Chinese researchers have reportedly developed a new “three-lane highway” optical fiber system. The new system, the researchers explain, could dramatically expand the data-transfer capacity of future networks, notably those for artificial intelligence (AI).

Put in simpler terms, the innovation effectively “squeezes” more traffic from fiber-optic cables without having to replace or lay new cabling. According to the team, they have been able to increase traffic by as much as five times while also increasing transmission capacity per core by nearly 50%.

Today, most internet traffic travels through glass fibers using laser light. Importantly, each fiber doesn’t just carry one beam of light. It carries many wavelengths (colors) of light simultaneously, like multiple radio stations sharing the airwaves.

Presently, most commercial systems use a mixture of C-band (the workhorse) and L-band wavelengths. The latter is used to extend capacity when needed.

The team, they report, has managed to add a third, called S-band; hence the “three-lane highway” analogy. The fiber itself isn’t necessarily wider; they’re simply using more of the available light spectrum.

Adding an extra lane to optical fibers

So, you might ask, why hasn’t S-band been used before? Well, in short, over long distances, optical signals tend to weaken. To overcome this, telecom companies use optical amplifiers placed along the route.

The industry’s amplifiers were optimized for C-band (and later L-band). S-band signals were more difficult and expensive to amplify cleanly. To this end, the Chinese team claims to have solved enough of these engineering problems to make commercial deployment practical.

But there is another trick up the team’s sleeve: multiple cores to the fibers. Normal optical fibers consist of a single core, but the team’s new ones reportedly actually contain four.

To this end, each of these core acts like an independent fiber. So, unlike traditional fibers with a single core and two optical bands, the new fibers actually have four cores, with three optical bands working simultaneously.

That’s a significant leap in capability. For applications like AI, this could prove to be very useful indeed, especially when it comes to removing data-transfer bottlenecks.

At present, most large AI models tend to use thousands of graphics processing units (GPUs), constantly exchanging data at the speed of light. A modern AI cluster can move terabits per second between machines.

5x the data transfer

Often, the bottleneck is not the GPU but getting data from one GPU cluster to another. So, if you can move five times more data through the same fiber infrastructure, you necessarily get faster training, larger distributed models, and lower network congestion.

Looking at the bigger picture, this isn’t a breakthrough in terms of fiber optics; similar achievements have happened in Japan, Europe, and the US. What is different is that this appears to have been commercially deployed, not just developed in a lab.

According to reports, the new optic fibers have run over about 21.7 miles (35 km) of an existing telecoms network, combining the innovations mentioned. Looking ahead, the team suggests the new cables could be deployed internationally, perhaps even in submarine cables.

It could also play a major role in China’s “Eastern Data, Western Computing strategy,” which seeks to shift data-intensive workloads from densely populated eastern regions to resource-rich western provinces, according to the developers.

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Chinese military planners have reportedly devised a plan to target US carriers in places like Guam. The strategy, published in the Chinese journal Tactical Missile Technology, claims a combination of satellites, AI, and missiles could render carrier groups vulnerable, even at distances of over 1,620 nautical miles (3,000 km).

At present, both the People’s Liberation Army (PLA) and the United States Navy know that the former can threaten critical assets like aircraft carriers close to China. To reduce that threat, the US Navy has increasingly positioned key assets farther from China’s coastline, relying on bases such as Guam and adopting more dispersed operating patterns across the Pacific.

The Navy has also been dispersing deployed ships in the region to make them much harder to find, track, and potentially attack. Not keeping their eggs in one basket, as it were.

However, as the South China Morning Post (SCMP) reports, the PLA has been working on a potential plan to threaten such ships even at great distances. Led by associate professor Gao Tianyun from the College of International Studies at the National University of Defence Technology in Nanjing, the proposal is very interesting indeed.

Dangerous game of hide-and-seek

The study, titled “Research on the effectiveness of anti‑ship missile swarm operation under distributed confrontation,” basically describes an innovative “kill-chain” solution rather than a new wonder weapon.

