Technology

Vizrt, a media technology company, has introduced a new AI-powered tool to simplify the creation of virtual scenes in live production. Its latest release, the AI Keyer, is built around a simple idea: remove the need for green screens and make virtual production possible in almost any environment.

Traditionally, creating virtual backgrounds or augmented reality (AR) scenes requires controlled studio setups, green screens, precise lighting and skilled operators. That makes high-end visual production expensive and difficult to scale, especially for smaller teams or live, on-the-ground reporting.

The AI Keyer is designed to address that gap. It uses AI trained on real-world footage to identify people in a frame and separate them from the background in real time. This allows production teams to replace backgrounds, insert AR graphics or place presenters into virtual environments—whether they are indoors, outdoors or on location.

"Creating XR environments typically demands large infrastructure investments and requires specialized skills for daily operations. The Vizrt AI Keyer removes all these constraints, so high-quality virtual scenes and AR graphics become a reality for live productions of every size", says Edouard Griveaud, Senior Product Manager at Vizrt.

In practical terms, this means a presenter can appear in a different location without moving, a remote speaker can be placed inside a virtual event space or branded graphics can be added to live interviews without a complex setup. The system works without chroma keying, reducing both preparation time and production overhead.

This shift also reflects how the company is approaching AI more broadly. Instead of treating it as a background feature, Vizrt is positioning AI as a core part of the content creation and delivery process.

"AI is transforming the world, and the creative industries are no exception. At Vizrt, we have been on this journey for years, embedding intelligence into our solutions, empowering storytellers and delivering real, measurable impact for our customers", says Rohit Nagarajan, CEO of Vizrt. "That is not a vision for tomorrow. That is happening today. The Vizrt AI Keyer is the latest proof point of our relentless commitment to innovation. Putting breakthrough technology in the hands of every creative, at every level, everywhere in the world".

Beyond the product itself, the direction is clear. By removing the need for green screens and complex setups, tools like the AI Keyer make it easier to produce high-quality visual content in more flexible settings. The result is a production model that is less tied to physical studios and more adaptable to real-world environments, where content can be created and adjusted in real time.

DeepCyte, a startup in the drug development space, is focusing on a long-standing problem: why drugs that appear safe in early testing still fail in clinical trials or are withdrawn later due to toxicity. DeepCyte has launched with US$1.5 million in seed funding to build tools that detect and explain the harmful effects of drugs at much earlier stages.

The startup’s approach focuses on how individual cells respond to a drug. Instead of analysing cells in bulk, it studies them one by one. This helps capture differences in how cells react, which are often missed in traditional testing methods.

Drug toxicity remains one of the main reasons for failure in drug development. Methods such as animal testing and bulk cell analysis do not always reflect how human cells behave. This gap has pushed the industry to look for more reliable and human-relevant ways to test drug safety.

DeepCyte combines cell-level data with artificial intelligence. Its platform, MetaCore, studies what is happening inside individual cells by capturing detailed molecular information. This data is used to build large datasets that can train AI models.

Additionally, the company has developed an AI system called DeeImmuno. It is designed to predict whether a drug could be toxic and identify the biological reasons behind it. In internal testing on 100 drugs, the system identified different types of toxicity and their underlying mechanisms with a reported accuracy of 94 percent.

The focus on explaining why a drug is toxic, not just whether it is, reflects a broader shift in the industry. Regulators such as the U.S. Food and Drug Administration and the European Medicines Agency have been encouraging methods that rely more on human cell data and clearer biological evidence. The seed funding will be used to develop and scale these tools. The company aims to help drug developers make earlier decisions, which could reduce costly failures in later stages. Whether tools like this become widely used will depend on how they perform in real-world settings. For now, DeepCyte’s approach highlights a growing effort to make drug testing more precise by focusing on how drugs affect cells at the most detailed level.

A newly built district in northern China is being used to test how cities function when infrastructure, data and automation are integrated from the ground up. In Xiong'an New Area, traffic systems, public monitoring and urban services are designed to respond in real time rather than operate on fixed rules.

At the centre of this is a traffic management system powered by more than 20,000 roadside sensors. These track traffic flow, vehicle types and congestion levels, feeding data into an AI system that adjusts signals in milliseconds. Official figures show this has reduced the average number of stops per vehicle by half. The system also detects equipment faults, sends alerts and generates maintenance requests without manual input.

Automation extends beyond roads. Drones are deployed across the city for routine monitoring. In the Rongdong district, roadside units release drones that follow fixed patrol routes of around 1.27 kilometres, completing each run in about five minutes. They are used to monitor traffic, detect illegal parking and inspect public spaces. Similar systems operate in parks to track water levels and issue flood alerts, while in some work zones, drones transport packages of up to five kilograms between buildings.

