Technology
Researchers Develop Breakthrough Imaging Tech That Lets Robots See Inside Boxes
The system, called mmNorm, uses millimeter wave (mmWave) signals — commonly used in Wi-Fi networks — to reconstruct high-resolution 3D shapes of objects that are fully occluded from view

A team of researchers at the Massachusetts Institute of Technology (MIT) has developed a new imaging technology that allows robots to see hidden objects — such as tools buried under packing material or items tucked inside drawers — with unprecedented accuracy.
The system, called mmNorm, uses millimeter wave (mmWave) signals — commonly used in Wi-Fi networks — to reconstruct high-resolution 3D shapes of objects that are fully occluded from view. The method achieved 96% reconstruction accuracy on complex-shaped items such as mugs, power tools, and silverware — outperforming existing methods by a wide margin.
In a media statement, Fadel Adib, associate professor in MIT’s Department of Electrical Engineering and Computer Science and senior author of the study, said:
“We’ve been interested in this problem for quite a while, but past methods weren’t getting us where we needed to go. We needed a very different way of using these signals than what’s been done for over 50 years.”
Seeing What’s Invisible
mmNorm works by capturing and interpreting the way mmWave signals bounce off surfaces — even when those surfaces are hidden from view. Unlike traditional radar, which struggles to image small items with detail, mmNorm estimates the direction of each object’s surface using signal strength and geometry, then reconstructs a full 3D model from that data.
“Some antennas might have a very strong vote, some might have a very weak vote… and we combine all votes to produce one surface normal that is agreed upon by all antenna locations,” explained Laura Dodds, lead author and MIT research assistant, in a media statement.
The researchers built a prototype by mounting a radar unit on a robotic arm, which moved around the object while collecting signal data. This allowed the system to determine not just what an object was, but its exact shape and orientation — crucial information for robots tasked with delicate or complex manipulation.
Real-World Applications
The implications of mmNorm are wide-ranging. In manufacturing or warehouses, it could enable robots to retrieve the right tool or part from cluttered drawers or sealed containers. In homes or assisted living facilities, it could allow service robots to interact more naturally and safely with everyday items. In security and defense, the technology could enhance the detection of concealed objects in scanners.
“Our qualitative results really speak for themselves. The amount of improvement you see makes it easier to develop new applications using these reconstructions,” said Tara Boroushaki, co-author and research assistant.
The system also successfully distinguished between multiple objects made of different materials — including wood, glass, plastic, and metal — although its performance drops when objects are behind thick walls or metallic barriers.
The research team aims to improve mmNorm’s resolution, enhance its ability to handle less reflective materials, and make it more robust for use through thicker obstructions.
“This work really represents a paradigm shift in how we think about these signals and the 3D reconstruction process,” Dodds added. “We’re excited to see how the insights we’ve gained here can have a broad impact.”
The study, co-authored by Fadel Adib, Laura Dodds, Tara Boroushaki, and former MIT postdoc Kaichen Zhou, was presented at the 2025 Annual International Conference on Mobile Systems, Applications and Services (ACM MobiSys 2025).
Society
How 2025’s Emerging Technologies Could Redefine Our Lives