The idea, in a nutshell, is to first find the group using a mixture of satellites, drones, radar aircraft, ships, submarines, signals intelligence, etc. Once done, the plan would rely on near-constant tracking for long-range missiles to be targeted and launched.

With that achieved, the paper suggests firing many missiles (a mix of hypersonics and “pre-strike firepower packages”) at the target, not one or two.

Once in flight, the plan would rely on the missiles cooperating by sharing target data, sorting real ships from decoys, assigning themselves to different targets, and attacking from different angles.

According to the researchers, such a coordinated attack could overwhelm layers of US naval defense, including Aegis-equipped destroyers, interceptor missiles, electronic warfare systems, decoys, and close-in weapon systems.

So, something of a coordinated, long-range missile swarm attack. The point is to make the US defence system run out of time, interceptors, radar capacity, or correct target choices.

Means and motive

Sounds reasonable on the surface, but the plan comes with one major caveat. That being said, this is just a plan right now, not proof that China can actually do it tomorrow.

Needless to say, hitting a moving carrier group at 1,620 nautical miles distant is not an easy task. Achieving it in reality would be brutally hard because the target moves, hides, jams, uses decoys, and fights back.

The hardest part is not the missile range; it is maintaining accurate targeting data across the whole chain. While effectively just a wargame made public, the release of this information is likely intended to send a warning to the US, rather than actually boast about its technological prowess.

In effect, they are saying that hiding and dispersing your ships won’t necessarily keep you safe. We (China) have the means to get them if we want to.

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In our latest episode of Lexicon, we sat down with Tom Grainger, Commercial Vice President at Niron Magnetics,  to explore the hidden role permanent magnets play in modern technology and electrification.

From electric vehicles and wind turbines to smartphones and speakers, these components are essential to countless devices we rely on every day. Tom also discussed the growing strategic importance of rare earth magnets and the risks associated with highly concentrated global supply chains.

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Reinventing the magnet

Permanent magnets rarely make headlines. Yet, as Grainger explained to us, they sit at the core of modern electrification.

“Pretty well every modern electronic device relies on permanent magnets,” he told us. “The car you drive, the speakers you’re hearing me come out of right now, the microphone that’s picking up my voice, all of those are permanent magnet devices,” he added.

“Relying on rare earth magnets today means relying on a supply chain that is over 90 percent concentrated in China. Single point of failure geopolitically,” he said.

But it turns out the issue is not limited to mining.

“All through the supply chain, you see that concentration,” he explained. The result is what he calls a pinch point. “You’ve got a pinch point on which the global economy hinges,” he added.

A magnet-hungry world

Furthermore, the demand side only intensifies the pressure. “As cars install more speakers and compete on infotainment and a great in-cab experience, doubling the speakers doubles the magnets,” Grainger told us. 

“Imagine as you move from an F-35 to a swarm of drones, you’re saving a lot of money, saving a lot of material, but you are greatly increasing your magnet consumption,” he added.

Even in a stable geopolitical climate, supply would be strained. “Even if everything is peachy globally, there are just not enough rare earths to solve this magnet-hungry global economy,” he added.

“For some critical rare earths, China put in place export controls,” he said. Those elements are required for high-temperature applications, which represent roughly 80 percent of use cases. Automotive production slowed. Defense programs accelerated alternative sourcing efforts. Phones, he recalls, were “ringing off the hook.”

“Magnets may already be as strategically important as semiconductors,” he added.

Forty years without a new material

Beyond supply risk, Grainger argues, there is a deeper technological constraint. The last major breakthrough in magnetic materials came in the 1980s with rare-earth magnets.

“The last time we had a new magnetic material that has had any sort of real commercial impact was rare earth magnets in the 1980s,” he told us.

That means four decades of motor and generator design constrained by the same materials. He uses a culinary analogy. “You can imagine you are a chef. You’ve been working with four ingredients. Suddenly, you have another option. It is just an unlock for breakthroughs in motor design,” he added.

