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Ansys says simulations will close the gap with reality and make the world more sustainable

You may not have heard of Ansys, but it’s in the process of being acquired by chip design tool firm Synopsys for $35 billion.

That’s happening because Ansys, an engineering software corporation, specializes in the simulation of the world’s complex electronic systems, and the world of chip design is increasingly moving into the more complex world of system design, showcased Prith Banerjee, CTO of Ansys, in an interview with GamesBeat.

Ansys spans a lot of businesses. It works in the automotive space with carmakers (original equipment manufacturers, or OEMs). It works with the tier one suppliers in the car industry, and it works with chip companies that are making chips for the cars and more. Ansys makes tools for engineering simulations and more, expressed Banerjee. And he noted that companies all over the world are embracing AI and machine learning. He can see it in his clients’ simulations.

“With AI and ML, we are able to use simulation much easier as well as much faster. Something that takes a hundred hours to run can run in a matter of minutes, so we have got some techniques to aid us in that area,” Banerjee mentioned. “AI was big in general at CES. I mean Jensen (Huang, CEO of Nvidia) talked about AI and all the GPUs and so on, but we are embracing AI like never before.”.

Ansys simulation tools help companies design race cars.

Ansys is working with a lot of companies. At CES 2025, it unveiled a collaboration with Sony Semiconductor Solutions to improve perception system validation in smart cars. Ansys’ solutions are used by more than 200 automotive and tech companies that show off stuff in Las Vegas each January. Every year, Ansys tries to close the gap between engineering design and reality using the power of simulation.

It creates virtual wind tunnel technology to optimize F1 racing car designs with Oracle Red Bull Racing, Porsche and Ferrari.

Increasingly, this simulation superpower also speeds time-to-market, lowers manufacturing costs, improves quality, and decreases risk.

LightSolver, another Ansys partner being presented today, says that the fourth industrial revolution, also known as Industry [website], is fully underway. Almost every industry — from automotive and aerospace to consumer goods and healthcare — is demonstrating a shift toward digitalization.

The industrial equipment and manufacturing industries are no exception. A global industrial robotics survey revealed that industrial companies are expected to invest 25% of their capital spending on automation from 2022 to 2027. The survey also found that automation is already being implemented or piloted for many popular industrial tasks, including palletization and packaging, material handling, goods receiving, unloading, and storage.

BMW is building a digital twin of a factory that will open for real in 2025.

Banerjee is excited about the tools like Nvidia’s Omniverse, which is enabling the creation of virtual designs known as digital twins. With such twins, companies like BMW are designing car factories in a virtual space of the Omniverse first. When the design is perfect, they build the factory in the real world. They outfit the factory with sensors that collect data and feed it back to the digital design. That makes the virtual design more effective and creates a feedback cycle of continuous improvement. That means that the simulations of everything from Microsoft Flight Simulator to the car factories are getting closer to real life.

“Digital twins as a topic is very big for us. Of all the conversations that I had with all clients, we talked most about our concept of hybrid digital twins the most,” Banerjee noted. “The rest of the industry is doing digital twins by putting sensors on the actual assets, right? You’re making a digital model of the asset by just putting in sensors. And we’re using data analytics. What we do in terms of digital twins is physics-based, simulation-based digital twins.”.

Banerjee added, “We combine it with data analytics to do what is called hybrid digital twins. Sustainability is big for us. So we are driving a lot of things around how to make the world more sustainable, lower carbon emissions using simulations.”.

Asked about whether Ansys would like to see more of Nvidia’s digital twin technology as open source, Banerjee mentioned he would like to see open standards in the ecosystem.

“The faster this whole thing comes, the bigger the opportunities for everyone,” he stated. “It doesn’t help anyone to have four different standards.” No one wants to be tied to a single GPU or a single software stack.

Nvidia is bringing OpenUSD to metaverse-like industrial applications.

Banerjee noted the metaverse is real, as many companies are taking it seriously beyond Meta. He noted those include Amazon Web Services, Microsoft, Google and Nvidia.