In an age when algorithms help cars avoid traffic and synthetic microbes could soon deliver our medicine, the boundary between science fiction and science fact is shrinking. The World Economic Forum’s Top 10 Emerging Technologies of 2025 offers a powerful reminder that innovation is not just accelerating — it’s converging, maturing, and aligning itself to confront humanity’s most urgent challenges.
From smart cities to sustainable farming, from cutting-edge therapeutics to low-impact energy, this year’s list is more than a forecast. It’s a blueprint for a near future in which resilience and responsibility are just as crucial as raw invention.
Sensing the World Together
Imagine a city that can sense a traffic jam, redirect ambulances instantly, or coordinate drone deliveries without a hiccup. That’s the promise of collaborative sensing, a leading entry in the 2025 lineup. This technology enables vehicles, emergency services, and infrastructure to “talk” to each other in real time using a network of connected sensors — helping cities become safer, faster, and more responsive.
It’s one of several technologies on this year’s list that fall under the theme of “trust and safety in a connected world” — a trend reflecting the growing importance of reliable information, responsive systems, and secure networks in daily life.
Trust, Truth, and Invisible Watermarks
But as digital content spreads and AI-generated images become harder to distinguish from reality, how do we safeguard truth? Generative watermarking offers a promising solution. By embedding invisible tags in AI-generated media, this technology makes it easier to verify content authenticity, helping fight misinformation and deepfakes.
“The path from breakthrough research to tangible societal progress depends on transparency, collaboration, and open science,” said Frederick Fenter, Chief Executive Editor of Frontiers, in a media statement issued alongside the report. “Together with the World Economic Forum, we have once again delivered trusted, evidence-based insights on emerging technologies that will shape a better future for all.”
Rethinking Industry, Naturally
Other breakthroughs are tackling the environmental consequences of how we make things.
Green nitrogen fixation, for instance, offers a cleaner way to produce fertilizers — traditionally one of agriculture’s biggest polluters. By using electricity instead of fossil fuels to bind nitrogen, this method could slash emissions while helping feed a growing planet.
Then there’s nanozymes — synthetic materials that mimic enzymes but are more stable, affordable, and versatile. Their potential applications range from improving diagnostics to cleaning up industrial waste, marking a shift toward smarter, greener manufacturing.
These technologies fall under the trend the report identifies as “sustainable industry redesign.”
Health Breakthroughs, From Microbes to Molecules
The 2025 report also spotlights next-generation biotechnologies for health, a category that includes some of the most exciting and potentially transformative innovations.
Engineered living therapeutics — beneficial bacteria genetically modified to detect and treat disease from within the body — could make chronic care both cheaper and more effective.
Meanwhile, GLP-1 agonists, drugs first developed for diabetes and obesity, are now showing promise in treating Alzheimer’s and Parkinson’s — diseases for which few options exist.
And with autonomous biochemical sensing, tiny wireless devices capable of monitoring environmental or health conditions 24/7 could allow early detection of pollution or disease — offering critical tools in a world facing climate stress and health inequities.
Building Smarter, Powering Cleaner
Under the theme of “energy and material integration”, the report also identifies new approaches to building and powering the future.
Structural battery composites, for example, are materials that can both carry loads and store energy. Used in vehicles and aircraft, they could lighten the load — quite literally — for electric transportation.
Osmotic power systems offer another intriguing frontier: by harnessing the energy released when freshwater and saltwater mix, they provide a low-impact, consistent power source suited to estuaries and coastal areas.
And as global electricity demand climbs — especially with the growth of AI, data centers, and electrification — advanced nuclear technologies are gaining renewed interest. With smaller, safer designs and new cooling systems, next-gen nuclear promises to deliver scalable zero-carbon power.
Toward a Converging Future
This year’s edition of the report emphasizes a deeper trend: technological convergence. Across domains, innovations are beginning to merge — batteries into structures, biology into computing, sensing into infrastructure. The future, it seems, will be shaped less by standalone inventions and more by integrated, systemic solutions.
“Scientific and technological breakthroughs are advancing rapidly, even as the global environment for innovation grows more complex,” said Jeremy Jurgens, Managing Director of the World Economic Forum, in the WEF’s official media release.
“The research provides top global leaders with a clear view of which technologies are approaching readiness, how they could solve the world’s pressing problems and what’s required to bring them to scale responsibly,” he added.
Beyond the Hype
Now in its 13th year, the Top 10 Emerging Technologies report has a strong track record of identifying breakthroughs poised to move from lab to life — including mRNA vaccines, flexible batteries, and CRISPR-based gene editing.
But this year’s list is not just a celebration of possibility. It’s a reminder of what’s needed to deliver impact at scale: responsible governance, sustained investment, and public trust.
As Jeremy Jurgens noted, “Breakthroughs must be supported by the right environment — transparent, collaborative, and scalable — if they are to benefit society at large.”
In a time of climate stress, digital overload, and health inequity, these ten technologies offer something rare: a credible roadmap to a better future — not decades away, but just around the corner.
Space & Physics
MIT unveils an ultra-efficient 5G receiver that may supercharge future smart devices
A key innovation lies in the chip’s clever use of a phenomenon called the Miller effect, which allows small capacitors to perform like larger ones

