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How Starlink & T-Mobile’s partnership will impact 5G for the better for AI cameras
Starlink and T-Mobile’s partnership will be revolutionary for cellular service and Smarter AI CEO Chris Piche had some thoughts on how the new partnership will impact 5G capability for the automotive industry.
Chris, who has created services including AT&T TV, BBM Video, Poly Video, and STUN/TURN/ICE shared his thoughts on the effect of 5G on vehicles and telecommunications in an interview with Teslarati.
AI Cameras, Tesla, Starlink & autonomous vehicles
Before founding Smarter AI, the Top 40 under 40 entrepreneur’s company created a technology that BlackBerry licensed to enable voice and video calling. This gave Chris a front-row seat to witness the speed at which technology can transform markets.
Smarter AI is a software platform for artificial intelligence cameras.
“Smarter AI is to cameras as Android and iOS are to phones,” he told me. The company’s first vertical market is focusing on transportation. Vehicle camera systems such as dash cams or other camera systems for larger vehicles are in this market.
“The connection here with Tesla, Starlink, and T-Mobile is all around autonomous transportation. Today’s autonomous transportation whether it’s in Tesla or another kind of vehicle all relies on line of sight situational awareness. In Tesla’s case, they rely on some cases exclusively and other cases primarily on cameras and computer vision to try to understand what’s happening around the car.”
“Many of their competitors use LiDAR and don’t rely on cameras. But in both cases, it’s all based on line of sight. What they can actually see in a straight line.”
Seeing beyond the line of sight
Chris told me that one of the new technologies that Smarter AI and other companies are developing is called vehicle to vehicle (V2V) or vehicle to everything else (V2X).
“These technologies enable cars to see beyond line of sight. Imagine you’re coming to an intersection and are planning to take a turn.”
Instead of waiting to see what’s ahead of you on the street, you’re turning on to, the technology will tell you exactly what is ahead. There could be a stopped car, a pedestrian about to jaywalk, or some type of temporary obstruction that you are unaware of.
“Imagine if there was a camera system located at the intersection. Imagine that as your vehicle is approaching that intersection, your vehicle could communicate with the camera and the camera could tell your vehicle that there’s some sort of obstacle.”
An autonomous vehicle would use this information to determine whether or not it can make that turn. This technology, Chris told me, relies on high-capacity and high-availability communications networks such as 5G.
Starlink & T-Mobile’s partnership could help with the challenges of implementing V2V and V2X
“One of the challenges with implementing technologies like V2V or V2X on top of 5G is that 5G deployments tend to be pretty good and getting better in large urban areas.”
5G is pretty spotty in Baton Rouge and personally, 4G LTE works faster than 5G does for me although there’s a tower across the street from me. Chris, who is in Las Vegas, said that the coverage is pretty good for his friend with AT&T. He doesn’t have AT&T and his coverage is pretty spotty like mine is.
“But this agreement with Starlink and T-Mobile has the promise or the potential to either eliminate or significantly reduce the spottiness in the 5G coverage and that will enable technologies that are designed on top of 5G such as V2V and V2X to work either more reliably in urban areas where 5G is already available but is a little bit spotty,” he said.
“It would also enable these technologies to work in other areas where there is no 5G. We think this is a really significant announcement in terms of the promise of autonomous transportation and bringing it much closer to being a reality.”
How V2V and V2X could improve Tesla’s Autopilot
Chris told me he’s been using Tesla’s Autopilot for around five years.
“It’s so good. It’s to the point that for the things it can see, it’s a way better driver than I am,” he said adding that when he drives for over a couple of minutes, he engages Autopilot. However, there are a couple of things that it lacks.
“It can’t see that far ahead and it lacks context. Sometimes, if there’s a car making a turn in front of my car, the Autopilot won’t understand the context that maybe this other car is momentarily in front of mine. And if I was driving, I’d keep driving. I wouldn’t take my foot off the accelerator or slam on the brakes unless I could see that something was going wrong with the turn that the other car was making.”
One way to improve Autopilot is through V2V or V2X, Chris explained.
“In V2V, my car would talk to the car that’s making the turn in front of me and they would orchestrate the speed and direction of both of the cars so that the car in front of me could make its turn and my car could continue driving without slamming on the brakes.”
“With V2X, that would enable my car to talk to the cameras, traffic lights, and intersections to gain situational awareness about either other cars that aren’t equipped with the same technology or about other objects such as bicycles, pedestrians, or other obstacles on the street.”
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Tesla FSD (Supervised) is about to go on “widespread” release
In a comment last October, Elon Musk stated that FSD V14.2 is “for widespread use.”
Tesla has begun rolling out Full Self-Driving (Supervised) V14.2, and with this, the wide release of the system could very well begin.
The update introduces a new high-resolution vision encoder, expanded emergency-vehicle handling, smarter routing, new parking options, and more refined driving behavior, among other improvements.
FSD V14.2 improvements
FSD (Supervised) V14.2’s release notes highlight a fully upgraded neural-network vision encoder capable of reading higher-resolution features, giving the system improved awareness of emergency vehicles, road obstacles, and even human gestures. Tesla also expanded its emergency-vehicle protocols, adding controlled pull-overs and yielding behavior for police cars, fire trucks, and ambulances, among others.
