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Tesla dials in on FSD improvements with ‘millimeter-wave radar sensor’ filing

Tesla

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Tesla’s Full Self-Driving (FSD) suite is among the most complex and accurate systems on the road, but the company has always focused on constant improvement. Tesla has now filed an application with the Federal Communications Commission (FCC) for a “millimeter-wave radar sensor” for its vehicles.

Tesla’s focus on cameras and sensors has been evident since the beginning of its self-driving journey. With the company having several options to utilize in its quest for autonomy, Elon Musk has always maintained that Tesla would utilize cameras and radar, not LiDAR, for its self-driving projects. Musk once called LiDAR “a fool’s errand” and refused ever to consider the system for Tesla.

Instead, Tesla has used eight external body cameras, twelve ultrasonic sensors, and a front-facing radar to improve the accuracy of its self-driving cars. To make the cars even more predictable and safe, Tesla also uses a Neural Network to gather data and information that learns other drivers’ behavior. The 20 billion miles of real-world data Tesla has gathered over the years contributes to the Neural Net’s development and makes the entire Autopilot and FSD system more accurate as more miles are driven.

Tesla Autopilot’s 4D upgrade could lead to more FSD features

With all of these sensors, cameras, and radars, most would think that Tesla’s FSD suite, which is already showing vast improvements since the FSD Beta rollout in late 2020, just needs more miles and time to improve. But this isn’t the case, because Tesla wants to install a more refined radar sensor in its cars to improve accuracy even further.

Originally obtained and reported by Electrek, the FCC document doesn’t reveal full details on the device because of a confidentiality agreement. This will keep the finer points of the system until July 2021.

The document says that the new radar will operate in a 60 GHz band.

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“The equipment under test (EUT) was a Vehicle Millimeter-wave Radar Sensor operating in 60 GHz band (60-64 GHz).”

Ultimately, using a new, more refined, and more accurate sensor will help Tesla develop its self-driving suite even further. Last year, Musk revealed during the Q3 2020 Earnings Call that the company planned to move to a 4-dimensional training program, moving away from its “~2.5D” system that it currently uses. 4D is “essentially video” and would help improve the system’s accuracy.

Musk explains:

“So what we’ve been doing, thus far, has really just been like 2D — mostly 2D, and like I said, well correlated in time. So just hard to convey just how much better a fully 4D system would work — does work. It’s capable of things that if you just look — looking at things as individual pictures as opposed to video — basically, like you could go from like individual pictures to surround video, so it’s fundamental. So the car will seem to have just like a giant improvement.”

The 4D system would be capable of handling different traffic scenarios in a more sophisticated and accurate fashion because video is easier to gain information from than pictures. It will likely work in combination with Tesla’s Dojo supercomputer, which is set to be released late this year.

What do you think? Leave a comment down below. Got a tip? Email us at tips@teslarati.com or reach out to me at joey@teslarati.com

Tesla Millimeter Sensor Wave Radar by Joey Klender on Scribd

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Joey has been a journalist covering electric mobility at TESLARATI since August 2019. In his spare time, Joey is playing golf, watching MMA, or cheering on any of his favorite sports teams, including the Baltimore Ravens and Orioles, Miami Heat, Washington Capitals, and Penn State Nittany Lions. You can get in touch with joey at joey@teslarati.com. He is also on X @KlenderJoey. If you're looking for great Tesla accessories, check out shop.teslarati.com

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Elon Musk

SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff

Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.

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Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.

The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.

Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.

Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry

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None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.

The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.

Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.

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Investor's Corner

Tesla has one big financial question to answer for investors: Morgan Stanley

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Credit: Tesla

In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.

Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.

Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue

Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.

The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”

Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”

Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”

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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.

Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.

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Investor's Corner

SpaceX AI investment gamble will make it a big winner, firm says

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Credit: SpaceX

SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.

The firm also upgraded shares to a Buy from Hold and set a $160 price target.

SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.

Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.

There are plenty of ways the company can do this:

Leasing excess compute capacity through contracts

SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.

SpaceX is charging Anthropic massive money for its compute

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High utilization driven by industry-wide scarcity

The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.

Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.

Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.

High incremental margins on the rental business once capacity is online

GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.

Parallel monetization of its own AI software and applications

Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.

These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.

Efficient, large-scale deployment and vertical integration advantages

SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.

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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.

SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.

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