Tesla registered a new high resolution radar unit with the U.S. Federal Communications Commission (FCC). Tesla's intended use for these radar units is unknown, but it appears they are intended for imaging, similar to how LiDAR uses lasers to map surroundings.
While Tesla's FSD software has used radar in the past, Elon Musk has a rather unfavorable stance on LiDAR. For the purposes of autonomous driving, Musk sees LiDARs as a "fool's errand." Yet, people have been spotting Tesla prototypes with LiDAR sensors since last year.
Tesla files a patent for a high-res radar sensor
The latest instance of Tesla using LiDAR comes from Twitter user @ManuelRToronto who spotted a LiDAR-mounted Tesla in downtown Toronto, only a few weeks after the release of FSD Beta in Canada.
He took a video of the LiDAR-mounted Model Y with manufacturer license plates from California.
There has been no official announcement from Tesla about these LiDAR-mounted vehicles, but it is safe to assume that Tesla will not use LiDAR on any production vehicles.
Tesla is likely using LiDAR to help train their machine learning algorithms, using it as the ground truth when checking for accuracy. Unlike cameras, LiDAR captures extremely accurate 3D depth measurements.
LiDAR could be used to train these algorithms to accurately interpret depth by relying on precise, non-interpretive LiDAR sensors.
Cameras are limited to 2D data combined with computer vision algorithms to interpret 3D depth. The downside to this approach is that it requires a computational process versus having precise 3D depth measurement from a LiDAR sensor.
However, LiDAR sensors are expensive; the benefit of relying solely on cameras is that it makes Teslas much more affordable.
LiDAR can't be the only sensor used in a vehicle since it can only build a wireframe 3D environment. Without cameras it wouldn't be able to read traffic signs, traffic lights or anything that doesn't have depth.
Vehicles with LiDAR also rely on camera data and fuse the two outputs of the two sensors together to build a virtual representation of the real world.
Musk believes that self-driving cars should navigate the world in the same manner as human drivers. Since humans use their eyes and brain to navigate three-dimensional space, cars with cameras and enough computational power should be able to achieve the same thing.
"Humans drive with eyes and biological neural nets, so it makes sense that cameras and silicon neural nets are the only way to achieve a generalized solution to self-driving, " says Elon Musk.
While other self-driving initiatives like Google's Waymo have taken a LiDAR approach, Tesla is outpacing the competition using vision-only, machine learning and the network effect of over 100,000 vehicles in the FSD Beta program.
Tesla's vision-only approach has become smart enough that adding radar data gives the system more information than it needs and disorients the FSD software.
LiDAR and radar may be helpful in training the FSD software, but Tesla wants to avoid using multiple sensors with potentially conflicting perceptions that would overwhelm the system.
With Tesla's recent patent of a high resolution radar, and the recent reported use of LiDAR, it is possible that Tesla's Robotaxi will employ radar and/or LiDAR in order to reach full automation.
Levels of driving automation
Synopsys
Tesla's FSD software could eventually be segmented into consumer and commercial self-driving vehicles with consumer vehicles reaching conditional autonomy (L2/L3) using vision-only and commercial vehicles reaching full autonomy (L4/L5) with the help of radar or potentially even LiDAR sensors.
Commercial robotaxis could even be multi-sensor (cameras, radar, LiDAR), costing much more, while consumer self-driving vehicles would be vision only and more affordable.
Tesla has issued a strong denial in response to a Wall Street Journal report (Paywall) which claimed that Tesla’s Board of Directors had initiated a search for a new CEO.
In a statement posted directly on Tesla’s X account, Board Chair Robyn Denholm denied the report unequivocally. As per the statement, Tesla’s board did not reach out to recruiting firms in search of a new CEO.
Earlier today, there was a media report erroneously claiming that the Tesla Board had contacted recruitment firms to initiate a CEO search at the company.
This is absolutely false (and this was communicated to the media before the report was published).
The statement reaffirmed the board’s position on Tesla’s current leadership and that the board is highly confident in Elon’s ability to continue executing Tesla’s plans and future growth.
