organization. As organizations continue to become data-driven, data could well be the key to another significant change in the world economy and the current ethos towards outsourcing. By including IoT technology and sensors into products that gather data, information can be sent back to the organization to provide on-the-ground insight into how products are being used, how well they’re performing and the status of the operating system.

When internal battery monitors indicate low levels in devices, you tailor offers to include extended battery-life models. If a customer typically adds an additional 30 seconds after microwaving their dinner, flag them as a target for a higher-wattage model, or offer them a service call to check the output of the appliance. Global beauty chain Sephora builds DToCs to predict products that customers would most likely be interested in, based on their purchase and browsing history.

Digital ways to improve CX.

Combined with other technologies, such as AR, digital twins can offer a truly immersive environment where anything can be turned into a digital experience. Whether the goal is to execute a new strategy, grow a more competitive workforce, improve organizational effectiveness or identify potential issues and obstacles, this is the technology that can be the linchpin between it all. As businesses connect more expansive twin networks and build out this virtual infrastructure, the prediction and automation capabilities will gradually grow. In turn, HR leaders will be able to expand real-time agility at scale and usher in new innovation processes, all the while working out the kinks beforehand. “Initially, it will be hard to convince customers they need a digital twin that your brand stores and that the customer should help create it to improve their experience,” said Jonathan Moran, head of MarTech solutions marketing at SAS.

How Will Digital Twins of Customers Impact CX?

These digital twins are more in the engineering and design domain and answer “what-if” questions to assess feasibility before significant investments in building or acquiring physical systems. With digital twins, your engineers can determine the ideal design before the unit goes into production. Operations engineers can react to real-time product disturbances based on the deep insights gained during R&D. In other words, when it comes to providing a better overall customer experience, physical objects paired with digital twin technology are a perfect match.

There will be more use cases beyond maintenance for productivity, quality, supply chain and more. There have been many definitions of digital twins, each correct in its own context, as the concept means different things to different people. With iTwin Capture, users can take drone imagery or point cloud scans of infrastructure assets and start building digital twins directly off of these reality captures. In iTwin IOT, data from sensors and other Internet of Things devices mounted on infrastructure assets or at jobsites can flow directly into the iTwin platform, granting the digital twin a more active role in safety and environmental monitoring. Using simulation to understand complexity creates opportunities to deploy the insights to your businesses’ advantage.

OpenAIs Fidji Simo: Key Life Pillars AI Can Benefit

Despite the huge surge of generative AI within online search, many people are still wary of the responses they’re receiving from AI. There’s the Rabbit R1, a small square gadget that costs $199 and uses an OpenAI model to answer questions, as well as the AI pin developed by Humane, which later sold to HP. While the agentic AI experiences are the exciting new capabilities, the AI-powered ease of use starts at the beginning, when users set up Intuit Enterprise Suite, migrating from QuickBooks or even just spreadsheets. The reality for many mid-market companies is that they want to utilize AI, but they don’t want to deal with the complexity.

Tech and VC heavyweights join the Disrupt 2025 agenda

In June, Intuit announced the debut of a series of AI agents designed to help small businesses get paid faster and operate more efficiently. An expanded set of AI agents is now being introduced to the Intuit Enterprise Suite, which is designed to help meet the needs of mid-market organizations. In addition to sharing AI triumphs, businesses also need to show what AI misuse and failures look like in order to educate employees on positive and negative emergent patterns in AI adoption. In 2004, Google surpassed Yahoo in market cap—just two months after its $23 billion IPO. Almost two decades later, Google seems to be facing a similar scenario. “I’m sure there’s PTSD,” prominent Silicon Valley PR leader Brooke Hammerling told Forbes.

What has changed related to technology during your time at Manulife?

By giving employees the context, time, and resources necessary to understand and effectively use this new technology, companies can close the AI knowledge gap and experience positive business outcomes. Compared to GPT-4o, the o1 models feel like one step forward and two steps back. OpenAI o1 excels at reasoning and answering complex questions, but the model is roughly four times more expensive to use than GPT-4o.

• The finance agent, for instance, can generate monthly performance summaries, potentially saving finance teams up to hours per month.
• Harrison says he’s in camp one and that camp two requires you to trust AI to make the right decision.
• Seek AI solutions that work within that complexity rather than demanding simplification.
• It reveals why mid-market AI requires fundamentally different technical approaches than those for either small businesses or enterprise solutions.
• When Google demoed it at I/O that year, the company had LaMDA speak from the perspective of the dwarf planet Pluto and a paper airplane.