“They all have some form of the metaverse. So we believe that the metaverse is real, that that is going to happen. And we, as the leading simulation enterprise, need to integrate with the metaverse,” Banerjee noted. “And what is it? The metaverse allows you to combine the physical world with the virtual world, which is the concept of digital. For example, what we bring to the Omniverse from Nvidia is that they have got a solution, a stack.

He added, “The are using their simulators like Isaac, simulating robots and so on, right? But their simulations are kind of at a high level, an approximate simulation. They say it’s a physics-based simulation, but it’s not the level of accuracy that we bring to the table.”.

He mentioned that Ansys is focused on physics-based simulations, and the enterprise’s work revolves around core physics solvers. These cover mechanical structures, fluids and electromagnetic areas.

“These are the four core solvers. We are in discussions with Nvidia and we have an active partnership going on to take each of the solvers to visualize the output so the engineer will see the output on the desktop as it is happening,” Banerjee expressed.

He mentioned the world is moving to the cloud the world and AI. In that new world of AI plus cloud plus GPUs, the metaverse is the right way to do the user interface and interact with the results of simulation.

“We are working hand-in-hand with Nvidia to make sure our four core solvers are integrated with the Omniverse. So that’s one very core area of collaboration,” he stated.

Asked what he means by hybrid digital twins, Banerjee presented he used to be the CTO at a couple of other large industrial companies. He was CTO at ABB, a power and automation organization in Switzerland. And he was also CTO at Schneider Electric, a power and automation organization based in France.

In those roles, he saw that large industrial companies have lots of large assets. The assets can be transformers, robots or switch gears. And these assets are there for a long time.

“What you try to do is to see to see when that asset fails. Say a million dollar transformer fails, and when it does, you lose power and that’s bad for the environment and people. So what you try to do is put sensors on these assets to see if my transformer working or not,” he expressed. “And so before the transformer fails, it starts giving signals. So just like the human body, we have the normal things like our temperature. But before we fall sick, the temperature goes to 99. 100, 101 and then you get the fever and then it’s really pulsing. So before you really fall sick, you start giving signals. The same analogy works for digital twins.”.

A virtual wind tunnel used to help design a race car.

He added, “So you put sensors, collect data and before that asset fails, it starts giving different signals. So if you monitor the changes, you can predict that it’s going to fail. This is how when I was at ABB and Schneider Electric and again all the other companies like Caterpillar or GE and everybody, all these companies, they use digital twins using data analytics. So if they pull the data and they look at here’s the normal behavior and notice the abnormal behavior. And then based on the abnormal behavior, you see it’s going to fail.”.

He continued, “Now, what I found out when I was at ABB and Schneider is the accuracy of that prediction is based on pure data analytics at about 70%. And you say, oh, 70% is pretty good. Well, if you have a million-dollar part and you are 70% accurate, that means you made a 30% error. So you made an error to replace a part with a 30% probability. You just made a $300,000 mistake. You made a decision which was wrong because your accuracy was only 70%. So this was the problem I was facing when I was at Ansys.”.

Banerjee noted he always knew that if you could tie that to physics-based simulation, the accuracy would go up.

“I joined Ansys about six, seven years ago and I told my CEO, I introduced, this is the problem that we need to solve. If you could solve it through physics-based simulation, that would be absolutely amazing. So physics-based simulation says, “Here is a transformer, here is a robot, here is whatever, right? And you go back to the basic physics. This is how the transformer works, right? It is electrical, it signals going through the coils and is generating this and if there is a cut in the coil, right, those electrical signals, the mechanical signals will not come. That’s why the failure happens. Let’s go back to the first principles of the physics. So at Ansys, we did physics-based digital twins and simulation. The accuracy went from 70% to 90%.”.

He noted, “You say, ‘Wow, 90% is great.’ But with that million-dollar part and 90% accuracy, you’re still making a $100,000 mistake. So then we noted, what if you could combine the two? Combine the data analytics-based digital twins with the physics, and that is what we did called fusion technology, or a hybrid digital twin, which is now called a product called Twin AI.”.