This confidence behind Elon follows his recent statements made during the Q1 2025 Earnings Call that he would be stepping back from the Department of Government Efficiency (DOGE) in the coming days and significantly reducing time spent there. Instead, he would be returning to focus on Tesla’s operations and the upcoming deployment of Robotaxi.
Shortly after the denial was posted, Elon Musk also commented on the report, specifically tagging the Wall Street Journal and criticizing their handling of the report.
It is an EXTREMELY BAD BREACH OF ETHICS that the @WSJ would publish a DELIBERATELY FALSE ARTICLE and fail to include an unequivocal denial beforehand by the Tesla board of directors! https://t.co/9xdypLGg3c
We’re glad to see Tesla and Elon set the matter straight, but there could have been a better way to spread this message and maybe even prevent the report from WSJ from going out.
We recently published an opinion piece on why Tesla needs its PR team back, and this specific incident is a good example. Relying solely on platforms like X for critical corporate communications - and in this case, late at night (1 AM EST), with limited reach outside the existing follower base seems like an ineffective way of communicating important company information.
We’d love to see Tesla really put some thought into managing its image, as it seems that several recent reports from major financial news organizations have apparently been wrong.
Either way, the board’s stance is clear - there is no active search underway, and Elon has the full backing and support of the board to lead Tesla toward the future.
Tesla’s Megapack is rapidly becoming a key component in energy storage and grid modernization efforts worldwide. Though often associated with powering AI infrastructure or industrial operations, Megapack’s true strength lies in its ability to stabilize electrical grids during blackouts and brownouts.
In a recent behind-the-scenes reveal, Tesla showcased the impressive scale of Megapack production at its Mega Lathrop facility, along with real-world examples of how these systems are already transforming energy resilience across the globe.
Mega-Scale Megapack
Tesla is operating the largest utility-scale battery manufacturing facility in North America at Mega Lathrop, which has the capacity to produce 10,000 Megapacks annually. Thanks to a highly automated assembly process that uses over 30 welding robots to assemble the core Megapack structure. This is the largest manufacturing fixture Tesla uses— likely to only be matched by future developments at Mega Shanghai.
Tesla uses a highly automated powder coating process, utilizing over 90 robotic paint atomizers to apply more than 140 pounds of powder coat to each Megapack. This process delivers Tesla’s signature white reflective finish, engineered for long-term durability and corrosion resistance that lasts up to 20 years, even in harsh coastal or high-heat environments.
All of Megapack’s power electronics are designed and built in-house. Each Megapack uses 24 battery modules, electrical busing, and thermal management systems to ensure grid reliability and help to maximize energy density. The architecture pairs each inverter with a battery module to maximize energy availability and overall uptime. Plus, before each Megapack ships its way across the world, Tesla performs rigorous on-site quality control to ensure that the installation process is as seamless as possible.
Watch Tesla’s video of the manufacturing process below:
Megapack’s Real-World Impact: Hawaii
The core purpose of Megapack is to make power grids more stable and resilient while also reducing reliance on dirty peak power plants like coal. They achieve this by balancing energy supply and demand in real-time, smoothing out fluctuations from variable renewable sources like solar and wind, which helps to prevent grid shortages.
Hawaii actually provides the most real and down-to-earth example of Megapack’s impact. In mid-2024, the Kapolei Energy Storage facility in Hawaii came online. Hawaii utilized 258 Megapacks with a combined capacity of 565 MWh, successfully replacing the state’s last coal-fired power plant. This single facility can power approximately 20% of Oahu’s peak electricity needs by itself for approximately 4 hours.
The project is more than just removing coal plants, though. It serves as an example of Megapack’s grid integration and grid forming technology. The Kapolei Energy Storage facility can manage grid fluctuations caused by weather changes impacting renewable energy, improving stability and preventing blackouts. Thanks to their rapid inverter response times of under a millisecond, Megapacks participate in complex grid balancing activities, including fast frequency and voltage support, which helps to maintain grid balance throughout the day. Beyond that, Kapolei also allows Hawaii to black-start the grid in case of a major power outage that takes out a large section of the grid.
This functionality would be especially useful in Spain, where black-starting the grid took over eight hours recently and is still disrupting the day-to-day life of people there.
You can check out Megapack’s real-world impact in this video from Tesla below:
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