“We’ve spent four decades without a new key and without a new door open,” he said. That new key, according to Niron, is iron nitride.

Iron nitride to the rescue

According to Grainger, iron nitride is not a brand-new discovery, being first identified in the 1950s. Later attempts in Japan produced promising but inconsistent results. The missing piece was the ability to understand and control the material at the nanoscale.

“We did not have the technology at the time to be able to explain, just from a physics perspective, what makes iron nitride so magnetic, and then to reliably produce iron nitride in this magnetic phase,” Grainger told us.

Advances in imaging and characterization in the 2000s and early 2010s changed that. “The ability to see what you’re doing when you make an experimental attempt to measure it was unlocked by advances in characterization imaging,” he added.

From there, it took more than a decade to move from laboratory research to bulk, commercially viable magnets. “It was a decade from that program to actually having commercially viable bulk permanent magnets,” he said.

The potential upside is significant. “For a rare earth permanent magnet made of neodymium, that number is about 1.6 Tesla,” he explained. “For iron nitride, that equivalent limit is 2.4 Tesla,” he added.

“That ceiling is 50 percent higher than rare earth permanent magnets,” he said.

Temperature performance is another factor. Rare earth magnets rely on scarce heavy rare earth elements such as dysprosium and terbium to maintain performance at high temperatures. “Iron nitride, just by virtue of its underlying crystal structure and properties, gets that temperature stability for free,” Grainger said.

Unlocking variable flux motors

One of the most intriguing applications discussed in the episode is the variable flux motor. Traditional permanent magnet motors use a technique called flux weakening at high speeds, which requires continuous electrical input. 

Grainger described it with a metaphor: “think of it as holding a spring. If you move your hand, it pops right back up. And so you’re using power to do that.”

Variable flux offers a different approach. “Instead of continuous energy expenditure holding down that spring, it’s like a ratchet. You push down the spring once, and you lock it into place,” he said.

The result is improved efficiency across the speed range. In electric vehicles, that translates directly to range and battery savings. “You get a 2 percent decrease in battery materials. The cost savings on that don’t just pay for your magnets, that pays for your whole motor,” he added.

The same logic applies to appliances and data centers. Efficiency gains compound quickly when systems operate continuously.

Scaling manufacturing

Moving from breakthrough to production required another leap. “Niron has been introducing iron nitride permanent magnets, and we’re doing so on a nano scale,” Grainger told us. 

“Our lab breakthrough was then the second breakthrough, which is really the process. And the process in that case becomes the product,” he said. The goal is modular scalability. Facilities can be replicated in multiple regions, reducing geographic concentration risk.

Iron nitride is composed of iron and nitrogen. Both are abundant and widely sourced. “Anywhere you have an industrialized society, you’ve got an opportunity for iron nitride domestic magnet production,” he said.

A strategic shift

Looking at the bigger picture, Grainger drew a historical analogy to the Haber-Bosch process, which enabled synthetic fertilizer production and reduced reliance on guano mining. “What iron nitride is, is that shift,” he said. “So, what if we could avoid all of that digging. What if we could avoid the reliance on what is fundamentally any mine has a shelf life,” he added.

So, instead of finite ore bodies, he describes a factory-built approach. “This is innovation as a cookie-cutter. Sort of the abundance philosophy around magnets,” he told us.

And, defense customers have taken notice. Programs initially planned for five to seven-year development timelines were “suddenly on 18-month fast tracks” after export controls tightened.

What the next decade has in store

Looking ahead, Grainger defines success in pragmatic terms. “Success for iron nitride is that we’re not talking about magnets as a scarce or critical pain point in global supply chains,” he added.

Beyond stability, he anticipates innovation. New motor and generator designs built around the expanded magnetic ceiling. Localized manufacturing in Asia, Europe, and North America. Reduced vulnerability and expanded design freedom.

“It can be hard sometimes to think about, can new things be done that aren’t just new assembly or new software?” he told us. “And absolutely they can.”