A team of MIT researchers has developed a groundbreaking wireless receiver that could transform the future of Internet of Things (IoT) devices by dramatically improving energy efficiency and resilience to signal interference.
Designed for use in compact, battery-powered smart gadgets—like health monitors, environmental sensors, and industrial trackers—the new chip consumes less than a milliwatt of power and is roughly 30 times more resistant to certain types of interference than conventional receivers.
“This receiver could help expand the capabilities of IoT gadgets,” said Soroush Araei, an electrical engineering graduate student at MIT and lead author of the study, in a media statement. “Devices could become smaller, last longer on a battery, and work more reliably in crowded wireless environments like factory floors or smart cities.”
The chip, recently unveiled at the IEEE Radio Frequency Integrated Circuits Symposium, stands out for its novel use of passive filtering and ultra-small capacitors controlled by tiny switches. These switches require far less power than those typically found in existing IoT receivers.
A key innovation lies in the chip’s clever use of a phenomenon called the Miller effect, which allows small capacitors to perform like larger ones. This means the receiver achieves necessary filtering without relying on bulky components, keeping the circuit size under 0.05 square millimeters.

Traditional IoT receivers rely on fixed-frequency filters to block interference, but next-generation 5G-compatible devices need to operate across wider frequency ranges. The MIT design meets this demand using an innovative on-chip switch-capacitor network that blocks unwanted harmonic interference early in the signal chain—before it gets amplified and digitized.
Another critical breakthrough is a technique called bootstrap clocking, which ensures the miniature switches operate correctly even at a low power supply of just 0.6 volts. This helps maintain reliability without adding complex circuitry or draining battery life.
The chip’s minimalist design—using fewer and smaller components—also reduces signal leakage and manufacturing costs, making it well-suited for mass production.
Looking ahead, the MIT team is exploring ways to run the receiver without any dedicated power source—possibly by harvesting ambient energy from nearby Wi-Fi or Bluetooth signals.
The research was conducted by Araei alongside Mohammad Barzgari, Haibo Yang, and senior author Professor Negar Reiskarimian of MIT’s Microsystems Technology Laboratories.
Society
Researchers Unveil Light-Speed AI Chip to Power Next-Gen Wireless and Edge Devices
This could transform the future of wireless communication and edge computing

In a breakthrough that could transform the future of wireless communication and edge computing, engineers at MIT have developed a novel AI hardware accelerator capable of processing wireless signals at the speed of light. The new optical chip, built for signal classification, achieves nanosecond-level performance—up to 100 times faster than conventional digital processors—while consuming dramatically less energy.
With wireless spectrum under growing strain from billions of connected devices, from teleworking laptops to smart sensors, managing bandwidth has become a critical challenge. Artificial intelligence offers a path forward, but most existing AI models are too slow and power-hungry to operate in real time on wireless devices.
The MIT solution, known as MAFT-ONN (Multiplicative Analog Frequency Transform Optical Neural Network), could be a game-changer.
“There are many applications that would be enabled by edge devices that are capable of analyzing wireless signals,” said Prof. Dirk Englund, senior author of the study, in a media statement. “What we’ve presented in our paper could open up many possibilities for real-time and reliable AI inference. This work is the beginning of something that could be quite impactful.”
Published in Science Advances, the research describes how MAFT-ONN classifies signals in just 120 nanoseconds, using a compact optical chip that performs deep-learning tasks using light rather than electricity. Unlike traditional systems that convert signals to images before processing, the MIT design processes raw wireless data directly in the frequency domain—eliminating delays and reducing energy usage.
“We can fit 10,000 neurons onto a single device and compute the necessary multiplications in a single shot,” said Ronald Davis III, lead author and recent MIT PhD graduate.
The device achieved over 85% accuracy in a single shot, and with multiple measurements, it converges to above 99% accuracy, making it both fast and reliable.
Beyond wireless communications, the technology holds promise for edge AI in autonomous vehicles, smart medical devices, and future 6G networks, where real-time response is critical. By embedding ultra-fast AI directly into devices, this innovation could help cars react to hazards instantly or allow pacemakers to adapt to a patient’s heart rhythm in real-time.
Future work will focus on scaling the chip with multiplexing schemes and expanding its ability to handle more complex AI tasks, including transformer models and large language models (LLMs).
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