These applications reflect a broader approach: integrating multiple systems into a single, connected urban framework. Unlike older cities where infrastructure evolves in layers, Xiong’an has been built with coordinated digital systems from the outset. This allows transport, maintenance and public services to operate through shared data systems rather than in isolation.

Alongside this, the area is being developed as a technology and innovation hub. Since its establishment in 2017, it has attracted more than 400 branches of state-owned enterprises and over 200 companies working in sectors such as artificial intelligence, aerospace information and digital technology.

This ecosystem supports projects like the “Xiong’an-1” satellite, which completed research, design, production and testing within eight months of regulatory approval in 2025. The satellite is currently undergoing testing, with a planned launch expected in the second quarter of 2026. It forms part of a broader push to build an aerospace information industry in the region.

The area is also structured to bring companies, research and production closer together. At the Zhongguancun Science Park in Xiong’an, which spans 207,000 square metres, 269 technology companies operate across sectors including AI, robotics and biotechnology. The park hosts more than 2,700 researchers and industry professionals, with companies organised into sector-specific clusters.

Policy support continues to shape this development. In early 2026, the State Council approved the upgrade of Xiong’an’s high-tech industrial development zone to national level status, with a focus on attracting high-end research and strengthening links between scientific development and industrial output.  

Xiong’an is positioned as a testing ground for how smart city systems can be deployed at scale. The model depends on coordinated planning, integrated infrastructure and sustained policy support. Whether these systems can be adapted to existing cities, where infrastructure and governance are more fragmented, remains an open question.

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The China International Medical Equipment Fair 2026 will open in Shanghai from April 9 to 12 at the National Exhibition and Convention Center. It is one of the largest gatherings in the medical device industry. This year’s edition will cover more than 320,000 square metres. Nearly 5,000 companies and brands are expected to participate, representing over 20 countries and regions. Organisers also expect more than 200,000 professional visitors and buyers from around 150 markets.

A key focus this year is the growing use of artificial intelligence in healthcare. One of the headline technologies is an AI agent designed to carry out multiple diagnoses from a single scan. The exhibition will also feature diagnostic software that is already in clinical use. In addition, an integrated platform for AI training and inference will be showcased to improve computing capacity within healthcare institutions.

Robotics will also play a central role at the event. New systems across surgical procedures, rehabilitation and elderly care are expected to be presented. Together, these developments point to a steady move toward more precise and assisted forms of care. Many of these technologies are designed to support clinicians and patients, especially in tasks that require consistent accuracy or long-term physical assistance.

For the first time, the event will introduce a dedicated Future Tech Arena. It will focus on brain-computer interfaces, embodied intelligence and university-led innovation. The space will include AI-assisted MRI systems for Alzheimer’s diagnosis. It will also feature brain-computer interface technologies used for cognitive assessment and training, along with wearable robotic exoskeletons.

Alongside product showcases, the event will continue to act as a platform for international trade and collaboration. An International Zone will host exhibitors from countries such as the United States, Germany, Japan, South Korea, the United Kingdom, France, Singapore, Malaysia and Thailand. This provides a view of how different markets are approaching medical technology. It also reflects the global nature of innovation and deployment in this sector.

The programme will include a set of networking and exchange formats under its “We” initiative. These include discussion stages with representatives from consulates and industry organisations, as well as matchmaking sessions based on verified buyer demand. Guided tours will also be organised to help international visitors connect with relevant exhibitors. In parallel, organisers are working with hospital partners to provide medical support services for attendees during the event.

Across the four days, hundreds of forums are scheduled. These will bring together policymakers, researchers and industry leaders to discuss regulatory frameworks, market access and the future of healthcare innovation. Some of these sessions will be led by the Global Harmonization Working Party in collaboration with the Ministry of Health of Malaysia, with a focus on regulatory alignment and cross-border cooperation in medical devices.

As healthcare systems continue to adopt digital tools and advanced equipment, events like CMEF provide a clear view of how these technologies are being developed and applied. The scale of participation this year reflects continued activity across both innovation and international collaboration in the medical device sector.

As the FIFA World Cup 2026 approaches, attention is beginning to shift beyond the matches themselves to how an event of this scale is organised and run. Managing teams, coordinating venues and handling large crowds requires a system that works with precision. This time, robotics is set to become part of that system.

