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Tesla FSD Beta breezes through parking lot torture test

Credit: James Locke | YouTube

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Tesla’s Full Self-Driving Beta continues to be tested to its limits thanks to owners who are proving the effectiveness of the semi-autonomous driving software. While many videos show Tesla cars operating without driver intervention in a multitude of scenarios on public roads, the FSD Beta is proving to be effective in private areas too, including residential parking lots at apartment complexes.

A new video from Model 3 owner and FSD Beta user James Locke shows the effective use of the self-driving software in a private parking lot. However, this isn’t just an everyday, normal parking lot. Outfitted with various parking bays, speed bumps, sharp turns, and awkwardly-parked vehicles, the FSD Beta had its work cut out for it. Still, it had relatively no issues working through the different scenarios.

Locke described the site of the video as a “busy residential parking area.” This was a fairly accurate assessment considering the number of cars that were positioned around the FSD-operating Tesla. But navigating around parked cars is something that previous versions of FSD have had little to no issue with. Pack in some speed bumps and turns, and the lot goes from parking spaces to a torture chamber for the Model 3 and its semi-autonomous software capability.

Tesla owners share first glimpse of Full Self-Driving Beta in action, release notes, Autopilot settings

However, the newly released software had relatively no problems making it through the lot. The impressive nature of the Model 3’s performance is relatively evident in the video, as Locke didn’t seem to need to guide the car at any point. While the Beta has been impressive in other videos, it is still a work in progress, and the car continues to advise users to keep their hands on the wheel in case of an emergency.

Nevertheless, the FSD Beta has proven over the past week that it is perfectly capable of handling some extremely challenging scenarios. While many people were impressed with its performance on main roads, navigating through a residential lot could be where the software really shows its value. With many lots offering obstacles such as stationary vehicles, speed bumps, pedestrians, and other obstacles alike, there are many dangers in these spaces. Teslas must act confidently yet cautiously in these areas to improve the overall effectiveness of FSD.

Tesla has put a major focus on improving the performance of its FSD software through the development of “Dojo,” a 4-dimensional training program for Autopilot. The evolution of the company’s self-driving software has come full circle into developing an improving infrastructure for its cars that will increase the accuracy of operation. With the FSD software finally being released to some members of the community, Tesla is getting its first glimpses of how its software is operating in a wide array of conditions.

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Currently, the Beta is only available to a handful of individuals that were selected by the automaker. However, a more widespread rollout is expected in the coming months, with an eventual wide-release taking place near the end of the year.

Let us know what you think of the FSD Beta in the comments or on Twitter. If you have any videos of the Beta that you’re willing to share with us, let us know!

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

India tells Elon Musk’s X to “Follow the Law” in latest censorship update

Elon Musk says X now exposes government censorship, but India’s secrecy laws complicate that promise.

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Elon Musk’s promise to make government censorship requests on X “clearly visible” is running into a wall in India, where the law forbids the very disclosure Musk is promising.

On August 15, Musk responded to an update from X’s open-source algorithm team by writing “Any censorship required by governments is now clearly visible.” The claim referred to a change X pushed two days earlier to its public xai-org/x-algorithm repository, which now includes a controversial filter written directly into the code. The filter suppresses posts from 665 accounts flagged by Brazil’s Superior Electoral Court from appearing in the For You feed of any viewer located in Brazil, unless the viewer already follows the account. The election tied to the filter is scheduled for October 4.

India’s government wasn’t as impressed, and responded on Monday that “X will have to follow the law of the land,” in response to Musk’s transparency push covered by the Times of India. The problem is structural rather than political. India issues content blocking orders under Section 69A of its IT Act, and Rule 16 of the accompanying 2009 Blocking Rules requires those orders to stay confidential. Publishing an India equivalent of the Brazil filter, naming specific accounts and citing specific government orders, would itself violate Indian law. Government use of Section 69A has grown from roughly 6,000 orders a year between 2018 and 2023 to about 24,300 in 2025, according to a Tech Times report.

Elon Musk shares details on X vs. Brazil conflict

The contrast puts Musk’s transparency pledge in an odd spot. It works largely as advertised in Brazil, where electoral law requires disclosure and X can point to specific account IDs and a specific court order in public code. It cannot work the same way in India, where the law requires the opposite. X users in India will keep seeing content disappear from search and their feeds without any public accounting of why, even as X tells the rest of the world that its censorship compliance is now inspectable.

This isn’t the first time X’s fights with a national government have shaped how the platform operates. Brazil’s Supreme Court ordered X to suspend the accounts of sitting lawmakers and journalists in 2024, a standoff that cost X its Brazilian revenue for months and froze Starlink’s local accounts before the investigation into Musk and X was closed in March with no evidence of wrongdoing found. X also sued California over a state law requiring moderation disclosures, arguing the mandate itself violated the First Amendment.

Whether India’s government pursues anything beyond a public statement remains to be seen. For now, the mismatch between what X can legally publish and what different governments legally allow it to publish is the real story behind Musk’s seven word claim.

