News
“Smart skin” can identify weaknesses in bridges and airplanes using laser scanner
Recent research results have demonstrated that two-dimensional, on-demand mapping of the accumulated strain on metal structures will soon be a reality thanks to an engineered “smart skin” that’s only a fraction of the width of a human hair. By utilizing the unique properties of single-walled carbon nanotubes, a two-layer film airbrushed onto surfaces of bridges, pipelines, and airplanes, among others, can be scanned to reveal weaknesses in near real-time. As a bonus, the technology is barely visible even on a transparent surface, making it that much more flexible as an application.
Stress-inducing events, along with regular wear and tear, can deform structures and machines, affecting their safety and operability. Mechanical strain on structural surfaces provides information on the condition of the materials such as damage location and severity. Existing conventional sensors are only able to measure strain in one point along one axis, but with the smart skin technology, strain detection in any direction or location will be possible.
How “Smart Skin” Technology is Used
In 2002, researchers discovered that single-wall carbon nanotubes fluoresce, i.e., glow brightly when stimulated by a light source. Later, the fluorescence was further found to change color when stretched. This optical property was then considered in the context of metal structures that are subject to strain, specifically to apply the property as a diagnostic tool. To obtain the fluorescent data, researchers applied the smart skin to a testing surface, irradiated the area with a small laser scanner, and captured the resulting nanotube color emissions with an infrared spectrometer. Finally, two-dimensional maps of the accumulated strain were generated with the results.

The primary researchers, Professors Satish Nagarajaiah and Bruce Weisman of Rice University in Texas, have published two scientific papers explaining the methods used for achieving this technology and the results of its proof-of-principle application. As described in the papers, aluminum bars with holes or notches in areas of potential stress were tested with the laser technique to demonstrate the full potential of their invention. The points measured were located 1 millimeter apart, but the researchers stated that the points could be located 20 times closer for even more accurate readings. Standard strain sensors have points located several millimeters apart.
What Are Carbon Nanotubes?
Carbon nanotubes (CNTs) are carbon molecules that have been structurally modified into cylinders, or rather, rolled up sheets of carbon atoms. There has been some evidence suggesting that CNTs can be formed via natural processes such as volcanic events. However, to really capitalize on their unique characteristics, production in a laboratory environment is much more efficient.
Several methods can be used for production, but the most widely used method for synthesizing CNTs is chemical vapor deposition (CVD). This process combines a catalyzing metal with a carbon-containing gas which are heated to approximately 1400 degrees Fahrenheit, triggering the carbon molecules to assemble and grow into nanotubes. The resulting formation resembles a forest or lawn grass, each trunk or blade averaging .43 nanometers in diameter. The length is dependent on variables such as the amount of time spent in the high heat environment.

Besides surface analysis, carbon nanotubes have proven invaluable in many research and commercial arenas, their luminescence being only one of many properties that can improve and enable other technologies. Their mechanical tensile strength is 400 times that of steel while only having one sixth the density, making them very lightweight. CNTs also have highly conductive electrical and thermal properties, are extremely resistant to corrosion, and can be filled with other nanomaterials. All of these advantages open up their applications to include solar cells, sensors, drug delivery, electronic devices and shielding, lithium-ion batteries, body armor, and perhaps even a space elevator, assuming significant advances overcome its hurdles.
Next Steps
The nanotube-laced smart skin is ready for scaling up into real-world applications, but its chosen industry may take time to adopt given the general resistance to change in a field with long-standing existing technology. While awaiting embrace in the arena it was primarily designed for, the smart skin has other potential uses in engineering research applications. Bruce Weisman, also the discoverer of CNT fluorescence, anticipates its advantages being used for testing the design of small-scaled structures and engines prior to deployment. Niche applications like these may be the primary entry point into the market for some time to come. In the meantime, the researchers plan to continue developing their strain reader to capture simultaneous readings from large surfaces.
Elon Musk
Elon Musk reveals unfortunate truth of Tesla Full Self-Driving development
In a candid reply to a dramatic video of Tesla’s Full Self-Driving (FSD) system averting disaster, Elon Musk laid bare a harsh reality facing autonomous vehicle technology.