In some ways, Strawberry was never going to live up to the hype. Reports about OpenAI’s reasoning models date back to November 2023, right around the time everyone was looking for an answer about why OpenAI’s board ousted Sam Altman. That spun up the rumor mill in the AI world, leaving some to speculate that Strawberry was a form of AGI, the enlightened version of AI that OpenAI aspires to ultimately create. But it broke down its thinking for me at each step of the way and explained how it considered all of these external factors, including costs, family time, and oven management. Fidji Simo, soon to be the new CEO of applications at OpenAI, laid out a memo on Tuesday explaining her perspective on the role of AI around the world. Coming to OpenAI after serving as Instacart’s CEO, she frames AI as a service for good, identifying six life pillars — knowledge, health, creative expression, economic freedom, time, and support — that can benefit from it.

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A supply chain that can’t course-correct midstream or personalize at the edge isn’t just inefficient—it’s invisible to the modern customer. Finally, AI—in this case, GenAI—can help supply chain leaders with simulations and strategic planning. Leaders can run multiple scenarios and see how different parts of the supply chain will react under certain conditions.

I mean, we already made one change to one of them to reflect what was happening in the environment. We really do feel like they will change and they will evolve over time. And that is part of our job, is to say, ‘Are these still right?

• In addition to sharing AI triumphs, businesses also need to show what AI misuse and failures look like in order to educate employees on positive and negative emergent patterns in AI adoption.
• Coming to OpenAI after serving as Instacart’s CEO, she frames AI as a service for good, identifying six life pillars — knowledge, health, creative expression, economic freedom, time, and support — that can benefit from it.
• But it broke down its thinking for me at each step of the way and explained how it considered all of these external factors, including costs, family time, and oven management.
• Gain insight from top innovators and thought leaders in the fields of IT, business, enterprise software, startups, and more.

That’s likely how most people in the industry are viewing o1, but not quite as the revolutionary step forward that GPT-4 represented for the industry. I also asked o1 to help me plan out a busy day at work, where I needed to travel between the airport, multiple in-person meetings in various locations, and my office. It gave me a very detailed plan, but maybe was a little bit much. Sometimes, all the added steps can be a little overwhelming.

Five years ago, Google had what could be considered a coming out party of sorts for the company’s artificial intelligence ambitions. That year at I/O, Pichai unveiled Duplex, a stunningly human-sounding AI service that could book restaurant reservations for users. The AI was programmed to sound like a person by mimicking verbal tics like “um” and “uh,” taking long pauses and modulating its voice.

Jeff Dean, head of Google Research, later admitted that the company’s AI unit took a “reputational hit” because of the episode. In the balance is Google’s famous search engine, with its sparse white homepage, one of the most iconic pieces of real estate on the internet. Altering it drastically could affect the advertising revenues (at least in the short term) that have made the company one of the most valuable of all time. But to take back its AI mantle, Google may have to change the very nature of what it means to ‘google’ something.

World’s first AI real estate agent has already made $100M in sales

As it did for so many others, the short-term rental industry’s technological advancement exploded during Covid-19, and we had to find new ways to meet quotas and satisfy a new range of customer needs. Thankfully, as technology stepped in to provide many of those answers, AI, being part of that range of solutions, brought even more to the table, providing higher levels of operation and customer satisfaction than ever experienced. The process continues to be dominated by stagers, photographers, marketing agencies, and human virtual staging providers—leaving sellers to shoulder the cost, time, and coordination.

• Automated document management software powered by AI can help real estate teams make more informed decisions faster while reducing the time spent on manual review with minimal human error.
• According to Crunchbase, it received its seventh round of funding at the beginning of 2022.
• Now homeowners are watching their property values drop, sometimes drastically.
• Given the multitude of multifamily properties and separate rental agreements, organizing this disparate data can be challenging and time-consuming.

In today’s fast-changing business technology landscape, understanding the differences between AI agents and traditional software is essential. Organizations aiming to optimize operations are finding that AI agents offer adaptive, efficient, and integrated solutions, standing apart from conventional software applications. The technology will automate mundane tasks like data entry and posting listings to the Multiple Listing Service, Linsell said.

Those unwilling to embrace and adopt these cutting-edge tools will likely be left behind. With AI, buyers can search for properties by describing their dream home using ChatGPT or sharing images, rather than using traditional filters on platforms such as number of bedrooms and bathrooms, McLaughlin says. It could also identify neighborhoods or properties that buyers may not have discovered otherwise. Sellers can use AI to help compare the cost and estimated return of presale renovation projects. And some brokerages are utilizing it to review agents’ past transactions and see what steps they took that generated more sales or higher profits, McLaughlin says.

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Advancements in AI have led to a surge of real estate companies looking to capitalize on the new technology. The redesigned pages will display overall and category-specific ratings, meaning hosts must pay attention to every part of their presentation and process. It’s not solely about how attractive the property is or how idyllic the location is, but also how customer service incidents are handled and resolved and what those customers genuinely feel about their stay. Apart from pushing hosts to provide an experience that matches their claims and listings, these new badges will further gamify their marketing processes. Collov AI is also planning to launch new features to support listing prep—from generating social media posts and listing videos to one-click property websites—helping sellers market listings faster and more effectively.

