News
Tesla Firmware 6.1: Range, Routes and Parking Aid
Following the review of Firmware 6.1’s Trip Energy Prediction roll out I’ll be taking a deeper look at some of the other major features that came bundled with this version such as navigation routing and the reverse camera parking aid.
Range Display: Battery %
The Model S displays battery range based on a rated or ideal measurement as determined by the methodology in which the US EPA measures electric vehicle range.
This range always seems to be a hot topic of discussion amongst owners since, almost always, the actual mileage achieved is lower than what’s displayed on the car’s dash. This is especially true during the cold New England winter months when 265 miles of rated range turns out to be closer to 160 miles of actual range due to the effects of winter driving.
The grim reality is that range based on distance (mi/km) will vary depending on how you drive, the terrain you drive on and the environmental conditions during that time.
Tesla Firmware 6.1 solves this issue by giving drivers the ability to replace the display of range with the percentage of battery life remaining. Sure there’s the color-coded battery indicator but being able to see an actual value makes it much more relatable. On top of that the amount of battery remaining lines up nicely to the energy graph displayed through the Trip Energy Prediction feature.
Using this new way of measuring your range takes some getting used to but after a week of using it I kind of like it. It certainly beats using a rated range display that ends up being off by 40-50% during the winter months.
Route Overview
Tesla Firmware 6.1 also adds a new view for trip routing. A “Route Overview” option allows you to visualize your route using a north up view but with the ability to automatically zoom in as you approach your destination. There’s no need to manually pinch zoom anymore..
Enhanced Park Assist and Camera Guidelines
I’m lumping these two features together but also keeping in mind that Park Assist is limited to those with the parking assist package.
With this new update putting the Model S in reverse will display both front and rear parking sensors making parallel parking and backing into tight spots that much easier. You also have the ability to manually trigger Park Assist as long as the car is traveling below 5mph. This is a great addition since it provides visibility for all four corners of the Model S.
Tesla finally put the rumors of having an inadequate graphics engine, that supposedly prevented the ability to render parking lines, to rest with the addition of the reverse camera guidelines.
I never had rear camera guidelines on any of my previous cars so this feature wasn’t on my wish list and I never really understood why so many people wanted them. Now that I have them I can see how it would be hard to ever go back to a car without them.
Rear camera guidelines was the #1 requested feature for years and Tesla has delivered!
Summarizing the feature, the Model S will overlay lines on the screen to indicate the path of travel when backing up. These lines move with your steering wheel and apparently the lines will change colors to ensure maximum contrast and visibility depending on the background. Here’s a video of it in action.
Summary
Tesla outdid itself with this the release of Firmware 6.1. It introduces a solid list of big features and improvements around range, routing displays and parking assistance. Combine this with the new feature to dynamically calculate range based on terrain and driving behavior, this is one of the best updates to date.
Stay tuned as I review some of the other enhancements that came bundled with this version.
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