Tesla’s Full Self-Driving suite is one of the most significant technological developments in terms of passenger travel in decades, but it is not all sunshine and rainbows, even with major strides in safety, CEO Elon Musk revealed.
In a candid reply to a dramatic video of Tesla’s Full Self-Driving (FSD) system averting disaster, Elon Musk laid bare a harsh reality facing autonomous vehicle technology.
The clip shows a Model 3 traveling at over 65 mph on a foggy, rain-soaked highway when a pedestrian suddenly steps into traffic.
Full Self-Driving instantly detects the threat and swerves safely, preventing what could have been a fatal collision for both the pedestrian and the driver’s cousin.
Musk’s response was unequivocal:
“Tesla self-driving saves a lot of lives – the statistics are unequivocal. That doesn’t mean it’s perfect, of course.” Even with a projected 10x safety improvement over human drivers, FSD would still prevent roughly 90% of the world’s approximately one million annual auto fatalities. The remaining 10%—roughly 100,000 deaths—would expose Tesla to relentless lawsuits. Meanwhile, the vast majority of lives saved would go unnoticed. “The 90% who are still alive mostly won’t even know that Tesla saved them. Nonetheless, it is the right thing to do.”
This “unfortunate truth,” as Musk implicitly framed it, highlights a fundamental asymmetry in how society perceives safety technology. Human drivers cause the overwhelming majority of crashes through distraction, fatigue, or error.
Tesla self-driving saves a lot of lives – the statistics are unequivocal.
That doesn’t mean it’s perfect, of course.
Even when we improve safety 10X, saving 90% of the million lives lost in auto accidents every year, Tesla will still get sued for the 10% who did die. The 90%… https://t.co/OrNB1mO5eF
— Elon Musk (@elonmusk) April 6, 2026
Yet when FSD errs, the incident becomes headline news and a courtroom target. Prevented tragedies, by contrast, leave no trace.
Survivors simply continue their journeys, unaware of the split-second intervention that kept them alive. The result is a distorted public narrative that amplifies failures while rendering successes invisible.
We have seen this through various headlines throughout the years, including the mainstream media’s obsession with only mentioning the manufacturer’s name in the instance of an accident when it is “Tesla.”
Opinion: Tesla Autopilot NHTSA investigation headlines are out of control
The video’s real-world example underscores FSD’s current capabilities. In near-zero visibility, the system’s cameras and neural network reacted faster than any human could, demonstrating the life-saving potential Musk cites.
Tesla’s latest safety data already shows FSD (Supervised) performing significantly better than the U.S. average, with crashes occurring far less frequently per mile driven.
Still, regulatory scrutiny, liability concerns, and media focus on edge-case failures continue to slow widespread adoption. Musk’s frank admission suggests Tesla is prepared to push forward despite the legal and perceptual headwinds.
As FSD edges closer to unsupervised autonomy, Musk’s post serves as both a progress report and a reality check. The technology is already saving lives today.
The unfortunate truth is that proving it and scaling it responsibly will require society to value statistical lives saved as much as dramatic stories of those lost. In the race toward safer roads, perception may prove as formidable an obstacle as the fog and rain in that viral video.
News
Tesla Full Self-Driving v14.3: First Impressions
Tesla started rolling out Full Self-Driving v14.3 to Early Access Program (EAP) members earlier today, and I had the opportunity to see some of the improvements that were made from v14.2.2.5.
While a lot of things got better, and I truly enjoyed using Full Self-Driving again after being stuck with the widely confusing and frustrating v14.2.2.5, Tesla still has one major problem on its hands, and it has to do with Navigation and Routing. I truly believe those issues will be the biggest challenges Tesla will face with autonomy: the car simply going the correct way, not conflicting with what the navigation says, and taking the simplest and most ideal route to a destination.
Here’s what I noticed as an improvement with my first hour with v14.3. This is not a full review, nor is it reflective of everything I will likely experience with this new version. This is simply what I saw as a noticeable improvement from the past version, v14.2.2.5.
