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Tesla release notes detail remedies to address NHTSA Autopilot “recall”

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By the time news of Tesla’s Autopilot “recall” was published earlier this week, the company was already in the process of rolling out a free over-the-air software update for the advanced driver-assist system’s alleged safety issues. As per the National Highway Traffic Safety Administration’s (NHTSA) Safety Recall Report, software version 2023.44.30 would include Autopilot’s required remedies. 

The Autopilot “recall” covers over 2 million vehicles, including legacy vehicles like model year 2012 Model S sedans. As noted by the NHTSA, Tesla’s default safety checks for the affected vehicles’ Autosteer function may prove inadequate, which may result in drivers abusing the system and potentially increasing their chances of meeting an accident on the road. 

As could be seen in the release notes of software version 2023.44.30, which were posted by Tesla software tracking service Not a Tesla App, the changes to Autopilot’s driver checks are quite notable. Following are the pertinent sections of the 2023.44.30 release notes related to Tesla’s prolific 2-million-vehicle “recall.” 

2023.44.30 Release Notes

Over-the-Air (OTA) Recall

In accordance with a recent recall (campaign #23V-838 for US and #2023-657 for Canada), Tesla is making the following improvements to Autosteer:

– Improved visibility of driver monitoring warning alerts on the touchscreen by increasing the text size and moving the notifications to a more prominent position (Model 3 and Model Y only).

– Added option to activate Autopilot features with a single stalk depression, instead of two, to help simplify activation and disengagement.

– Increased the strictness of driver attentiveness requirements when using Autosteer and approaching traffic lights and stops signs off-highway.

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– Introduced a Suspension Policy that will restrict Autosteer usage for one week if improper usage is detected. Improper usage is when you, or another driver of your vehicle, receive five “Forced Autopilot Disengagements.”

You are the driver. As the driver, you must be vigilant to the road, keep your hands on the wheel, and be ready to intervene to maintain safety.

Autopilot Suspension

For maximum safety and accountability, use of Autopilot features will be suspended if improper usage is detected. Improper usage is when you, or another driver of your vehicle, receive five ‘Forced Autopilot Disengagements’. A disengagement is when the Autopilot system disengages for the remainder of a trip after the driver receives several audio and visual warnings for inattentiveness. Driver-initiated disengagements do not count as improper usage and are expected from the driver. Keep your hands on the wheel and remain attentive at all times. Use of any hand-held devices while using Autopilot is not allowed.

Autopilot features can only be removed per this suspension method and they will be unavailable for approximately one week.

FSD Beta 11.4.9

-Added option to activate Autopilot with a single stalk depression, instead of two, to help simplify activation and disengagement.

-Introduced a new efficient video module to the vehicle detection, semantics, velocity, and attributes networks that allowed for increased performance at lower latency.This was achieved by creating a multi-layered, hierarchical video module that caches intermediate computations to dramatically reduce the amount of compute that happens at any particular time.

-Improved distant crossing object detections by an additional 6%, and improved the precision of vehicle detection by refreshing old datasets with better autolabeling and introducing the new video module.

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-Improved the precision of cut-in vehicle detection by 15%, with additional data and the changes to the video architecture that improve performance and latency.

-Reduced vehicle velocity error by 3%, and reduced vehicle acceleration error by 10%, by improving autolabeled datasets, introducing the new video module, and aligning model training and inference more closely.

-Reduced the latency of the vehicle semantics network by 15% with the new video module architecture, at no cost to performance.

-Reduced the error of pedestrian and bicycle rotation by over 8% by leveraging object kinematics more extensively when jointly optimizing pedestrian and bicycle tracks in autolabeled datasets.

-Improved geometric accuracy of Vision Park Assist predictions by 16%, by leveraging 10x more HW4 data, tripling resolution, and increasing overall stability of measurements.

-Improved path blockage lane change accuracy by 10% due to updates to static object detection networks.

Cabin Camera

The cabin camera above your rearview mirror can now determine driver inattentiveness and provide you with audible alerts, to remind you to keep your eyes on the road when Autopilot is engaged. Camera images do not leave the vehicle itself, which means the system cannot save or transmit information unless you enable data sharing. To change your data settings, tap Controls > Software > Data Sharing on your car’s touchscreen.

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The NHTSA document also noted that Tesla Model S, Model 3, Model X, and Model Y vehicles that were produced from midday December 7, 2023 are not covered by the recall. This was because the vehicles were already loaded with 2023.44.30 out of the factory.

Don’t hesitate to contact us with news tips. Just send a message to simon@teslarati.com to give us a heads up.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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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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