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How Starlink & T-Mobile's partnership will impact 5G for the better for AI cameras How Starlink & T-Mobile's partnership will impact 5G for the better for AI cameras

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How Starlink & T-Mobile’s partnership will impact 5G for the better for AI cameras

Credit: Smarter AI

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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.”

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“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. 

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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.”

 

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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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Note: Johnna is a Tesla shareholder and supports its mission. 

Your feedback is important. If you have any comments, or concerns, or see a typo, you can email me at johnna@teslarati.com. You can also reach me on Twitter at @JohnnaCrider1.

Teslarati is now on TikTok. Follow us for interactive news & more.

 

 

 

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Johnna Crider is a Baton Rouge writer covering Tesla, Elon Musk, EVs, and clean energy & supports Tesla's mission. Johnna also interviewed Elon Musk and you can listen here

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Tesla crosses major Unsupervised Self-Driving milestone

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Credit: Tesla

Tesla has reached a notable benchmark in its autonomous driving program after its Robotaxi fleet surpassed one million miles of unsupervised operation. The company made the announcement during its Cybercab event in Austin on September 3.

Tesla Vice President of AI Ashok Elluswamy told attendees he was happy to report the fleet had achieved one million miles of unsupervised Robotaxi operation as a testament to safety.

The new total marked a sharp increase from the 380,000 unsupervised miles Tesla disclosed during its second-quarter 2026 earnings update in late July.

In roughly six weeks, the company added about 620,000 miles. That acceleration followed Tesla’s decision to remove in-vehicle safety monitors from most of its operations outside the San Francisco Bay Area.

Credit: Tesla

Tesla first launched Robotaxi service in Austin in June 2025 with safety drivers present. It later began fully unsupervised rides and expanded into Dallas, Houston, Miami, Orlando, and Tampa. The San Francisco Bay Area remains the exception, where a safety monitor still rides in the vehicle under California permitting rules.

The company has not released a city-by-city breakdown of the one million unsupervised miles.

The milestone arrived as Tesla began offering public Cybercab rides in Austin. The purpose-built vehicle has no steering wheel or pedals and is designed only for autonomous ride-hailing. Production versions joined the existing fleet of modified Tesla vehicles already operating in the service.

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Tesla’s unsupervised mileage is growing at a double-digit weekly rate according to earlier company comments, yet its fleet size remains modest compared with established competitors. Waymo has accumulated more than 200 million fully autonomous rider-only miles. Tesla has described its own unsupervised operations as having recorded zero notable incidents in the period leading up to the July update.

The one-million-mile figure reflects Tesla’s shift from supervised testing to broader driverless service in multiple states. It also highlights the company’s strategy of using both existing Model Y vehicles and the new Cybercab to scale its network.

Credit: Tesla

Whether the rapid recent growth continues will depend on further city expansions, regulatory approvals, and the performance of the purpose-built Cybercab in everyday paid rides. Tesla has not specified how many of the latest miles involved the new vehicle versus the rest of the fleet.

The announcement underscores Tesla’s progress toward a larger robotaxi network while illustrating the remaining gap in total autonomous experience relative to longer-operating rivals.

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Tesla Robotaxi will be a 24/7 service: here’s when

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Credit: @AdanGuajardo/X

Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.

The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.

That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.

Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.

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Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.

By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.

Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.

Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.

If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.

That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.

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Tesla Full Self-Driving will now overtake manual driving to avoid disaster

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Credit: Tesla

Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.

Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.

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The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.

The intervention is meant as a last-resort safety net, not a replacement for attentive driving.

Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident

Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.

After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.

The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.

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Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.

The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.

If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.

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