Hyundai Motor Company, a long-time FIFA partner, is expanding its role for the 2026 tournament. Alongside its traditional responsibility of providing vehicles for teams, officials and media, the company will introduce robotics in collaboration with Boston Dynamics. Robots including Atlas and Spot are expected to be deployed at selected venues.

According to the announcement, these systems will be used to support tournament operations while contributing to safety and efficiency. They will also play a role in shaping how fans experience the event, indicating a broader use of technology within the tournament environment. While specific use cases have not been detailed, the inclusion of robotics reflects a growing effort to integrate advanced systems into large-scale public events.

The direction was introduced through the company’s global campaign, “Next Starts Now,” unveiled at the 2026 New York International Auto Show. The campaign is positioned around its wider focus on innovation across mobility and robotics, aligning with its long-standing partnership with FIFA, which now spans more than two decades. As part of the 2026 tournament, the company will also deploy its largest mobility fleet to date, working alongside these newer systems across venues.

Beyond operations, the initiative extends into community engagement. Youth football camps are set to take place across four host cities in the United States—Atlanta, Miami, New Jersey and Los Angeles—targeting children between the ages of six and twelve. A global drawing programme will also invite young fans to submit artwork supporting their national teams, with selected designs to be featured on official team buses during the tournament.

Taken together, the introduction of robotics alongside existing infrastructure points to a gradual shift in how major events are supported. Rather than operating only behind the scenes, technology is becoming more visible within the event itself. How these systems perform in a live, large-scale setting will become clearer once the tournament begins.

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As artificial intelligence makes it easier to write code, a different problem is starting to surface. Building software is no longer limited by technical skill alone. Increasingly, the challenge lies in deciding what to build, how to structure it, and how to turn an idea into something that actually works.

That shift sits at the centre of BrainGrid, a startup that has raised $1 million in pre-seed funding led by Menlo Ventures, with participation from Next Tier Ventures and Brainstorm Ventures. The company is building what it describes as an AI-powered planning layer for people who want to create software but may not have a technical background.

The timing reflects a broader change in how products are being built. Tools like Claude Code and Cursor have made it possible to generate working code through simple prompts. For many first-time founders, this has lowered the barrier to entry. But writing code is only one part of the process. Turning that code into a reliable product requires structure, sequencing and clarity—areas where many projects begin to fall apart.

In traditional teams, this responsibility sits with product managers who define what needs to be built and in what order. Without that layer, even well-written code can lead to products that feel disjointed or incomplete. Features may not work together, integrations can break and the final product often does not match the original idea.

BrainGrid is designed to address that gap. Instead of focusing on generating code, it helps users map out the structure of a product before development begins. The aim is to give builders a clearer starting point so that the tools they use—whether human or AI—can produce more consistent results.

The company says more than 500 builders have already used it to create software products across areas like fitness, healthcare and productivity. These range from first-time founders experimenting with new ideas to experienced developers working independently. In many cases, the products are already live and generating revenue, suggesting that the demand is not just for experimentation but for building something that can scale.

For investors, the appeal lies in the evolving role of software development. As AI takes on more of the technical work, the value shifts toward defining the problem and structuring the solution. In that sense, planning becomes less of a background task and more of a core capability.

The US$1 million raise is relatively modest, but it points to a larger trend. As more people gain access to AI tools, the number of potential builders expands. What remains limited is the ability to organise ideas into products that work in the real world. If that shift continues, the next wave of software may not be defined by who can code, but by who can plan.

As global tech ecosystems become more interconnected, the ability to move innovation across borders is becoming just as important as building it. A new partnership between MTR Lab, the investment arm of MTR Corporation and ZGC Science City Ltd, a government-backed technology ecosystem based in Beijing’s Haidian district, reflects this shift.

At its core, the collaboration is designed to connect high-potential Chinese startups with global capital, real-world deployment opportunities and international markets. It focuses on sectors like AI, robotics, smart mobility and sustainable urban development—areas where China already has strong technical depth but where scaling beyond domestic markets can be more complex.

This is where the partnership begins to matter. ZGC Science City sits at the center of one of China’s most concentrated innovation clusters, with thousands of AI companies and a growing base of specialised and high-growth firms. MTR Lab, on the other hand, brings access to international markets, industry networks and practical deployment environments tied to infrastructure, transport and urban systems. Together, they are attempting to bridge a familiar gap: turning local innovation into globally relevant products.

In practice, the model is straightforward. ZGC Science City will introduce MTR Lab to startups working in priority sectors, creating a pipeline for potential investment and collaboration. From there, MTR Lab can support these companies through funding, pilot projects and access to overseas markets. The idea is not just to invest, but to help startups test and apply their technologies in real-world settings, particularly in complex urban environments.