There is also a more streamlined version on X, available at the thread below:
Tesla Full Self-Driving v14.3 testing now: pic.twitter.com/9UuP11Fv9f
— TESLARATI (@Teslarati) April 7, 2026
Yellow Light Behavior is Significantly Better
On v14.2.2.5, I had so many instances of the car slamming the brakes on to stop at a yellow light when it was clearly the safer option to proceed through. There were several times when the car would be about 20 feet from the line, traveling at 15-20 MPH, the light would turn yellow, and it would slam the brakes to stop. I would nudge it through yellow lights constantly because of this by putting my foot on the accelerator.
The instances I’m talking about here would not have been close calls — the car would have likely moved through the intersection completely before the light would turn red.
On multiple occasions this evening, FSD proceeded through yellow lights safely, without hesitation or any brake stabbing. It was refreshing:
🚨 Here’s an EXCELLENT example:
v14.2.2.5 would have slammed the brakes and stopped at this stop sign. I would have tapped the accelerator to proceed.
You can see the light turns yellow and the car makes — in my opinion — the correct decision to proceed. https://t.co/hHMikimkbp pic.twitter.com/Iesta1OYoV
— TESLARATI (@Teslarati) April 7, 2026
This was a huge complaint with v14.2.2.5. Sometimes, it’s a safer option to go through a yellow light, especially when you have traffic behind you. It’s a great way to get rear-ended.
Parking Performance
I had four instances of parking, and FSD v14.3 really did a flawless job. I was very impressed with how solid it was, but also with how efficiently it moved into the spot. When there was traffic around with past versions, I usually chose to park manually just because FSD took its time getting into a spot. I don’t see that being an issue anymore.
I complained about parking a lot and shared several images on X and Facebook of those examples:
Still a few issues with parking on FSD v14.2.2.4 pic.twitter.com/BphvVWDPqe
— TESLARATI (@Teslarati) February 5, 2026
No issues with it this evening. 4/4. Here are two looks:
Highway Performance
FSD v14.3 passed the five cars shown in this image:
The sixth was 200-300 yards ahead of the fifth. In v14.2.2.5, FSD would usually stay in the left lane, especially on Hurry and Mad Max. It did not do that, as it instead chose to get back over in the right lane after passing the final car.
Speed was not much of a concern here, even though it was going 21 MPH over. Although it was fast, I did have a line of cars behind me traveling at the same speed, and FSD had just merged about a half mile prior, so I chose to let it continue.
There were no instances of camping in the left lane for extended periods of time. I do want to do more testing with the Speed Profiles because they were in need of some work with the previous version. I am starting to side with those who want a Max Speed setting, which was removed last year.
Navigation and Routing Still Need Work
I was heading back toward where I came from, so I turned “Avoid Highways” on to take a different way. This confused the Routing system, and instead of turning left, then right, as the Routing said, the car turned right, then indicated for another right, basically going in a big rectangle. The car ignored the second right-hand turn and continued straight. I ended up turning “Avoid Highways” off and letting the car pick the same routing option as what took me here.
I have truly complained so much about Navigation and Routing that I’m starting to feel sort of bad. It is obviously such a massive challenge for some reason, but I am confident it will improve. I recall seeing Tesla hiring someone for this role a few months back, so perhaps there is hope for it to get better.
Smarter Behavior When Approaching Exits/Routing
This probably should be grouped in with Highway Behavior, but I wanted to highlight it on its own.
The highway exit pictured was always frustrating for v14.2.2.5. In the Hurry speed profile, I have seen it try to execute passes on multiple cars with as little as 0.6 miles to spare before taking the exit.
With three cars ahead of it, it chose to reduce speed and just wait until the exit. It was refreshing to see an improvement here, so I hope this behavior persists. Sometimes there’s just no reason to pass when you’re less than a mile from getting off the highway anyway.
Larger Visibility Warnings
Tesla seems to have increased the size of these “Camera Visibility Limited” warnings. Previously, they were just small thumbnails:
🚨 The warnings of “Camera Visibility Limited” appear to be larger with v14.3
Previously, it was a small thumbnail. Haven’t seen it this magnified before. https://t.co/iKJLsZ8P4Q pic.twitter.com/qRWwFyIZNd
— TESLARATI (@Teslarati) April 7, 2026
Stop Sign Behavior
This is probably the biggest improvement of all, because how it behaved at Stop Signs in v14.2.2.5 was so incredibly terrible and disruptive to the flow of a busy intersection.
