Tesla has recently detailed some of the improvements it’s working on for the Supercharger network, especially as it has slowly been expanding access to the stations to electric vehicles (EVs) from other brands.
As Tesla has begun giving new non-Tesla EV brands access to the Supercharger network this year, many have also noticed how charging port placement on other vehicles can make it harder for short cables to reach—often requiring drivers to block other charging stalls to plug in.
However, in a post on X from the Tesla Charging account on Friday, the company has highlighted four things it’s aiming to improve for all EV owners, including a boost to the number of long charging cables at its Supercharger stations. In particular, Tesla says that within the next 18 months, it will have more long V4 Supercharger cables at stations than short ones, as it aims to start upgrading shorter cables to meet the needs of other EV brands.
In the post, Tesla outlines the following four goals it’s working on as it dives into improving the charging network:
- Making stall availability more accurate than ever
- Increasing the number of long Supercharging cables
- Modifying Supercharger stations to avoid blocking stalls
- Encouraging manufacturers to follow suit with charge port locations
Tesla makes it easier to find towing-compatible Superchargers
Tesla says that the latest software update makes stall availability estimates even more accurate, as the vehicle is now able to detect when EVs with a non-Tesla charge port location are plugged into a short-cable stall. This algorithm is set to continue improving over time, making it easier for drivers to get an accurate picture of how many stalls are available, as well as how many are blocked out by those needing to park unconventionally to reach.
The updated stall availability algorithm is a big improvement, with nearby refresh rates now every ~15 seconds. We know car types plugging in and mapped out Supercharger site layouts, to know which stall is not available at short cable sites. Your Tesla's touchscreen now shows… https://t.co/5PF7wruNhQ— Max de Zegher (@MdeZegher) November 22, 2024
In addition, Tesla says it has already modified over 1,500 Supercharger stations to make it so that EV drivers never have to utilize more than two charging spaces to charge, and it plans to continue working on updating sites going forward. Lastly, the company has gone directly to other EV manufacturers to encourage them to move charging ports to the rear left of their vehicles or to the front right, in order to maximize compatibility with the company’s Superchargers.
As one example in March, Tesla’s Lead Cybertruck Engineer Wes Morrill encouraged Rivian CEO RJ Scaringe to re-consider the location of the charging port for the upcoming R2 and R3 platforms, after prototype designs for the EVs were first unveiled and showed the port on the rear right instead. If Rivian wants to optimize for street parking as it appears to be doing, Morrill says that the company should move the port to the front right instead.
The company’s deployment of longer V4 Supercharging cables also follows the company’s debut of V4 charging cabinets earlier this month, effectively debuting faster charging speeds of up to 500kW. Companies like Ford, Rivian, General Motors (GM), and Nissan have already started gaining access to Tesla’s Supercharger network after adopting the company’s NACS last year, and Tesla will continue to widen access to the charging stations in the coming months and years.
What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send us tips at tips@teslarati.com.
Ford to replace Tesla NACS adapters, warning of damaged charging ports
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.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