Streamlined Property Management

At the same time, modern consumers expect more from every penny they’re willing to part with, and with competition as it is, they’re getting it. The customizable AI bots created with eSelf AI’s platform have been adopted across various industries, including education, customer service, and real estate. Access to housing and equitable housing markets is important to society, which is why many governments implement stringent legislation around the buying and selling of property. Real estate agents, brokers and other industry professionals must be aware that they will be accountable if using generative AI puts them in breach of local laws and regulations. Real estate agents and other professionals in their industry are in the business of selling good old-fashioned solid bricks and mortar. As AI agents continue to evolve, they are set to redefine the landscape of business operations.

To be clear, the vast majority of agents in Southern California still conduct business the old-fashioned way. But the ones trying new things are often doing so in order to make a living. According to Crunchbase, it received its seventh round of funding at the beginning of 2022. Investors include Kleiner Perkins, Blackstone Group, Goodwater Capital and Dawn Capital, among others. “We believe agents should focus on selling, not photo editing,” said Xiao Zhang, co-founder and CEO of Collov AI, who holds a Ph.D. from Stanford. Shoppers are able view photos, videos and floor plans of new homes and can add what they like to their collection.

Some are outsourcing the work overseas, and others are turning to AI or automation in a last-ditch attempt to find a seller. As for hosts, they’ll need to accept where they’re failing and work to rectify those issues instead of hacking their review process. For their visitors, this should hopefully translate into walking straight into the high-quality stay they expect instead of a disappointing, over-optimized marketing ploy. Now, earning the “guest favorite” badge will show which properties are in the top 25% of listings and also the top 1%.

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No one can predict the future, but AI can analyze past data to make educated guesses about the future. For commercial real estate owners, maintenance can be a major financial cost but also a problem area for tenant satisfaction. Broken elevators, busted water pipes and clogged HVAC vents create maintenance chaos if not managed properly. AI-powered virtual staging is no longer a nice-to-have—it’s a must-have for professionals who want to move faster, stand out online, and provide greater value to clients. We’re not only leveraging AI to make better decisions, but also to reduce time and cost in real estate investing. I’ve found that embracing a human-AI partnership—in which human, investor expertise complements AI’s intelligent capabilities—is the best way forward for the commercial real estate sector.

Bret Baier’s DC House Sells for Record $25 Million—in Cash

Advocates say real estate professionals need to get on the AI bandwagon or risk getting left behind. Despite the fears, advocates say the new tools make it easier to focus on the jobs humans do best — spending time with clients, holding their hands when they’re nervous, explaining the details of a contract. Morgan, however, doesn’t anticipate an increase in fake listings on Bright’s platform, because its listing add-edit process requires final approval from an agent or team member before it’s published. Lenders have used AI for nearly 30 years for automated underwriting, according to the Mortgage Bankers Association. And new AI tools such as fraud prevention, next-generation chatbots, back-office automation, and document recognition are being evaluated, says Rick Hill, the MBA’s vice president of industry technology. “I have heartburn because my daughters may want to become agents someday and I don’t know how much all the disruptions in real estate will change things in the next ten to 20 years,” says Leigh Reed, an agent with Long & Foster in Bethesda.

DatologyAI is building tech to automatically curate AI training datasets

The issue, as several lawsuits argue, revolves around whether the bots make fair use of the material by transforming into something new, or whether they just memorize it whole and regurgitate it, without citation or permission. Harvard’s new AI training collection has an estimated 242 billion tokens, an amount that’s hard for humans to fathom but it’s still just a drop of what’s being fed into the most advanced AI systems. Facebook parent company Meta, for instance, has said the latest version of its AI large language model was trained on more than 30 trillion tokens pulled from text, images and videos. “A lot of the data that’s been used in AI training has not come from original sources,” said the data initiative’s executive director, Greg Leppert, who is also chief technologist at Harvard’s Berkman Klein Center for Internet & Society. This book collection goes “all the way back to the physical copy that was scanned by the institutions that actually collected those items,” he said.

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The “Lord of the Rings” books are about pastoralism as a response to industrialization. “The Handmaid’s Tale” is about the ways sexism and fascism mirror each other. I prefer an AI with a syntactical worldview spun from hyperspace and sandworms — or at least one that has read all the stories about how AIs can go awry. That said, I’d sure like to see a more diverse canon represented. Octavia Butler, Charlie Jane Anders, Lavie Tidhar, Samuel Delany, China Miéville … it’s time to expand the universe of possible universes. The question of what’s on GPT-4’s reading list is more than academic.