There are several four-way, all-stop intersections near me. In the past, FSD would stop well behind the Stop Sign or the white-painted line on the road. It would then inch forward, stopping again at this line, essentially making two stops at a single intersection.
If there is visibility, I don’t truly care where FSD stops, as long as it stops once. Stopping twice just isn’t ideal or logical. I can’t imagine many humans would do it, I know I wouldn’t.
I didn’t have that issue this evening:
🚨 Here’s a look with some commentary – Previously, FSD would stop where it did in this video, then again at the white line, before proceeding. https://t.co/xwyVGMy28y pic.twitter.com/MObgUa7DoA
— TESLARATI (@Teslarati) April 7, 2026
This was pretty tight, too, in the sense that both my car and the other one got to the intersection at the same time. FSD may have stopped first, but the other vehicle was probably around the same point that I was when FSD decided to stop. I was happy to see the assertiveness to proceed; it felt like it was ideal to just go through. I was happy it didn’t stop a second time up at the line. I’d be fine if it stopped at the line, as long as that was the only stop it made.
News
Tesla Full Self-Driving v14.3 rolls out: here’s what’s new
We are in EAP and will be on the road with v14.3 in the coming hours, so we’ll have a lot of things to discuss over the next few days, especially coming from v14.2.2.5, which I called the most “confusing” FSD release of all time.
Tesla has officially started rolling out Full Self-Driving v14.3 to Early Access Program (EAP) members, and there are a lot of new improvements.
We are in EAP and will be on the road with v14.3 in the coming hours, so we’ll have a lot of things to discuss over the next few days, especially coming from v14.2.2.5, which I called the most “confusing” FSD release of all time.
🚨 Tesla Full Self-Driving v14.3 is here and it is coming with so many new features
Looks like there will be some MAJOR improvements to the general performance.
Truly seems like it will be significantly different than v14.2 pic.twitter.com/mhdfBLuDup
— TESLARATI (@Teslarati) April 7, 2026
Tesla brought out a lot of improvements, according to the v14.3 release notes, which list a vast number of fixes, new features, and new capabilities.
Here’s what Tesla’s release notes for the v14.3 release state:
- Improved parking location pin prediction, now shown on a map with a P icon.
- Increased decisiveness of parking spot selection and maneuvering.
- Rewrote the Al compiler and runtime from the ground up with MLIR, resulting in 20% faster reaction time and improving model iteration speed.
- Enhanced response to emergency vehicles, school buses, right-of-way violators, and other rare vehicles.
- Mitigated unnecessary lane biasing and minor tailgating behaviors.
- Improved handling of small animals by focusing RL training on harder examples and adding rewards for better proactive safety.
- Improved traffic light handling at complex intersections with compound lights, curved roads, and yellow light stopping – driven by training on hard RL examples sourced from the Tesla fleet.
- Upgraded the Reinforcement Learning (RL) stage of training the FSD neural network, resulting in improvements in a wide variety of driving scenarios.
- Upgraded the neural network vision encoder, improving understanding in rare and low-visibility scenarios, strengthening 3D geometry understanding, and expanding traffic sign understanding.
- Improved handling for rare and unusual objects extending, hanging, or leaning into the vehicle path by sourcing infrequent events from the fleet.
- Improved handling of temporary system degradations by maintaining control and automatically recovering without driver intervention, reducing unnecessary disengagements.
Tesla also listed a handful of future improvements as well:
- Expand reasoning to all behaviors beyond destination handling
- Add pothole avoidance
- Improve driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting situations
CEO Elon Musk has said that v14.3 could be “where the last big piece of the puzzle finally lands.” We have high expectations for this release because, in a lot of ways, v14.2’s final version was extremely disappointing and seemed to be a regression more than anything.
Nevertheless, Full Self-Driving v14.3 is going to be quite an interesting test, considering this is also the first time Musk has stated it will feel like the car will be “sentient.”
Reasoning will be a bigger piece of the puzzle with this release, although there were some elements of it in v14.2.
Tesla AI Head says future FSD feature has already partially shipped
We plan to travel plenty of miles with it over the next few days, so we’ll keep you posted on what our thoughts are.

