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From an early point in the Russian war in Ukraine, we’ve seen many unorthodox efforts to try to improve the chances of survival of fighting vehicles. Now, Russian trucks are receiving ‘dazzle paint,’ borrowing the same kind of tactic Russia has used for some of its most important military aircraft, to try to confuse seekers on standoff weaponry that use image-matching capability.

Several images showing the unusually painted Russian trucks have appeared on social media channels in recent days. So far, examples of Ural and KAMAZ heavy-duty truck designs have surfaced. There are at least two distinct patterns so far: a zebra-style application of broadly straight lines, and a more organic, leaf-like, swirling design. In both cases, they extend over most external surfaces, including the wheels and tires. It is not entirely clear if the white paint is applied over a layer of black, or portions of black, or if the white is simply coated over the standard base color of very dark green. It could be a mix of both application concepts, as well.

At first sight, the truck patterns recall the iconic paint scheme that the U.K. Royal Navy pioneered for its warships back in World War I. ‘Dazzle paint’ or ‘dazzle camouflage’ was devised in 1917 by official War Artist Norman Wilkinson, as a means of reducing losses to attacks by German submarines, or U-boats. The geometric patterns work by using highly contrasting color blocks, often heavily featuring black and white,  as part of a carefully constructed pattern that breaks up the form of the ship and makes it harder to judge range and perspective.

As you can read about here, this kind of naval camouflage scheme appeared again during World War II, and on several occasions since then.

When first introduced, dazzle paint was intended to trick the human eye, normally looking through a periscope. There was still a benefit to be had in protecting vessels after the introduction of improved rangefinders and radar. For the eye, it made it harder to judge a ship’s course and speed, as well as simply identifying it reliably.

The same basic principle is at work on the dazzle-painted Russian trucks, although now it’s an artificial eye — chiefly using electro-optical and/or infrared cameras — that is supposed to be fooled.

Increasingly, Ukrainian drones are using artificial intelligence (AI) to boost their combat effectiveness. The revolutions that are coming as a result of embedding of AI into lower-end drones is something you can read about in our past feature here. This includes machine vision: a process of the drone learning object recognition, identification, classification, and tracking, as well as providing recommendations for the operator on what to do, provided there is an operator at all and the drone is not running autonomously.

AI-enabled capabilities make lower-end drones more resistant to electronic warfare systems and make it easier for them to be employed in networked swarms. Above all else, they can result in the cutting of the invisible radio frequency tether of constant man-in-the-loop control that in many ways hampers the potential of this class of drones.

The drawback of machine vision that the Russian countermeasure is supposed to exploit is the onboard AI agent’s capacity for learning object recognition. While it may be able to recognize a 6×6 Ural, for example, out of a wide range of potential truck targets, if the appearance of the vehicle is distorted enough, it will not be positively identified, or at least meet the threshold of corroboration that would result in a kinetic act. However, still with many drones that feature AI assistance, a human operator stays in or on the loop for all critical decisions.

This raises the question of how successful the dazzle-painted trucks might be, although the thinking here presumably stresses avoidance of detection during the autonomous target-search phase, rather than the endgame of an engagement. It is also worth noting that these kinds of paint schemes only really have value in areas where they are unlikely to be seen by any Ukrainian human eyes, even remotely via a sensor; after all, they are far more conspicuous than their standard-painted counterparts. It’s also possible that a drone could be taught to specifically hunt these patterns, as nothing else on the battlefield would look like them and they would be confirmed hostile by default.

Overall, paint schemes are another logical, if extemporized response to a growing threat in the Russian rear areas, following the example of the Russian trucks loaded with logs as makeshift armor to protect against kinetic threats in the early phases of the war.

This has been followed by successive counter-drone measures, best exemplified by the increasingly complicated ‘cope cages,’ ‘turtle tanks,’ nets, and arrays of spikes that have appeared on a range of vehicles on both sides of the war.

Perhaps most apposite, however, is the example of Russian bombers and strike aircraft being covered with disused tires, something that first appeared in around August 2023. TWZ was first to postulate that these were most likely intended to confuse the seekers on Ukrainian cruise missiles and drones that use image-matching capability. This was subsequently confirmed by a senior U.S. military technologist.

A “sort of classic unclassified example that exists is like a picture of a plane from the top, and you’re looking for a plane, and then if you put tires on top of the wings, all of a sudden, a lot of computer vision models have difficulty identifying that that’s a plane,” Schuyler Moore, U.S. Central Command’s first-ever Chief Technology Officer, explained in September 2024.

Moore said this as part of a larger discussion about AI models and data sets.

It’s also worth noting that Russian combat ships based in Crimea also received unique shading to break up their silhouettes for the same purpose during this period.