Many bot companies assume that you know what your customers want and that if you don’t it is your problem to figure it out. However, a tool that analyzes customer questions in real time is a key piece of any bot solution. The analysis will tell you what your customers actually want to do with your bot and will let you focus your training efforts where it pays the biggest dividends. This is the step in determining bot priorities relative to customer needs, and it is the most important part of any bot training framework. This is what many bot companies are pitching as the entire training program, when it is really only the first step of a real training plan.

• If you have a more complex business and are using your bot for customer service, you should plan to invest considerable effort in ongoing training.
• But some — for governance and compliance reasons or otherwise — are building models on custom data from scratch, and spending tens of thousands to millions of dollars in compute in order to train and run them.
• When the company first reached out to the Boston Public Library, one of the biggest in the U.S., the library made clear that any information it digitized would be for everyone, said Jessica Chapel, its chief of digital and online services.

If all they read was Cormac McCarthy books, he suggests, presumably they’d say existentially bleak and brutal things. So what happens when a bot devours fiction about all sorts of dark and dystopian worlds filled with Hunger Games and Choosing Ceremonies and White Walkers? “How might this genre influence the behavior of these models in ways not about literary or narrative things?” Bamman says.

“That ability to rapidly build off of what other people have built was a really important component of the whole web. That doesn’t exist for bots yet,” he continues, which is why he founded Seed Vault — a decentralized marketplace for conversational user interface development. In addition to the modern public-school canon — Charles Dickens and Jack London, Frankenstein and Dracula — there are a few fun outliers. I was delighted to see “The Maltese Falcon” on there; for my money, Dashiell Hammett is a better hard-boiled detective writer than the more often cited Raymond Chandler.

ChatGPT’s secret reading list

We serve over 5 million of the world’s top customer experience practitioners. Join us today — unlock member benefits and accelerate your career, all for free. Our sister community, Reworked, gathers the world’s leading employee experience and digital workplace professionals. And our newest community, VKTR, is home for AI practitioners and forward thinking leaders focused on the business of enterprise AI. Google spent years beating back legal challenges from authors to its online book library, which included many newer and copyrighted works.

What is the proper name that fills in the MASK token in it? This name is exactly one word long, and is a proper name (not a pronoun or any other word). One way to answer the question is to look for information that could have come from only one place. When prompted, for example, a GPT-3 writing aid called Sudowrite recognizes the specific sexual practices of a genre of fan-fiction writing called the Omegaverse. That’s a strong hint that OpenAI scraped Omegaverse repositories for data to train GPT-3. The chatbot’s GPT-4 version was amazingly accurate about the Bennet family tree.

The Silmarillion. Really?

Supreme Court let stand lower court rulings that rejected copyright infringement claims. The case adds to a growing spate of incidents, from spreading misinformation to generating misleading, offensive or harmful outputs, and underscore the need for regulation and ethical guardrails in the dizzying race for AI-powered solutions. It’s an impressive list of AI luminaries to say the least — and suggests that there might just be something to Morcos’ claims. Biases emerge from prejudicial patterns concealed in large datasets, like pictures of mostly white CEOs in an image classification set.

DatologyAI is building tech to automatically curate AI training datasets

The largest concentration of works is from the 19th century, on subjects such as literature, philosophy, law and agriculture, all of it meticulously preserved and organized by generations of librarians. Wysa co-founder Aggarwal emphasizes the importance of creating a safe and trustworthy space for users, particularly in sensitive domains like mental health. “Each time an LLM generates a word, there is potential for error, and these errors auto-regress or compound, so when it gets it wrong, it doubles down on that error exponentially,” she says.

If you are delivering the wrong answers more than 3 percent of the time, your system should be taken back to the drawing board. The book collection is more linguistically diverse than typical AI data sources. Fewer than half the volumes are in English, though European languages still dominate, particularly German, French, Italian, Spanish and Latin.

“Hurricane” and “wildfire” might not be at the top of any cell phone provider’s training list, but had Verizon’s chatbot not recognized the words, the company would have seemed unfeeling and out of touch. Even if you have a simple pizza-ordering bot, you’re going to have to continuously learn from your customers how they want to order and add new platform support and new products. If you have a more complex business and are using your bot for customer service, you should plan to invest considerable effort in ongoing training. “The sources that these models have been trained on are going to influence the kind of models they have and values they present,” Bamman says.

Considering IVR is probably the most-hated piece of technology invented in the last 50 years, replicating that process is probably not a great idea. So you’re thinking of implementing a chatbot, like every other company on the planet. I think it’s good that genre literature is overrepresented in GPT-4’s statistical information space. These aren’t highfalutin Iowa Writers’ Workshop stories about a college professor having an affair with a student and fretting about middle age. Genre — sci-fi, mystery, romance, horror — is, broadly speaking, more interesting, partially because these books have plots where things actually happen. Bamman’s GPT-4 list is a Borgesian library of episodic connections, cliffhangers, third-act complications, and characters taking arms against seas of troubles (and whales).