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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. 

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“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).

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“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.

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“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. 

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“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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The Boring Company just doubled its tunneling power in Nashville

The Boring Company’s Prufrock MB2 is commissioned and ready to mine beneath Nashville’s streets.

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The Boring Company’s second tunnel boring machine, Prufrock MB2, is officially ready to dig in Nashville. The company confirmed the news on X, posting: “Prufrock-MB2 is ready to mine in Nashville! MB2 commissioning is complete, including the brief 11 rpm rotation shown here. Will MB2 catch up to MB1, who had quite the head start? And Prufrock-MB3 ships in August!”

MB2 arrives with meaningful improvements over its predecessor. Lessons learned from the launch and operation of MB1 have already been applied to MB2 to improve efficiency and prepare the machine for launch.

Traditional tunnel boring machines operate in a stop-and-go cycle, digging roughly five feet, halt, erect precast concrete segments to line the tunnel wall, then resume. That repeated interruption is one of the main reasons conventional tunneling is slow and expensive. Prufrock is designed to install the tunnel liner simultaneously with mining, eliminating the need to stop every five feet. The machine also skips the need for excavated launch pits. Prufrock arrives on a truck, tilts down, and launches into the ground within 24 hours. And when the tunnel is complete, it emerges from the ground and drives to its next launch site on a trailer, eliminating the need for expensive cranes or pit excavation. The machine is also fully electric and runs with zero people in the tunnel during normal operations, controlled remotely from a surface operations center.

It won’t be long before we hear of another major update on The Boring Company’s Music City Loop project – a planned underground transit network beneath Nashville that would move passengers in electric vehicles through a series of tunnels at highway speeds, and bypassing surface traffic entirely. Nashville was selected in part because of its strong rock conditions that suits the Prufrock machines well, and relatively less regulatory hurdles.

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Progress has been steady on multiple fronts. All 37 permits and approvals required ahead of tunneling have been obtained, out of 45 total. Key wins include a fully executed TDOT tunnel permit authorizing 25 miles of tunnel, unanimous airport authority approval for a Nashville International Airport station, and the city’s first residential station agreement serving downtown tower residents.

With MB1 already tunneling, MB2 now commissioned, and MB3 shipping in August, Nashville is becoming something of a live proving ground for scaled tunnel boring. The broader ambition is not limited to one city. The Boring Company’s stated goal is to make underground transportation a practical alternative to surface roads across major metro areas. Nashville is one of many cities, including a successful Las Vegas tunnel system, where that idea is being put to the test at real speed.

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Tesla urges New Jersey owners to oppose new bill that could block Robotaxi

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Credit: Grok

Tesla has launched a direct campaign targeting its customers in New Jersey, sending emails that warn of pending legislation that could effectively block true driverless technology in the state.

The email focuses on Senate Bill S.1677 and Assembly Bill A.3968, measures intended to create a three-year autonomous vehicle pilot program but laden with requirements that Tesla argues make unsupervised Robotaxis impossible.

According to the email, the bills impose “restrictions so severe that true driverless deployment would remain illegal.” Specific hurdles include mandates for human safety drivers during operations, multimillion-dollar insurance minimums, reportedly $5 million, and thresholds like 100,000 miles of demonstrated safe autonomous driving before any driverless approval.

Tesla contends these are arbitrary barriers that ignore real-world performance data and favor entrenched competitors over innovative technologies like its Full Self-Driving (FSD) system.

The push comes as Tesla has started expanding Robotaxi operations in states like Texas, where unsupervised vehicles are already providing rides in several cities. New Jersey, by contrast, risks falling behind. The company highlights in the email communication that more than 94 percent of serious crashes result from human error, meaning impairment, distraction, or fatigue. These are all problems that Robotaxis eliminate entirely.

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In 2025, New Jersey recorded 582 traffic deaths, underscoring the human cost of delayed adoption.

Tesla’s outreach stresses the transformative potential of robotaxis. For families, they could offer safer school runs without drowsy or distracted drivers. For seniors and people with disabilities, robotaxis promise independence and reliable mobility.

In areas with limited public transit, they could deliver affordable, on-demand transportation, reducing congestion, emissions, and overall transportation costs. Economically, the company warns that restrictive rules could cost New Jersey jobs, innovation investment, and billions in potential growth as autonomous ride-hailing scales elsewhere.

Supporters of the legislation, including Sen. Andrew Zwicker, describe the pilot as a cautious framework with strong safety oversight, including incident reporting, expert task forces, and restrictions in sensitive zones like school areas. They view it as balancing innovation with public protection.

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Tesla and pro-AV advocates counter that the bill lacks technology neutrality, creates insurmountable entry barriers for commercial deployment, and prioritizes process over outcomes — effectively functioning as a de facto ban on services like Robotaxi.

This latest clash echoes Tesla’s past battles in New Jersey over direct vehicle sales. The email directs owners to Tesla’s advocacy platform, where they can send customized messages to legislators calling for amendments: outcome-based safety standards, open competition, and clear pathways for fully driverless commercial operations.

As hearings approach, Tesla’s campaign frames the issue as a choice between protecting the status quo and embracing life-saving progress. With robotaxi technology already proving itself in permissive states, New Jersey owners are being asked to ensure their state doesn’t lock out the future of transportation.

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Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest

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Credit: TESLARATI

Turn-by-turn navigation is not new technology.

For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.

Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.

Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much

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Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.

Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.

Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes, we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.

But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.

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This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.

More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.

It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?

Multiple Data Sources

First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.

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Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.

Persistent Learning

FSD seems to struggle with persistent learning from driver interventions.

Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.

This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.

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I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.

Reasoning, Scaling, and Intuition

Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.

Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.

Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.

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Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.

Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.

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