“The accuracy of that combination is 99%. So on that million-dollar part, I will only make a $1,000 mistake. So our clients are super excited,” he noted.

“At CES, I talked to many consumers about our Twin AI technology, digital twin technology that works at the system level. We could build a digital twin of an entire car or a subsystem. You can take an EV car, break it down into different components of power electronics — the battery the drive train or inside the battery. We can keep going down and down now and build digital twins of the system, the subsystem, the components. But at every level, if there are sensors, we can actually build this fusion-based digital twin, this sort of hybrid digital twin. That is an absolutely amazing technology, and this is something I’ve been proud of.”.

The intersection of simulation, game worlds and the real world.

Microsoft Flight Simulator 2024 simulates the African savannah because it can.

I noted how there’s an intersection of simulated worlds and game worlds and the real world with products like the game, Microsoft Flight Simulator 2024. The 2024 game had 4,000 times more detail on the ground than the 2020 version. It enabled them to do amazing simulations like using a helicopter to herd a flock of sheep on the ground.

They added gliders to the game and that meant you could land anywhere, so they needed well-simulated places where you could land just about anywhere on the planet. They enlisted aircraft manufacturers to give them CAD models of the designs for aircraft in the game, and they pulled camera video footage from the planes after they flew over parts of the planet. My question was whether we would ever get to one-to-one accuracy between simulation and reality.

“So that’s a great question. So let me take a step back and give you the approach to simulation that we use. In our world of computer-aided engineering simulation, CAE simulation, we take the world around us which is governed by the laws of physics. Physics doesn’t lie, right? When in the world of fluids, there’s an equation called Navier Stokes equation. These are second order partial differential equations. That is the equation that is the way nature works. So we take those equations, and we solve them numerically.”.

He added, “Now when you solve it numerically you can take a particular type. You can break it up into four quadrants or more. Four or 16 or 32. The more elements I have, the more accuracy I get.”.

And he stated, “The trouble is, as you add more elements, more accuracy, your runtime goes out the window. Because runtime is sort of N cubed, right? So the number of elements, it’s N cubed. So this has been the challenge in our industry. With CAE simulation, you can absolutely get more accuracy, but your runtime increases. So how do you get more accuracy faster?”.

As CTO at Ansys, Banerjee has multiple technology pillars. There are advanced numerical methods where you’re looking at just the algorithm itself on a single processor, making it go faster, more accurate, and so on. The second thing is using HPC, high-performance computing.

“You have a thousand hours of work to do. I have a hundred processors, and I’ll give them to you to run much faster just by adding parallelism to it,” he presented. “That’s why GPUs come in the partnership with Nvidia, helping us to take a fixed amount of work using GPUs to make it run much faster right with the same accuracy.”.

The third focus is AI, where the enterprise is training those its four core simulators. Once trained, the AI model runs 100 times faster.

“In the world of digital twins, we have actually taken all those technologies, GPU, HPC technology and AI technology, and we call that reduced order models, ROMs, and it’s because of Ansys’ leading position in the area of reduced order models and AI cost simulation.

Simulations can reduce the risks of maintenance failures.

The simulation market is around $10 billion today and it’s growing around 12% a year.

If you look at the entire R&D budget across all industries in the world, it’s about $[website] trillion dollars, Banerjee said. In the automotive industry, the R&D is about $250 billion. About 75% of that cost is banging up cars in “physical validation” of the vehicles. It’s physical prototyping, he said.

“What we believe is that the simulation becomes so accurate and so fast that companies will stop doing physical programming,” Banerjee stated. “In fact, the CEO of GM has stated that by 2035, GM will stop doing physical programming if everything will be virtual. So simulation is growing at 12% today. But once those use cases come in, there will be a hockey stick event.”.

The complexity of chip design and the coming of systems design.

Banerjee noted that one reason that Synopsys is acquiring Ansys for $35 billion in cash and stock is that the world is moving from chips to systems when it comes to design.