As TWZ has explored in detail in the past, AI is now pushing drones toward a major new evolution, if not a revolution in capabilities.

As well as the possibility of operating in large groups or fully networked swarms, it means long-range one-way attack drones can conduct dynamic targeting deep in contested territory. Trucks, for example, can be hunted and struck far behind the front lines, where once they were safe and where air defenses are sparse.

This is a scenario we have set out in the past, too:

“Waves of similar drones could be sent to their own individual geographical ‘kill boxes,’ or defined areas of engagement. Collectively, they could put enemy targets at risk over a huge area persistently without ‘doubling up’ and attacking the same target twice. Using machine learning/AI and associated hardware, they could not just identify targets of interest, but also differentiate moving from still targets, to ensure they are indeed active (not destroyed or already damaged) vehicles. Meanwhile, they can be set to engage other target types, such as surface-to-air missile systems or other high-priority targets, regardless of whether they are static or not. Even troop movements on the ground could potentially be recognized and attacked. All the parameters as to what the drone can engage, and where it can do so, can be defined and tailored to each mission before launch.”

It is also worth noting that different types of sensors will be affected to different degrees by passive countermeasures like complex paint jobs. While electro-optical sensors may have issues with the patterns, infrared may not, especially at longer wavelengths.

TWZ has previously highlighted how AI algorithms can be rapidly trained in a digital environment, as well as incorporate data collected from actual real-world employment, to improve their ability to spot, categorize, and engage targets. It is, however, unclear how hard it would be to overcome infinite dazzle patterns. It could, as Schuyler Moore observed, lead to software programmers spending inordinate amounts of time on computer vision with very little to gain, once a new pattern arrived.

While it remains to be seen how effective the dazzle-painted trucks might be, they are another sign of drones, especially AI-enabled ones, being one of the key drivers of innovation on the modern battlefield.

Contact the author: thomas@thewarzone.com

CLOVIS, Calif. — There were many impressive performances at the CIF state track and field championships on Saturday, but the most breathtaking of all was one the fans packed inside Buchanan High’s Veterans Memorial Stadium did not see — Jaslene Massey’s throw of 196 feet and four inches in the discus — a mark that not only broke the state record but was the farthest throw ever by a girl in a U.S. high school meet.

The discus competition finished before any of the track events started and was held on an auxiliary field, but the Aliso Niguel senior got a standing ovation on the victory stand half an hour after her third throw thrust her into the record books.

“My goal was to for the gold first, then the mark,” said Massey, who will continue throwing at Oregon and may even compete in hammer and javelin. “I always dreamed of this and I wouldn’t be here without my support system.”

Aliso Niguel senior Jaslene Massey competes in discus at the CIF state track and field championships on Saturday.

(Steve Galluzzo / For The Times)

Massey waited several agonizing minutes while the distance was measured, but when the mark flashed on the scoreboard, she leaped in the air and screamed “Let’s go! Three more!”

After all, she still had three throws left.

“I wanted something big and I got something big,” said Massey, who defended her state title and topped the meet record of 186-9 set by Anna Jelmini of Shafter in 2009. “I had good warmups yesterday and today, and I knew I had it in me.”

To prove her historic hurl was no fluke, she came back with a 192-6 effort on her sixth and last throw. Shelbi Vaughan from Mansfield Legacy High in Texas set the American Junior record of 198-9¼ at the USA junior outdoor championships in 2012.

Massey later defended her shot put title with a throw of 52-9. She is the national leader in both events.

Also making history was Sherman Oaks Notre Dame senior JJ Harel, who repeated as boys high jump champion at 7-2. Harel cleared 6-9 on his third attempt to stay alive but still trailed Jay Woodson of American Canyon on misses until the bar was raised to 6-11. Harel cleared it on his first try while Woodson failed on his three attempts to ensure a second straight state title for Harel, who won with a height of 6-9 last year.

“I backed up on my first two attempts at 6-9 and that messed me up,” Harel said. “My heart was sinking and it went through my mind that I might finish second so when I cleared it that gave me adrenaline and muscle memory kicked in. At 6-11 I had such a great clearance, I knew I could get over at 7 and even at 7-2 I didn’t touch it.”

Sherman Oaks Notre Dame’s JJ Harel competes in the high jump at the CIF state track and field championships on Saturday.

(Steve Galluzzo / For The Times)

Harel cleared 7-2 on his first attempt — a personal best — tying for fourth on the national list this year. The bar was raised to 7-3½, giving Harel a chance to break the state record of 7-3¼ set by Lee Balkin of Glendale in 1979, but he was unsuccessful on three tries.

“I was 17 jumps deep and that took too much out of my legs,” Harel said of his unsuccessful efforts at the last height. “This season was an emotional roller coaster but I know I can get 7-3.”

