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FBI taps Tesla Sentry Mode footage to help catch man behind alleged hate crimes

Credit: CourtListener

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It appears that some members of the Federal Bureau of Investigation (FBI) are now becoming familiar with Tesla’s built-in security features like Sentry Mode, which allows vehicles to record videos from their cameras to actively monitor their surroundings. This was undoubtedly the case in an incident back in December, which involved slashed tires, arson, and what appears to be a racially motivated attack against a church. 

In an affidavit dated April 15, 2021, FBI Special Agent Casey Anderson outlined the events that led to an incident that resulted in the destruction of the Martin Luther King, Jr. Community Presbyterian Church in Springfield, Massachusetts. The suspect behind the incident, 44-year-old Maine resident Dushko Vulchev, is a naturalized United States citizen from Bulgaria. As per the FBI agent’s affidavit, Vulchev had previously run afoul of the law prior to his apparent arson in December, having been convicted of threatening a foreign official in 2015 and a series of offenses such as domestic violence assault in 2017. 

The Martin Luther King, Jr. Community Presbyterian Church in Springfield, Massachusetts before the fires. (Credit: CourtListener)

The Attacks

In December 2020, the MLK Church experienced a series of fires, one of which eventually destroyed the whole building. The first of these fires were reported on December 13, when the fire department was deployed to extinguish a blaze behind the church. On the same day, a vehicle had its tires slashed two miles away from the church. The next day, a BMW about 1.5 miles away from the MLK church and a Tesla parked less than a mile away from the church had their tires slashed. In the case of the Tesla, its owner found that one of the vehicle’s wheels was also missing. 

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Another fire behind the Martin Luther King, Jr. Community Presbyterian Church was set on December 15, 2020, at around 6:32 p.m. The Springfield Police Department (SPD) Arson and Bomb Squad investigated the fire and promptly determined that the blaze had been intentionally ignited. Interestingly enough, another fire in the church was reported at 11:03 p.m. that same day. Upon investigation, the SFD reported that the blaze had been “intentionally set to eventually involve the structure” of the church. 

Things essentially calmed down until December 27, when a Dodge Charger had its tires slashed just 400-500 feet away from the MLK Church. At around 5:06 a.m. the next day, the American International College campus police reported a new blaze at the MLK Church. This time, the fire was started just outside the basement side door, where it burned through and up through the church’s main floor. The blaze essentially destroyed the church, and upon investigation, the SPD concluded that the fire was intentional. 

Photos of the MLK Church during the December 28, 2020 blaze. (Credit: CourtListener)

The Investigation

Investigators working on the case were able to obtain several video footage relevant to the case. In the first tire slashing incident on December 13, footage from the City of Springfield recorded a gray Chevy Cruze pulling up into the same parking lot as the vehicle that was attacked. The car was found to have been registered to the suspect, Vulchev. City video footage captured the suspect crossing the street in the direction of the MLK Community Center later that day. The gray Chevy Cruze was also recorded circling the MLK Church.

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Vulchev’s Chevy Cruze was sighted by city video footage once more the next day, when the BMW tire slashing incident transpired. As per the FBI agent’s affidavit, a while male matching Vulchev’s height, gait, and clothing, was spotted approaching the BMW. Later that day, a Tesla became the next victim of the suspect’s tire slashing tendencies. But this time around, the special agent didn’t just have a faraway shot of a man approaching a vehicle. This time around, authorities were able to get a clear shot of Vulchev as he was slashing and stealing the Tesla’s tires and stealing a wheel, thanks to Sentry Mode. Tesla’s built-in cameras even captured the suspect putting the stolen goods inside his trunk. 

Special Agent Casey Anderson related his experience with Teslas and their built-in cameras in his affidavit. “Based on my training and experience and this investigation, I am aware that the Tesla referenced above is equipped with cameras at various points around the body. ATF Special Agent Marc Maurino (“SA Maurino”) and I have reviewed video footage retrieved from the Tesla showing an individual that I can identify as Vulchev, based on my observation of Vulchev during the Vulchev PPD Interview. 

“The video footage from the Tesla shows Vulchev at a close distance crouching near the Tesla and using a tire iron to remove the wheels. Additional Tesla video footage captured Vulchev removing one of the Tesla’s wheels and placing it in the trunk of Vulchev’s car. Vulchev’s face is clearly visible in the video. Vulchev was wearing grey pants and a dark-colored sweatshirt, Adidas three-stripe sneakers, a black hat with two grey stripes, and light-colored work gloves, the agent noted in his affidavit. 

Vulchev and his vehicle were spotted around the MLK Church fires, as well as subsequent tire slashing incidents. 

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The MLK Church after the December 28, 2020 fire. (Credit: CourtListener)

The Arrest

On December 30, 2020, a complaint about a vehicle driving erratically was reported to authorities. When provided with the license plate of the vehicle in question, it was determined that the car was Vulchev’s. Police stopped the suspect’s vehicle on suspicion of erratic driving and possible links to the multiple tire slashing incidents. Since they were aware of the ongoing federal investigation into the fires against MLK Church, local authorities promptly contacted FBI Supervisory Special Agent of the Springfield Resident Agency Matthew Fontaine. 

Special Agent Fontaine arrived at the scene of the stop, and upon initial investigation, the FBI agent noted that the suspect may have been living in his car for some time. The FBI agent spoke with the suspect for about eight minutes outside, and immediately, Fontaine noted that Vulchev was wearing the sneakers that were captured clearly by Tesla’s Sentry Mode. PPD officers initially released the suspect, though he was arrested the day after over his links to the multiple tire slashing incidents and the Martin Luther King, Jr. Community Presbyterian Church fires. 

On January 4, 2021, the FBI and ATF conducted a search of Vulchev’s vehicle, where they found a computer, a hard drive, and several USB storage devices. A search of the computer revealed Vulchev’s shocking racially charged stance against non-white people. This was seen in messages to an ex-girlfriend—who currently has a lifetime protective order against Vulchev—which featured numerous slurs against Muslims and blacks. Vulchev’s apparent hate against non-whites was notable, as seen in a message to his ex-girlfriend where he was complaining about the race of ABC’s The Bachelorette. A search of the suspect’s phone revealed photos of several notable items, such as a firearm, an image of Adolf Hitler in an Adidas tracksuit, and a “White Lives Matter” mural, as well. 

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With these in mind, FBI Special Agent Casey Anderson noted that there is probable cause to believe that Vulchev committed damage to religious property, which is in violation of 18 USC §§ 247(c) and (d)(3), and the use of fire to commit a federal felony, which is in violation of USC § 844(h)(1). As per a press release from the US Department of Justice, Vulchev is currently in state custody and is due to make an initial appearance in federal court in Springfield at a later date. 

FBI Special Agent Casey Anderson’s complete affidavit could be accessed below. 

gov.uscourts.mad.233009.2.1_1 by Simon Alvarez on Scribd

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Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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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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