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Opinion: Tesla and India is the right thing at the wrong time
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.
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.
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.
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
News
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
