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Tesla FSD Beta 10.69.3.1 update reviews from Beta testers

Credit: teslaphotographer/Instagram

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Tesla Full Self-Driving (FSD) Beta 10.69.3.1 has been out for some time now, and Teslarati talked to a few beta testers about the update. 

Below are some notes and observations about v.10.69.3.1 from Tesla FSD Beta Testers. 

FSD Beta 10.69.3.1 and Lanes

Lane selection has been one of the issues that most FSD Beta testers bring up when they talk to Teslarati. Before 10.69.3.1, FSD Beta reportedly had trouble understanding when to switch lanes, which one to switch to, or when to remain in a lane. FSD Beta testers are still experiencing lane selection issues

“Not only has lane selection in anticipating a turn been a step back for me, lane selection whilst performing dual lane left-hand turns still suffer. The car doesn’t stay in its assigned lane but drifts. This does not happen on right turns,” said Les, a long-time FSD Beta tester.

“Lane selection still has issues. Most of the time it’s ok, but occasionally, it does strange things like changing into the right lane momentarily, then back to the left when there is an upcoming left-hand turn,” noted FSD Beta tester Sandy.

Turn Issues in FSD Beta 10.69.3.1 

Les and fellow FSD Beta tester Sandy mentioned other lane issues related to turns. Les noted that one of the biggest step back with FSD Beta 10.69.3.1 occurs when the car faces an upcoming turn. 

“On previous builds, the car would only occasionally move in the opposite lane direction of an upcoming turn. On this build, virtually every turn I had upcoming, when the car got within half a mile of said turn, it would signal and move into the lane of the opposite direction,” Les said.

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“Virtually every right turn I’ve had upcoming, the car, inexplicably, signals and changes into the left-hand lane. Same for left-hand turns, within half a mile out the car signaled and changed into the right-hand lane. Confounding to say the least, to the point of comedy,” he added. 

Sandy noticed that his car requires interventions or disconnects at stop signs sometimes. In the past, other FSD Beta testers have mentioned that their vehicle experiences jerky movements or their signal lights turn off and on during intersections, traffic lights, and stop signs. It’s as if the car is deciding whether the driver wants to turn or not. 

“Following and lane changes seem smoother and more natural,” said Sandy. “However, it still has issues that require intervention/disconnects. When it creeps at stop signs, it can make jerky movements with steering wheel and, imo, it creeps to slowly and takes too long before proceeding.”

Mixed Reviews for 10.69.3.1

As with all of Tesla’s FSD Beta updates, there have been a few good reviews and bad ones. Beta testers tend to focus on the issues, as it is their responsibility to report them so Tesla can improve FSD. However, testers also report significant improvements they see during their drives. 

In the case of 10.69.3.1, it seems like FSD Beta received mixed reviews. Some testers believed that the update significantly improved the advanced driver assist software while others thought it was a step back. 

“I have tested the 10.69.3.1 build on my Model Y, and it’s a giant leap forward from builds prior to 10.69,” observed Tony, a Model Y owner and a member of the FSD Beta program. 

Tony noted that the biggest changes were improvements to acceleration, smoother turns, and less necessary steering wheel input. Sandy also observed more improvements with Tesla FSD Beta 10.69.3.1 rather than issues. 

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On the other hand, Les believed that v.10.69.3.1 was a step back for FSD Beta. 

“These 10.69.3.1 step backs are the biggest in my FSD Beta testing experience to date. Previous builds have been much better for me. But again, I understand the process; updates are sometimes “2 steps forward and 1 step back.” I still enjoy testing. The product isn’t finished yet,” he said.

Tesla FSD Beta Wide Release

Tesla started the wide release of FSD Beta v.10.69.3.1 in late November. A day after its release, Tesla rolled out FSD Beta to cars with less than 100 Autopilot miles and Safety Scores lower than 80.

The EV maker rolled out FSD Beta V11 to a few testers already. FSD Beta V11 is Tesla’s single-stack update. However, update 10.69.3.1 seems to be rolling out to more testers. 

Tesla also made Full Self-Driving Beta available to anyone in North America who purchases it from their car screen. Now that Tesla has released FSD Beta to anyone in North America interested in trying it out, the company might want to streamline its performance. Based on Teslarati‘s interviews with FSD Beta Testers, the software performs differently based on location, driver, terrain, and other factors.

“Phantom braking on city streets (not highways) returned for me in one bizarre instance; it wasn’t the sudden hard kind of braking, rather this was a new braking behavior that was slow and gradual almost to a stop while I was going straight in the middle lane of a three-lane road. Not at a turn, wasn’t going through an intersection, and the road was clear,” described Les in one instance. 

“There were no cars around me so I let the car do its thing to see what it was doing; it literally started slowing from 40mph to 5mph before I disengaged and accelerated back up to speed. Very weird. I went back to that spot a couple days later and the car didn’t do it. It acted normal,” he explained. 

Tesla Full Self-Driving has not received regulatory approval yet. It still faces a lot of skepticism, especially in terms of safety. Delivering consistent, reliable performances in various driving situations might help it get regulatory approval. 

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Are you an FSD Beta tester? Have you tried out V11? If you have, I’d like to hear from you! Contact me at maria@teslarati.com or via Twitter @Writer_01001101.

Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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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

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.”

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

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.

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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