Rosary won the girls 4×100-meter relay by a full second in 44.87 seconds.

Calabasas junior Malia Rainey won the girls 100 meters in 11.54. Maliyah Collins, who anchored Rosary’s relay, was third in 11.62, followed by Rainey’s teammates Marley Scoggins (11.63) and Olivia Kirk (11.63).

“I love my teammates, but today I had to focus on me — it was all about getting the win,” Rainey said. “Seeing my name up at the top made me so happy.”

Servite won the boys 4×100 in 39.73, shattering Hawthorne’s 38-year-old meet record of 40.24. Jorden Wells ran the first leg and was followed by Benjamin Harris, Kamil Pelovello and Robert Gardner. The Friars have run the seven fastest times in state history.

Servite’s record-setting 4×100-meter relay team (from left): Jorden Wells, Kamil Pelovello, Benjamin Harris and Robert Gardner.

(Steve Galluzzo / For The Times)

Harris won the boys 100 meters in a wind-aided 10.14 (the wind-legal state record remains 10.20 by Rodrick Pleasant of Gardena Serra in 2023) in a showdown against top qualifier Cy Lugo of Elk Grove, who won the 200 in a wind-aided 20.31 to edge Servite twins Jace (20.69) and Jorden Wells (20.79). Harris was fifth in 20.84.

“That’s the most locked in I’ve ever been in my whole career,” Harris said of his 100 triumph. “My mentality was kill or be killed.”

Arkansas-bound Braelyn Combe of Corona Santiago pulled off a distance trifecta, winning the 1,600 in 4:35.59, the 800 in 2:05.13 and anchoring the Sharks’ 4×800 relay, which won with a meet record time of 8:46.16. Afterward, Combe hugged her teammates. She pulled away from Stanford commit Chiara Dailey of La Jolla to repeat as the four-lap champion in the fourth-fastest time in the nation this year.

Long Beach Wilson junior Clara Adams doubled in the 400 (circling the track in 52.28, seven-tenths of a second ahead of teammate Saniah Varnado) and the 200 (clocking 23.40 to beat Amirat Temi Aganju of Pittsburg by 12-hundredths of a second.

Loyola’s Ejam Yohannes, left, celebrates after winning the boys 400 meters at the CIF state championships. Riverside King’s Maximo Zavaleta, right, wins the boys’ 1,600 meters.

(Steve Galluzzo / For The Times)

Varnado won the 300 hurdles in 39.95 and Wilson won the girls 4×400 relay in 3:36.17.

Wilson won its seventh girls team title and fourth in a row, tying the record set by Moore League rival Long Beach Poly from 2008-11.

Dailey won the 3,200 in 10:01.91. Irvine’s Summer Wilson was sixth in 10:16.89.

Transgender athlete AB Hernandez of Jurupa Valley won the girls triple jump in 42-8¾, won the high jump at 5-10 and was third in the triple jump, won by Ellie McCuskey of St. Ignatius with a leap of 20-3½.

Loyola’s Ejam Yohannes (45.73) clipped Servite’s Jaelen Hunter (46.05) at the wire in the boys 400 meters.

Riverside King senior Maximo Zavaleta won the 1,600 in 4:02.78 and the 3,200 in 8:52.47.

Servite closed the meet by winning the 4×400 relay in a state meet record 3:07.62 — the fastest time in the country this year — to repeat as the boys team champion with a state-record 60 points.

The all-you-can-eat venue says it has had a problem with ‘many customers’

An all-you-can-eat restaurant in Spain is introducing a “vomit fee” for diners who eat until they are sick on the premises. Sushi Toro, located in Gelves near Sevilla, said it had experienced a growing number of incidents in recent months involving customers “eating until they burst” and then vomiting.

The restaurant said the problem had affected tables and bathrooms, creating difficulties for staff and raising concerns over hygiene and customer service. In a statement shared on social media, restaurant staff said: “We have had many customers who keep ordering non-stop and eat until they burst, until they vomit. We have had vomit on the tables and in the bathrooms.”

They added that “the only solution” was to start charging vomiting fees. The restaurant, which promotes a fusion of “tradition and innovation”, offers a buffet menu featuring dishes prepared using fresh ingredients and specialist techniques. Prices range from €16.90 (£14.40) to €23.90 (£20.30), depending on the day and time of dining.

Sushi Toro bosses said their staff “strive hard to get orders out on time and maintain good hygiene” throughout all service periods. They urged diners to “order what you can eat” and apologised for any inconvenience caused by the new policy.

Demand for sushi has been surging in Spain in recent years, with diners increasingly opting for Asian seafood dishes over traditional Spanish fish fare.