“You have electronic chips that were designed with tools from Cadence and Synopsys and Mentor Graphics, but they’re only building the chip inside a system. So it’s going inside a car, right? But now you are going from chips to systems and the opportunity for simulation to design these really complicated chips to systems is enormous. It’s powered by GPUs, powered by the Omniverse, powered by AI. I am very excited about the future of simulation and synthesis for the vision of chips to systems across industries like automotive, aerospace, energy, high tech and healthcare. These are the five verticals that I we look at in terms of the opportunity to move from chips to systems.”.

Banerjee has worked in the electronic design automation (EDA, or using software to automate chip design) for more than 20 years. He spent his first 20 years in academia, building EDA tools. Forty years ago, he had to teach VLSI design by drawing rectangles on the screen, which is now called Custom IC. Then the whole design industry moved. Chips had perhaps 10,000 transistors, which was pretty hard for engineers to process. Then each progressive improvement, from standard cells to Synopsys’ synthesis, the level of complexity of the designs improved. Now chip designers can create 200-billion transistor chips.

“My projection is that we could do a similar thing with synthesis tools for systems. Can you have a synthesis tool for a system as complicated as an automobile or an airplane? Today, it is done. You look at a specification and a human designer goes and does the CAD of the airplane engine,” he stated.

He added, “I am saying at some point in the future you will not have to do the CAD. It will be synthesized, right? Just like we use synthesis tools for chip design, there will be system level synthesis tools. Now this is like I’m talking five to ten years out. We have got things going on at Ansys, but that’s the opportunity. Once that happens, the design of the systems will be accelerated by many factors.” So you could do a thing like a 200 billion transistor chip, right? It’s something much more complicated than what you can do. And as the automotive companies are struggling to reduce that design time from four years to two years to whatever, could you imagine a new car design coming out in a matter of a month? Yeah. that can be enabled by synthesis.”.

Credit: VentureBeat made with Midjourney V6.

I asked Banerjee what was the most complicated design possible. Is it the human brain? The human heart?

“I’m glad you mentioned the human heart. I will tell you, at Ansys, I am really passionate about the healthcare area and we in the CTO office are working on simulating the human body, the heart, the brain, the lungs and so on,” her noted. “That is just such a complicated thing that we live and breathe every day. Simulation of a human body accurately will enable us to come up with solutions to heart disease. When you have arrhythmia, you have irregular heartbeat. That can be treated through either you take a drug, AstraZeneca, and it will treat your [condition]. Or you take a pacemaker from Medtronic and that will take it. Or you do more jogging, right? Changing your behavior.”.

He revealed, “Each of these things. or you can do actually an operation, right? You go in and you insert a stent. We are imagining a future where each of these things can be simulated. Here is this cardiovascular drug. If I take that medication, will it interact with the molecules in the human body? If I put a stent in, what is going to happen? So imagine in the future you will not require what is called clinical trials. Everything will be done through simulation of a human body, right? Virtual humans. And that will accelerate the use of the discovery of drugs and discovery of medical devices.”.

The funding comes weeks after it raised INR [website] Cr ($[website] Mn) from its extended Series A funding round by issue of CCPS.

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Backed by €500K, Edmund brings AI to the factory floor to solve industry’s biggest data challenges

It's an uncomfortable truth, but the hype of Industrie [website] failed to reach its potential.

In the 2010s, IoT was my beat as a journalist. I wrote at length about the promise and opportunity of Industrie [website], especially in manufacturing. Yet, it didn't wholly lead to the predicted success. Despite the promises of data-driven benefits such as predictive maintenance, it suffered from high costs, (some) insecure tech, integration complexity and, of course, the infamous IT/OT divide.

Smart factories may have created a wealth of data, but it is often unstructured and resides in silos rather than leading to actionable insights.

, CEO and founder of Czech startup Edmund, "Predictive maintenance was a buzzword" with limited success in large, custom-built environments.

"A manufacturing line that costs 40 million euros is built by 50 people on-site. Predictive maintenance for this kind of technology is basically impossible." "If you ask any manufacturing CEO or technician if predictive maintenance helped them, they'll say: 'I don't know.' "Even fully automated manufacturing lines can have 20 downtimes or failures per day. Automation doesn't eliminate breakdowns—it just makes systems more complex."