A trio of students from the University of British Columbia has put their expertise to the test by building a single-player, artificial intelligence (AI)-controlled air hockey table. This is interesting enough, but what really takes the biscuit is that the AI managed to learn to play purely in simulation.

Typically, AI-controlled robots like this are trained through trial and error in the “real world” by failing and learning from thousands of practice runs. While effective, this is time-consuming and can damage hardware.

The UBC team, however, decided to see if they could train the AI in the digital space, make its mistakes there first, and then be unleashed on a real air hockey table. To this end, they built a highly accurate digital twin of the table to train the AI.

Once the training was complete, they then copied the trained AI into the real robot to see how it performed against a human opponent. And the results were surprising.

Despite any real-world experience, the AI-controlled robot air hockey player was able to put up a real challenge. All this straight “out of the box,” as it were.

Tempered digitally for the real world

What’s also interesting here is that AI typically struggles to learn tasks like air hockey. This is because the puck, in particular, moves very fast, can move unpredictably, and is heavily influenced by subtle changes from interactions with paddles and walls.

Any robot player also has to factor in time lags from motors, cameras, voltage fluctuations, mechanical vibrations, and imperfect puck tracking. So, even tiny errors can result in game-losing miscalculations.

To this end, the team purposefully designed the AI’s training environment to be imperfect. This is a diversion from most training scenarios, which can be “too perfect,” but the real world clearly isn’t.

So, the team factored in things like uneven rails, warped tables, inconsistent rebounds, power supply dips, and camera latency. Called “domain randomization,” this enabled the AI to learn to expect the unexpected and react as best it can, just like a human player has to.

This, the team explains, teaches the AI to predict a range of likely outcomes from a puck bounce rather than an exact outcome based on a set algorithm. So, the AI learned to expect a puck to be in an approximate place in the future and react accordingly.

To speed up training, the team ditched the idea of using normal physics engines like Unity and Unreal and instead turned to something called “soft actor critic” training. In short, this is a sort of carrot-and-stick-based learning environment.

Air hockey is a punishing sport

Within it, the AI takes action and gets rewards or punishments based on its performance. Over millions of simulated games, the AI gets better and better at playing the game and adapting to all the built-in chaos of the game.

When applied to the real world, the AI player was also giving a helping hand using a special overhead camera and a retroreflective tape-coated puck. This helps the AI “see” the puck more clearly at 120 frames per second.

Beyond air hockey, the team’s innovation also has some potential applications for training other autonomous systems like drones, vehicles, robots, etc. If the training of these platforms could be sped up and made more realistic, similar sim-to-real transfers could be a huge boon.

If you want to learn more, details are available on the project’s official GitHub page.

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Electric vehicle startup Harbinger has reportedly teamed up with American Rheinmetall to develop various trucks for military use. Based on the former’s medium-duty hybrid and electric truck chassis, the plan is to develop trucks ranging from robotic cargo haulers to battlefield logistics and resupply vehicles.

Since Rheinmetall has extensive experience as a defense contractor, it will be able to provide expertise on survivability and integration into military supply chain operations.

The new vehicles will use something called “drive-by-wire,” which essentially means steering, braking, and acceleration will be electronically, not mechanically, operated. Such a setup will be essential for remote operations, autonomous operations, and potentially artificial intelligence-assisted driving.

The new vehicles will also form part of the Pentagon’s drive for what it calls “attritable mass.” In essence, this means they are looking for ways to field hardware that is cheap enough to be essentially disposable if needed.

Harbinger of the future of army logistics?

This is especially the case when trained personnel are thrown into the mix. Losing a $50 million vehicle and its crew is not only expensive but should be avoided if at all possible.

And this is where Harbinger and Rheinmetall’s venture potentially comes into its own. If dangerous logistics and supply runs can be achieved using cheap autonomous electric vehicles, the costs of losses become more acceptable.