The timing is notable. China’s AI and deep tech ecosystem has expanded rapidly, with thousands of companies contributing to advancements in automation, smart infrastructure and sustainability. At the same time, global demand for these technologies is rising, especially as cities look for more efficient and scalable solutions. Yet, moving from innovation to adoption often requires cross-border coordination—something individual startups may struggle to navigate alone.

This partnership also builds on a broader pattern. Corporate venture arms like MTR Lab are increasingly positioning themselves not just as investors, but as connectors between markets. By combining capital with access to infrastructure and deployment scenarios, they offer startups a way to move faster from development to real-world use. For ZGC Science City, the collaboration adds an international layer to its ecosystem, helping local companies extend beyond domestic growth.

What emerges is a model that goes beyond a typical investment announcement. It reflects a growing recognition that innovation today is rarely confined to one geography. Technologies may be developed in one ecosystem, refined in another and scaled globally through partnerships like this.

As cross-border collaboration becomes more central to how startups grow, partnerships like the one between MTR Lab and ZGC Science City point to a more connected innovation landscape—one where access, not just invention, defines success.

Endometriosis affects roughly one in ten women worldwide, yet diagnosing the condition often takes years. In many cases, patients experience symptoms for nearly a decade before receiving a confirmed diagnosis. One reason is that detecting endometriosis through ultrasound requires specialized training and clinicians do not always encounter enough real cases to build that expertise.

To address this gap, medical simulation company Surgical Science has introduced a new ultrasound training module designed specifically for identifying endometriosis. The system allows clinicians to practice scanning techniques in a virtual environment, helping them recognize signs of the disease without relying solely on real-patient cases.

A key feature of the simulator is training on the “sliding sign,” an ultrasound indicator used to detect deep endometriosis. Because the condition can appear differently from patient to patient, mastering this assessment in real clinical settings can be difficult. The simulator allows clinicians to repeat the process across multiple scenarios, improving their ability to identify the condition during routine examinations.

The module also incorporates the International Deep Endometriosis Analysis (IDEA) protocol, which provides a structured method for performing a complete pelvic ultrasound assessment. Additional training cases, region-based scenarios and certification options are included to support standardized learning.

Early training results suggest strong improvements in clinician confidence, including higher skill levels in transvaginal ultrasound and better recognition of deep endometriosis. By expanding access to structured ultrasound training, simulation tools like this could help reduce diagnostic delays and improve care for millions of women living with the condition.

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People often assume robots make people uneasy everywhere. But a new global study suggests something more nuanced. Robot anxiety tends to be highest in places where people rarely see robots in real life. Where robots are more visible, attitudes are often far more positive. That insight comes from a global study by Hexagon AB, which surveyed 18,000 participants across nine major markets. The research explored how adults and children think about robots and how those views change depending on everyday exposure.

In the United Kingdom, anxiety about robots is the highest among the countries studied. Around 52% of adults say they feel worried that something might go wrong when they think about interacting with or working alongside robots. South Korea sits at the other end of the spectrum, with only 29% reporting similar concerns. One factor appears to explain much of the gap: familiarity.

British adults are among the least likely to have encountered robots in real life. Only about 30% say they have seen or used one. In contrast, countries where robots are more visible tend to report greater comfort. China offers the clearest example. Around 75% of adults there say they have seen or interacted with robots. At the same time, 81% say they feel excited about the technology’s future potential.

The study suggests that attitudes toward robots are not fixed. Instead, they shift depending on where people encounter them and what tasks they perform. When robots are seen solving clear, practical problems, confidence tends to rise.

Across the surveyed countries, adults report the highest comfort levels with robots working in factories and warehouses. Around 63% say they are comfortable with robots in those environments. These are settings where tasks are clearly defined and safety standards are well understood. Acceptance drops in more personal spaces. Only 46% say they feel comfortable with robots in the home, while comfort falls further to 39% when robots are imagined in classrooms.

In other words, context matters. People appear more willing to accept robots when they take on physically demanding or dangerous work. Half of the respondents say improved safety is one of the main advantages of robotics in those environments. A similar share point to productivity gains as another benefit. Another finding challenges a common assumption about public fears. Job loss is often described as the biggest concern surrounding robotics. But the study suggests security risk worries people more.

Around 51% of adults say their biggest concern about robots at work is the possibility that the machines could be hacked or misused. That fear outweighs worries about physical malfunction or injury, which stand at 41%. Concerns about being replaced at work appear at the same level.