Manufacturing is facing a perfect storm thanks to increasingly complex machinery and production lines, overwhelming amounts of data, and a growing shortage of skilled technicians.

This disconnect between human capabilities and machine complexity creates operational efficiency bottlenecks across industries.

Edmund specialises in AI solutions for manufacturing. It has closed a €500,000 pre-seed round for its AI-powered platform, which combines large language models with industry expertise.

From student project to industry game-changer.

Edmund was founded in 2023 by two engineering students, Jakub Szlaur and Benjamin Przeczek, and experienced project manager Miroslav Marek.

While studying, Jakub and Benjamin worked on real-world engineering projects at Ostrava's student hub. The idea for Edmund came during a sleepless night while Jakub was cramming for finals - he realised how LLMs could simplify complex technical problems. By the end of 2023, they had an MVP and a lucky break: an investor from Czech Founders VC, Ondřej Smikal, heard about them from his mother, a teacher at Batia University in Zlín. She'd seen their presentation and immediately told her son, "Ondřej, call these guys. They seem pretty cool."

Since then, they've joined the Sherpa accelerator at Czech Founders and landed their first consumers — all before fully launching their product.

One interface, endless Insights: How Edmund transforms industrial data.

"One of the biggest problems we see in the industry is data incompatibility. Operators, technicians, and maintenance workers have tens to hundreds of different systems connected together, with many interfaces they need to access to learn even the smallest information."

Edmund solves this by creating data parsers that pass unstructured data to AI, making it accessible through a single interface:

"We are creating these data pipelines that enable large language models to understand industry-specific data... so you have only one interface in your phone to your whole corporation."

By integrating real-time data, technical documentation, and control software, Edmund provides actionable insights directly to engineers and technicians, cutting troubleshooting times from days to minutes.

Significantly, unlike competitors such as Siemens Copilot, which are limited to their own proprietary systems, Edmund is universally compatible and can process diverse data formats from various manufacturers.

The platform also boasts more rapid onboarding, processing business data in just 24 hours to deliver an MVP-ready solution tailored to specific client needs.

"We're not just aggregating data - we're transforming it into meaningful, actionable insights that technicians can use immediately to solve problems. Manufacturing may look automated on the surface, but beneath that shiny exterior lies a chaotic complexity that Edmund is uniquely equipped to handle."

, the reality of the industry is that "the guy with the screwdriver is your most precious asset... If a machine breaks, somebody has to go there and repair it. It doesn't matter how many reports, charts, data, AI, digital things, predictive maintenance you have—if the machinery stops, all that goes out the window."

Edmund provides technicians with direct and simplified access to critical machine data instead of overwhelming them with unnecessary analytics.

Industry reports suggest nearly 50 per cent of Europe's engineers are expected to retire in the next 5-10 years, leaving a critical skills gap.

Edmund stands out is that the startup is led by engineers who work in manufacturing, as opposed to programmers.

"We see the demographic change in Europe. Each year, 200 IT students graduate, but only two actually go into industrial tech. Nobody wants to do it. It's a hard job."

He notes that experienced technicians are aging, while younger workers expect modern tools and home-office options.

"New technicians don't even use Google—they use ChatGPT. They expect AI-driven tools."

Szlauer is humble about his success, sharing, asserts: "I am not a startup guy... I'm lucky investors gave me half a million euros, but I am an engineer. And so are all the good people working at this."

He attributes their success to spending 12 months working directly with clients to identify real-world problems rather than pushing generic software solutions.

"It boiled down to really simple use cases. But the big software providers are creating more problems—more data, more complexity.

Further, the demand for in-house teams who understand how machines work will only increase.

"This is where Edmund will shine—when you use Edmund, it learns with you. So even when older engineers retire, the knowledge stays inside the system."

