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Tesla's battery acquisitions are paying off in spades, and giving rivals a lot of pain
There was a time, not too long ago, when Tesla skeptics questioned the company’s focus in designing and producing its own batteries with a dedicated partner like Panasonic and a facility like Gigafactory 1 in Nevada. Batteries, after all, are available off-the-shelf from companies like LG Chem, and it seemed pretty futile for Tesla to insist that it needs its own battery supply for its future business.
Fast forward to 2020, and Tesla’s extreme focus on battery development is paying off in spades. Over the years, Tesla has acquired multiple companies that have, in some way, enabled the company to accelerate or improve its products’ batteries. Included among these are Grohmann Automation, whose machines are the bread and butter in Gigafactory 1, Maxwell Technologies, and more recently, HIBAR systems.
At this point, Tesla’s batteries have pretty much become the gold standard for EVs, and the company appears to be well on its way towards releasing vehicles that have a range of 400 miles or more. The Plaid Model S and X will likely be the first of these, as well as the next-gen Roadster, which will have 620 miles of range. Even the reasonably-priced Cybertruck tops out at over 500 miles of range per charge. Massive battery developments are needed to achieve these, and Tesla seems to have done it, or at least is well on its way.
This does not appear to be true for other OEMs attempting to enter the electric vehicle market. As veteran companies unveiled their EVs, and as none have really managed to hold a candle to Tesla’s flagship Model S in terms of range, it is becoming evident that the electric car maker’s investments in batteries may have actually been the right strategy all along. Daimler, for one, seems to be feeling this inconvenient truth, with works council chief Michael Brecht explaining during a recent interview with Manager Magazin that Tesla’s battery-related acquisitions are actually having an effect on Germany’s EV efforts.
Daimler launched its first EV, the Mercedes-Benz EQC, in 2018, and it has not really lived up to the hype. Despite being dubbed at some point as a potential “Tesla Killer” due to its pedigree and excellent German build quality, the all-electric SUV has faced battery shortages and low sales. Registrations in Germany for the vehicle only show about 55 units sold to date despite all the ad campaigns dedicated to the SUV. Battery supply shortages have also forced Daimler to cut the annual production target of the EQC by 50% from 60,000 to just 30,000.
Quite interestingly, Brecht partly blames Tesla for some of the challenges facing the EQC today. Explaining his points to the publication, he argued that one of the reasons Daimler is struggling with battery demand is because Tesla bought Grohmann Engineering, which has valuable technology that could be used for battery-related developments and activities. Brecht also mentioned that Grohmann was actually hired by Mercedes-Benz to build up its own battery manufacturing capacity.
Brecht’s statements are notable since it is quite rare to see a veteran car manufacturer actually point the finger at Tesla to explain the dire condition of its own EV program. One can only hope that perhaps, the EQC would be a lesson that Daimler could learn from. After all, Daimler, among German automakers, would likely have no issues tapping into Tesla’s established technologies, batteries and powertrains alike, as the two companies have already worked together in the past. Elon Musk has stated that eventually, Tesla may be open to selling its batteries and powertrains with other OEMs. If this were to happen, it would be wise for Daimler to wait right in front of the line to avoid another EQC-sized flop.
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.”
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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
