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Opinion: Tesla and India is the right thing at the wrong time

Elon Musk and Narendra Modi, India's Prime Minister

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Tesla and India will not be working together any time soon, as new reports now indicate that Tesla has pulled its team responsible for entrance into the Indian market to other regions. Tesla and India might be a powerful one-two punch in the future, but in 2022, the two are just the right thing at the wrong time.

When Tesla first started making moves toward entering the Indian automotive market, there was a lot of excitement. The unbelievable potential of a partnership between the world’s leading electric car company and a government that primarily focuses on domestic manufacturing efforts, mainly due to the Make in India initiative, had people buzzing. However, there were still hoops to jump through. Any person with any sort of knowledge about India and cars knows that it is an expensive place to own one, especially if it was not built there. Getting cars from outside of India into the country doubles the cost of the vehicle on most occasions due to import duties. This is when Tesla started to realize how difficult this whole process might be.

Tesla places its India entry on hold after failing to secure lower import taxes: report

In routine negotiations, even with companies and governments, there is always a brief standoff period to see who will budge first. The hypothetical game of chicken can be magnified when dealing with two large entities, but eventually, something happens where someone makes a move, and things start to come together. I thought a great, recent, and relevant example of this would be the Elon Musk-Twitter buyout, where, as the board of the platform mozied over the Tesla CEO’s offer, new developments were few and far between, as expected. Nothing was going to move forward until someone budged.

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The issue is that sometimes people choose not to budge because their needs in a particular deal are non-negotiable. When the needs of both sides are non-negotiable, it complicates the entire ordeal, and this is what made the Tesla-India deal stagnate: Two large entities that had specific requirements to make something happen. Neither was asking for a small thing, so it is not necessarily unreasonable that Tesla put its plans for India on hold.

Tesla needed to test demand for its cars. It would only be able to do this by building them in Fremont, California, Austin, Texas, Brandenburg, Germany, or Shanghai, China, and then shipping them to India. The problem with this system was it would not be an accurate representation of what Tesla might be able to sell in the market, as the vehicles would still be subjected to massive import duties that would double the cost of the car in some cases. Only a small percentage of the population would be able to afford that, and with very little EV infrastructure in India, it made the company’s products even less attractive. Tesla was effectively stuck between a rock and a hard place because it had an interest in building and selling cars in India, it just needed to confirm that the people of India wanted to buy the cars. Indian government officials rarely offered commentary that was indicative of a willingness to budge.

India wanted Tesla to commit to building a new Gigafactory in their country, which would align with the government’s focus on domestic manufacturing efforts and would likely give officials enough to pull back import duties for Tesla. However, Tesla could not commit to this: there was no indication that demand would be high enough to justify an entire factory, and Tesla was not sure it would be able to export vehicles from the Indian factory to other countries. Given the economic situations across the world during the past two years due to the COVID-19 pandemic, neither entity would be able to budge from their needs.

India and Tesla were the right thing, just at the wrong time. Given the extreme demands that both Tesla and Indian officials needed, it was best to not beat a dead horse any longer and move on from the potential partnership, at least temporarily. Tesla does have a lot of potential in India, but it cannot justify purchasing massive land plots for a new facility, it cannot justify spending millions more on showrooms and service centers, and it can not adequately test the want for its vehicles with massive import taxes trailing behind every car sent to the market.

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Try again in a few years, hopefully.

I’d love to hear from you! If you have any comments, concerns, or questions, please email me at joey@teslarati.com. You can also reach me on Twitter @KlenderJoey, or if you have news tips, you can email us at tips@teslarati.com.

Joey has been a journalist covering electric mobility at TESLARATI since August 2019. In his spare time, Joey is playing golf, watching MMA, or cheering on any of his favorite sports teams, including the Baltimore Ravens and Orioles, Miami Heat, Washington Capitals, and Penn State Nittany Lions. You can get in touch with joey at joey@teslarati.com. He is also on X @KlenderJoey. If you're looking for great Tesla accessories, check out shop.teslarati.com

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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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