Edmund already signed four paying end-consumers, including industry leaders Festo and Vitesco Technologies, and have over 20 PoCs and demos running in Czechia and Slovakia. With funding secured, they're going to expand beyond Central Europe and explore a larger seed round in 2026.

Lighthouse Ventures led the funding with Czech Founders VC, Borovicka Capital, and deeptech investor Tensor Ventures joining.

, Managing Partner at LightHouse Ventures, Edmund combines artificial intelligence with practical expertise, delivering a solution that, thanks to its versatility and rapid deployment, has the potential to succeed not only in Europe but also in the US.

"Within its first year, it has already gained the trust of key European industrial players. It has all the prerequisites to become a global leader in maintenance."

The €500,000 raised will be directed toward finalising core functions of Edmund, expanding into US and international markets, and scaling Edmund's team.

In the next 6-12 months, Edmund aims to expand beyond Central Europe, targeting partnerships with global manufacturing leaders. The corporation is also exploring the possibility of a larger Seed round in 2026 to further accelerate growth and development.

Image: Edmund founders (L-R): Jakub Szlaur (co-founder and CEO), Miroslav Marek (co-founder and CSO), Benjamin Przeczek (co-founder and COO). Photo: uncredited.

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Apple launches ambitious health study to advance wellness tech

Apple in recent times launched its first pair of wireless earbuds with an integrated heart rate sensor. Down the road, this convenience will reportedly arrive on the AirPods family, as well. The uber popular earbuds have already landed their hearing aid clearance, alongside a slew of new wellness-centric elements.

The focus is clear. Health-tech is the next great avenue for innovation at Apple.

To that end, the business has just revealed the Apple Health Study, which aims to collect biomarker information and user inputs to connect the dots between sensor data and the current health status. Onboarding will happen via Apple’s Research app and the focus will be on US citizens who meet the age criteria.

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Apple will be working with Brigham and Women’s Hospital to understand how data collected by wearable devices can be used to predict, monitor, manage, and assess a person’s physical and mental well-being.

There’s plenty of precedent for such work. Researchers at the University of Barcelona lately showcased how smartwatch data can be used to predict psychiatric illnesses and trace them down to genetic roots. Experts at Tampere University have developed a framework that can analyze the ECG readings from a smartwatch and detect signs of congestive heart failure with roughly 90% accuracy.

Multiple doctors, including experts from the American Heart Association, not long ago told Digital Trends that smartwatches can play a complementary role in helping keep track of “healthy habits such as physical activity, heart rate during activity, and sleep habits in several ways.”.

Apple’s health study simply builds atop an unprecedented strength of its ecosystem. There are millions of individuals out there who rely on Apple devices, such as the Apple Watch and iPhones, for keeping track of their heart activity, sleep patterns, and workouts.

That massive pool of participants and data is a goldmine for more research, allowing scientists to develop new algorithms and frameworks to get the best out of biomarker data collected by wearable devices.

Apple says the study will broadly focus on “activity, aging, cardiovascular health, circulatory health, cognition, hearing, menstrual health, mental health, metabolic health, mobility, neurologic health, respiratory health, sleep, and more.”.

It is, owing to such studies, that the organization was able to develop attributes such as Walking Steadiness on iPhones and the Vitals app for its smartwatch. The organization says its new study will try to understand how body signals, both physical and emotional, are tied to the overall health of a person.

Of course, this is scientific research we are talking about, so it’s going to take a few years before the data collected as part of the health study will produce any remarkable findings, or new capabilities. Furthermore, validation and approval by regulatory authorities, both local and overseas, is a long drawn-out process.

Apple’s focus on tech-driven health and wellness is not odd. Back in 2019, CEO Tim Cook told CNBC that health would be Apple’s greatest contribution. In the years that have elapsed since, Apple has made some remarkable advancements, even though the competition has also matured a lot.

Monzo’s chief operating officer Sujata Bhatia is leaving the UK challenger bank after five years.

Bhatia presented on LinkedIn that she is.

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The appointment strengthens Bay Capital's advisory board which includes experts like Prof. Russell Napier and Preston Hutchings.