Connect with us

News

Tesla's Elon Musk shares MCU1 retrofit target timeframe, estimates $2k upgrade cost

Tesla Model touchscreen MCU maps [Credit: Tesla]

Published

on

Elon Musk has provided new details about Tesla’s Media Control Unit (MCU) retrofits for vehicles that are equipped with older infotainment systems. According to the CEO, MCU1 to MCU2 retrofits may start in a few months, though he does not personally recommend it, especially considering its estimated $2,000 cost. Musk has instead suggested that Tesla will release an update to older cars that can optimize the performance of their existing MCUs.

Musk’s recent statements were shared on Twitter while the CEO was interacting with Tesla owners, some of whom owned MCU1-equipped vehicles. The limitations of the older hardware have become more prominent over time, particularly as Tesla rolled out media-heavy features such as the Tesla Theater and the Tesla Arcade. Similar to older hardware in mobile devices, MCU1 vehicles have become slower compared to the company’s newer vehicles like the Raven Model S and X, as well as the Model 3.

Elon Musk has previously stated that MCU1 retrofits would be offered to owners whose vehicles are still equipped with older hardware. The CEO confirmed this following the initial rollout of MCU2 vehicles, and the idea was reiterated after the release of the company’s new Tesla Arcade titles. That being said, a number of Tesla owners have been informed by local service centers that an MCU1 to MCU2 retrofit was not possible.

Tesla Infotainment Upgrade

For the uninitiated, Tesla’s MCU1 is equipped with an Nvidia Tegra 3 processor, which is capable but a tad slower than its newer sibling. Meanwhile, the MCU2 runs on an Intel Atom E800 series chip and comes with a faster browser. The unit also renders videos with sound, giving it the capability of running new features such as the Tesla Theater, which includes video streaming apps such as Netflix and YouTube, as well as video games in Tesla Arcade. All Tesla Model 3s run on MCU 2, as well as Model S and Model X units purchased after March 2018. Customers who bought their Model S and X prior to March 2018 use the MCU1.

Many Tesla owners whose vehicles are equipped with MCU1 have been clamoring for an update to avail of features only enjoyed by those using the newer system. Tesla has not left those on MCU1 in the dark and has rolled out several updates to improve the performance of the older infotainment systems. That being said, the gap between the actual capabilities of Tesla’s MCU1 hardware and its MCU2 features such are growing, and it has pretty much reached the point where the infotainment systems of older vehicles are significantly slower than those in newer cars.

Advertisement

In a way, Elon Musk’s recent statements hint that Tesla’s current priority is the rollout of its Hardware 3, which is essential for its Full Self-Driving initiatives. Retrofits for HW2.5 vehicles have already begun, and HW2 vehicles are expected to follow soon. HW3 is Tesla’s custom-designed computer that replaces the old Nvidia computer used for HW 2.5. As noted by Tesla during its Autonomy Day presentation, Hardware 3 was specifically built to achieve true Full Self-Driving capabilities and can enhance the electric car’s processing capability by as much as 1,000 percent.

Nevertheless, it would be wise for Tesla to start rolling out its MCU1 retrofits for older vehicles, even if it’s later than expected. Considering that Tesla owners have shown a willingness to pay for the retrofit, and the CEO himself has confirmed that the upgrade is possible, it is in both Tesla and its customers’ best interest to make sure the vast majority of its fleet are able to enjoy the best that the company has to offer — even if it’s just for infotainment purposes.

A curious soul who keeps wondering how Elon Musk, Tesla, electric cars, and clean energy technologies will shape the future, or do we really need to escape to Mars.

Advertisement
Comments

News

Tesla urges New Jersey owners to oppose new bill that could block Robotaxi

Published

on

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.

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.

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.

Continue Reading

News

Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest

Published

on

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

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.

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.

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.

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.

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.

Continue Reading

Cybertruck

Tesla Cybertruck driver gets pickup seized for ‘legitimate concerns’ in UK

Published

on

A Tesla Cybertruck driver in the United Kingdom had their all-electric pickup seized by local police in the Greater Manchester area after the department cited “legitimate concerns.”

Last Thursday, police saw the pickup on the roads and decided to pull the driver over. Greater Manchester Police said:

“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a collision with the Cybertruck.”

The Cybertruck in question was, according to the BBC, registered and insured abroad and was confiscated. The driver, who is a UK resident, was reported.

The Greater Manchester Police Department then added:

“The Tesla Cybertruck is not road-legal in the UK and does not hold a certificate of conformity.”

The Cybertruck cannot be legally driven in the UK because it has no UK Type Approval for operation in the country. This is due to some safety concerns, which are related to its angular shape and design. The stainless steel exoskeleton has sharp edges and projections that violate UK/EU rules on pedestrian protection.

Tesla has considered creating what it referred to as an “international version” that would be approved for operation in Europe. However, there has been no real movement on that front by the company, as it has been focused on the Robotaxi rollout primarily.

Continue Reading