Electric vehicles (EVs), in particular, offer some interesting benefits in this role too. First and foremost, they are relatively quiet in operation, making them better suited for stealth logistics, reconnaissance, and nighttime resupply.

They also produce less of a heat signature compared to internal combustion engine-driven vehicles. EVs also benefit from massive onboard power, which can be used as a kind of mobile giant battery to power/recharge other electronic assets like drones, electronic warfare (EW) systems, and potential directed-energy weapons.

This new venture is looking, specifically, at providing an Extended Range Electric Vehicle (EREV) like its announced “Praesidia.” In short, this is basically a militarized, ruggedized hybrid electric-diesel vehicle that provides the best of both worlds.

Such a platform will have an excellent range and reliability, making it very attractive for military operations in a range of theatres. Scant details have been officially released, but according to Harbinger, the Praesidia should have a range of around 500 miles (805 km).

Any army marches on its stomach

This vehicle, according to Harbinger, will also provide “100kW Exportable power for counter-drone systems, directed energy, radar, and off-grid needs like forward operating bases.”

“Harbinger has always built for the toughest commercial missions, and the Warfighter’s mission is the toughest of all,” explains John Harris, Co-Founder and Chief Executive Officer of Harbinger.

“Partnering with American Rheinmetall, one of the most capable ground systems integrators serving the DoW, allows us to bring our autonomy-ready platform at a price point that makes true attritable mass possible,” he added.

Together, we can give Soldiers robotic systems that are affordable enough to be everywhere they’re needed, and tough enough to do the job when they get there. Most importantly, by taking the driver out of the vehicle with advanced autonomy and teleoperation, we can keep service men and women out of harm’s way,” he said.

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Astronomers believe they may have found evidence that one star in a faraway binary system may have eaten its own planets in the past. If true, this may well violate the generally accepted rules governing the formation of binary star systems.

The star system in question, HD 81809, lies in the constellation Hydra and is roughly 90 to 101 light-years from Earth. It consists of one main primary star, HD 81809A, which is now in its twilight years, having spent its hydrogen fuel.

The second, HD 81809B, is still a main-sequence star, but also has a noticeably different composition from its larger twin. Under “normal” circumstances, at least as far as we believe, binary stars typically form together from the same gas cloud. They also tend to form at roughly the same time.

According to researchers from the Technical University of Denmark, studying it, it has significantly more lithium, and the iron content appears different between them, too. In fact, the difference is about 3.7 times (0.57 dex in technical speak).

A case of hungry, hungry stars

While some variance would be expected, the research team believes that the differences are too large to be ignored. Something else has happened in the past, but what?

Well, the only logical answer seems to be that the “metal-rich” star must have swallowed planets or other planetary material sometime in the past. Likely candidates would be rocky planets (like our own Earth), which tend to be rich in iron, silicon, magnesium, etc.

If a star consumes them, its outer layers become chemically enriched, which can be detected from afar. This hypothesis is also supported by other evidence, such as what appears to be a debris disk around the star.

What likely happened, the team explains, is that the planet spiraled inwards towards the star, became orbitally unstable, and was eventually absorbed. All well and good, but the high levels of lithium may point to a very recent event.

Lithium usually doesn’t survive very long inside stars and may point to very fresh planetary materials being introduced. However, computer modeling suggests that the star would have needed to eat huge amounts of planetary material, roughly between 25 and 75 Earth-like bodies.

Planet-munching star caught red-handed?

But if this were the case, the level of lithium should be much higher than observed. “The models predict that such a metal-rich accretion would over-enrich lithium at the surface; matching the observed lithium instead requires accreting less than 6 M_⊕,” the team writes in the paper.

“This tension highlights the need for precise knowledge of the accreted material’s chemical composition,” they added.

While they cannot be entirely sure, the team believes that engulfment was likely recent and may have involved “unusual” composition planets. Either that, or only certain kinds of planets or materials were actually absorbed by the star.

Likely, we may never know, but whatever is going on with HD 81809B certainly deserves further research.

You can view the study for yourself in the journal arXiv.

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