A deeper integration of navigation and routing into the vision network now allows the system to respond to blocked roads or detours in real time. The update also enhances decision-making in several complex scenarios, including unprotected turns, lane changes, vehicle cut-ins, and interactions with school buses. All in all, these improvements should help FSD (Supervised) V14.2 perform in a very smooth and comfortable manner.
Elon Musk’s predicted wide release
The significance of V14.2 grows when paired with Elon Musk’s comments from October. While responding to FSD tester AI DRIVR, who praised V14.1.2 for fixing “95% of indecisive lane changes and braking” and who noted that it was time for FSD to go on wide release, Musk stated that “14.2 for widespread use.”
FSD V14 has so far received a substantial amount of positive reviews from Tesla owners, many of whom have stated that the system now drives better than some human drivers as it is confident, cautious, and considerate at the same time. With V14.2 now rolling out, it remains to be seen if the update also makes it to the company’s wide FSD fleet, which is still populated by a large number of HW3 vehicles.
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Tesla FSD V14.2 starts rolling out to initial batch of vehicles
It would likely only be a matter of time before FSD V14.2 videos are posted and shared on social media.
Tesla has begun pushing Full Self-Driving (Supervised) v14.2 to its initial batch of vehicles. The update was initially observed by Tesla owners and veteran FSD users on social media platform X on Friday.
So far, reports of the update have been shared by Model Y owners in California whose vehicles are equipped with the company’s AI4 hardware, though it would not be surprising if more Tesla owners across the country receive the update as well.
Based on the release notes of the update, key improvements in FSD V14.2 include a revamped neural network for better detection of emergency vehicles, obstacles, and human gestures, as well as options to select arrival spots.
It would likely only be a matter of time before FSD V14.2 videos are posted and shared on social media.
Following are the release notes of FSD (Supervised) V14.2, as shared on X by longtime FSD tester Whole Mars Catalog.


Release Notes
2025.38.9.5
Currently Installed
FSD (Supervised) v14.2
Full Self-Driving (Supervised) v14.2 includes:
- Upgraded the neural network vision encoder, leveraging higher resolution features to further improve scenarios like handling emergency vehicles, obstacles on the road, and human gestures.
- Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
- Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances.
- Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
- Added additional Speed Profile to further customize driving style preference.
- Improved handling for static and dynamic gates.
- Improved offsetting for road debris (e.g. tires, tree branches, boxes).
- Improve handling of several scenarios including: unprotected turns, lane changes, vehicle cut-ins, and school busses.
- Improved FSD’s ability to manage system faults and improve scenarios like handling emergency vehicles, obstacles on the road, and human gestures.
- Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
- Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances).
- Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
- Added additional Speed Profile to further customize driving style preference.
- Improved handling for static and dynamic gates.
- Improved offsetting for road debris (e.g. tires, tree branches, boxes).
- Improve handling of several scenarios, including unprotected turns, lane changes, vehicle cut-ins, and school buses.
- Improved FSD’s ability to manage system faults and recover smoothly from degraded operation for enhanced reliability.
- Added alerting for residue build-up on interior windshield that may impact front camera visibility. If affected, visit Service for cleaning!
Upcoming Improvements:
- Overall smoothness and sentience
- Parking spot selection and parking quality
News
Tesla Model X lost 400 pounds thanks to these changes
The Tesla Model X has always been one of the company’s most loved vehicles, despite its low sales figures, which can be attributed to its high price tag.
However, the Model X has been a signature item on Tesla’s menu of cars, most notably recognized by its Falcon Wing Doors, which are aware of its surroundings and open according to what’s around it.
But recent improvements to the Model X were looking slim to none, but it appears most of the fixes actually happened under the body, at least according to Tesla’s Vice President of Powertrain, Lars Moravy.
In a recent interview with Car and Driver, Moravy detailed all of the changes to the 2026 iteration of the vehicle, which was about 400 pounds lighter than it was originally. The biggest change is a modification with the rear motor, switching from an induction-type motor to a permanent-magnet design and optimizing the half-shafts, which shed about 100 pounds.
Tesla also got “almost 80 pounds out of the interior bits and pieces,” which “included making parts thinner, different manufacturing process choices, and incorporating airbag-deployment requirements into the headliner fabric,” the report said.
Additionally, the standard five-passenger, bench seat configuration saved 50 pounds by ditching pedestal mounting. This also helped with practicality, as it helped the seat fold flat. Engineers at Tesla also saved 44 pounds from the high-voltage wiring through optimizing the wiring from the charge-port DC/DC converter and switching from copper to aluminum wiring.
Tesla makes a decision on the future of its flagship Model S and Model X
Tesla also simplified the cooling system by reducing the number of radiators. It also incorporated Nürburgring cooling requirements for the Plaid variant, which saved nearly 30 pounds.
Many Tesla fans will be familiar with the megacastings, manufactured in-house by presses from IDRA, which also saves more than 20 pounds and boosts torsional stiffness by around 10 percent. Tweaks to the suspension also saved 10 pounds.
People were truly disappointed with what Tesla did with the Model S and Model X, arguing that the cars needed a more severe exterior overhaul, which might be true. However, Tesla really did a lot to reduce the weight of the vehicle, which helps increase range and efficiency. According to Grok, every 200 pounds removed adds between 7 and 15 percent to range estimations.
This makes sense considering the range estimations both increased by 7 percent from the Model X’s 2025 configuration to the 2026 builds. Range increased on the All-Wheel-Drive trim from 329 miles to 352 miles, while the Plaid went from 314 miles to 335 miles.