For many respondents, the issue is not simply whether robots can perform tasks. It is whether the systems controlling them are secure. According to researchers involved in the study, these concerns reflect how people evaluate emerging technologies. Instead of having a single opinion about robotics, people tend to judge each situation individually.

A robot helping assemble products in a factory may feel acceptable. The same technology operating in more sensitive environments can raise different questions. Dr. Jim Everett, an associate professor in moral psychology, says trust in artificial intelligence and robotics is often misunderstood. People are not simply asking whether they trust the technology, he notes. They are thinking about specific tools performing specific roles.

A robot assisting in a classroom or helping in healthcare carries different expectations than an AI system used in defense or surveillance. Even though these technologies are often grouped together in public debates, people evaluate them differently depending on their purpose.

Finally, the study also highlights another important factor shaping public attitudes: experience. When people actually encounter robots, fear often declines. Michael Szollosy, a robotics researcher involved in the project, says reactions tend to change quickly when individuals meet a robot for the first time.

The idea of an autonomous machine can feel intimidating in theory. But when people see a small service robot or an industrial machine performing a straightforward task, the reaction is often much calmer. Exposure can shift perceptions from abstract fears to practical understanding.

That shift matters because robotics is moving steadily into everyday environments. From manufacturing and logistics to healthcare and public services, machines capable of autonomous or semi-autonomous work are becoming more common.

As that happens, the study suggests public confidence may depend less on technical breakthroughs and more on visibility and transparency. Burkhard Boeckem, chief technology officer at Hexagon AB, argues that trust grows when people understand what robots are designed to do and where their limits lie.

Anxiety tends to increase when systems feel invisible or poorly understood. Clear boundaries and clear explanations can have the opposite effect. When people see robots working safely alongside humans, performing well-defined tasks and operating within clear rules, the technology becomes easier to accept.

In that sense, the future of robotics may depend as much on public familiarity as on engineering. The machines themselves are advancing quickly. But the relationship between humans and robots is still being negotiated. For now, the study offers a simple insight: the more people encounter robots in everyday life, the less mysterious they become. And once the mystery fades, the conversation often changes from fear to curiosity.

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As Hollywood prepares for this weekend’s Oscars, a different kind of performer is stepping into the spotlight — one that doesn’t physically exist.

Tilly Norwood, described as the world’s first AI actor, has released her debut musical comedy video, Take the Lead. The project arrives at a moment when artificial intelligence has become one of the most contentious topics in the film industry.

The message of the song is simple. AI should not be seen as a threat to actors. Instead, it can become another creative tool. The release also offers a first look at what Norwood’s creators call the “Tillyverse”. It is envisioned as a cloud-based entertainment world where AI characters can live, interact and perform.

Behind the character is actor and producer Eline van der Velden. She is the CEO of production company Particle6 and AI talent studio Xicoia. Van der Velden created Tilly as a way to experiment with how artificial intelligence could be used in storytelling.

The timing is not accidental. The entertainment industry has spent the past few years debating the role AI should play in filmmaking and acting. Questions about digital replicas, automated performances and creative ownership continue to divide artists and studios.

Norwood’s musical video enters that debate with a different tone. Instead of warning about AI replacing actors, the project suggests that the technology could expand what performers are able to do.

The video itself also serves as a technical experiment. The song Take the Lead was generated using the AI music platform Suno. The video was then produced using a combination of widely available AI tools and Particle6’s own creative process.

One of the newer techniques used in the project is performance capture. Van der Velden physically acted out Tilly’s movements and expressions so the digital character could mirror a human performance. But the production was far from automated. According to Particle6, a team of 18 people worked on the video. The group included a director, editor, production designer, costume designer, comedy writer and creative technologist. In other words, the project still relied heavily on human creativity.

“Tilly has always been a vehicle to test the creative capabilities and boundaries of AI,” van der Velden said. “It’s not about taking anyone’s job”. She added that even with powerful tools, good AI content still takes time, taste and creative direction.

The project also reflects how quickly production technology is evolving. Tools that once required large studios are now accessible to smaller creative teams experimenting with AI-driven storytelling.

For Particle6, the character of Tilly Norwood acts as a testing ground. Each project explores how AI performers might be developed, directed and integrated into entertainment. Whether audiences embrace digital actors remains an open question. Many in the industry are still wary of how AI could reshape creative work.

But projects like Take the Lead show another possibility. Instead of replacing performers, artificial intelligence could become part of the creative process itself. In that sense, Tilly Norwood may represent something more than a virtual performer. She is also an experiment in how humans and machines might collaborate in the future of entertainment.