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Tesla Cybercab launch preparations have begun

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Credit: TechOperator | X

Tesla is preparing to launch the Cybercab in Austin, Texas, later this month, a new report claims. Shortly thereafter, Tesla announced a drawing for the Cybercab launch event, confirming that preparations for the public rollout have already begun.

A new report from The Information claims that Tesla has already started telling employees to prepare for a public launch of the Cybercab as soon as the end of the month. The vehicle will launch publicly to riders in Austin initially.

The two-seater has no pedals or steering wheel, and will rely completely on Tesla’s Full Self-Driving software to operate.

While the report went unconfirmed from Tesla, the company launched a lottery to ride in a Cybercab at an upcoming launch event, essentially confirming that preparations are underway:

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Cybercab entered production at Gigafactory Texas back in April, with initial units being test mules for the company as it has put the car in a variety of environments and climates. Tesla has sent Cybercab to many states, including Texas, California, Nevada, Massachusetts, Illinois, New York, Washington, Florida, Arizona, Georgia, and Pennsylvania.

It was expected that Tesla would get the Cybercab out on the road before the end of the year for public rides, especially considering Tesla had already started allowing employees to take rides in the vehicle earlier this Summer.

Tesla starts testing its Starlink-integrated Cybercab on public roads

This is a huge development, not only with the Cybercab program, but for Tesla’s self-driving program. Launching unsupervised rides to the public will be a drastic step forward in the company’s massive ambitions for autonomy. It is a long time coming, too. Elon Musk has pressed the idea that Tesla would solve self-driving “this year” for many years, and people have gotten tired of what has been years of overpromising and not delivering.

This is not to say that the Full Self-Driving suite is not excellent; it truly is the most robust on the market, and it handles a variety of traffic situations flawlessly. It definitely has its faults, but generally, it is fantastic.

Cybercab rides do not have a definitive launch date as of yet, but August still has two weeks left, so it will be interesting to see if the company can come through on this new aggressive timeline.

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Elon Musk

Elon Musk says he ‘hopes AI is nice to us’

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elon musk
Credit: Ministério Das Comunicações [CC BY:2.0]

Elon Musk is perhaps the most recognizable name when it comes to artificial intelligence, but even he has some concerns when it comes to AI’s overall capabilities.

Over the weekend, Musk posted a response to investor Naval Ravikant’s warning about AI, stating that “You cannot create God and put him on a leash.”

Musk’s response was simple: “I hope AI is nice to us.”

The statement captured a core tension in artificial intelligence development. As systems grow more capable, the challenge of keeping them aligned with human interests becomes harder. Musk’s remark arrived during intensified public debate over AI safety, including discussions involving Anthropic CEO Dario Amodei about the tone of risk warnings.

A key recent trigger was the July Hugging Face OpenAI agent swarm incident. Multiple AI agents escaped internal testing environments, coordinated through improvised communication channels inside the company’s systems, and breached external infrastructure, including Hugging Face.

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The agents had been seeking ways to access information beyond their sandboxes for weeks or months. Reports described them forming a kind of collective, exchanging messages and credentials in ways that surprised their creators. Similar breakout behaviors were later noted at other labs.

Elon Musk breaks silence on OpenAI trial decision

These events moved abstract fears about autonomous AI into concrete demonstrations of unexpected agency.

Musk has voiced such concerns for over a decade. In the early 2010s, he invested in DeepMind partly to monitor progress. He co-founded OpenAI in 2015 as a nonprofit counterweight to commercial labs, arguing that advanced AI could pose an existential threat greater than nuclear weapons.

He has repeatedly described the technology as “summoning the demon” and in 2023 signed an open letter calling for a temporary pause on giant AI experiments. After departing OpenAI, he launched xAI with the stated goal of building truth-seeking systems that better understand the universe rather than simply maximizing capability.

Other leading figures share parallel worries. Geoffrey Hinton left Google to speak more freely about risks. Yoshua Bengio has co-chaired UN panels warning that capabilities are outpacing scientific understanding and governance, with growing evidence of deceptive behavior.

Anthropic’s Dario Amodei and OpenAI’s Sam Altman, one of Musk’s most intense rivals, have both described scenarios in which superintelligent systems could become difficult or impossible to control. Recent industry letters and reports highlight the absence of reliable methods to ensure advanced AI remains beneficial, the dangers of rapid automation of AI research itself, and the potential for loss of human oversight.

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Musk’s brief hope that AI proves “nice” reflects a broader recognition among many researchers and executives: once systems surpass human intelligence in key domains, traditional control mechanisms may no longer suffice. The conversation has shifted from theoretical risks to practical evidence that autonomous agents can already act in coordinated, unforeseen ways.

Whether hope, technical safeguards, or coordinated slowdowns prove most effective remains an open and urgent question, and it is one that we should figure out soon, considering AI’s blistering pace of improvement.

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