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Tesla’s in-house Full Self-Driving chip puts TSLA 4 years ahead of competition: analyst
Tesla’s decision to develop its Full Self-Driving (FSD) computer chip in-house has put it four years ahead of the competition, according to ARK Invest analyst James Wang.
Wang laid out the case for the all-electric car maker’s custom automotive-grade computer against the next-best options in the market, all Nvidia products, in an article on ARK Invest’s website. His stated goal in the piece was to clarify Tesla’s position and achievement with full self-driving in simple terms as well as explain why an off-the-shelf chip would not have accomplished the same feat.
Admittedly, Tesla’s Autonomy Day livestream debuting the arrival of its Full Self-Driving computer was chock full of very technical details that many outside the computer science world indicated were difficult to follow. Thus, Wang’s FSD simplification is helpful for gaining insight into Tesla’s autonomous driving progress in terms of the bigger industry picture.
In summary, by focusing only on what its particular needs were for its particular software demands, Tesla was was able to improve its chip’s performance efficiency to a level that has allowed it to “leapfrog” over competitors. Wang predicts that by 2021, Tesla will be ready to release its next generation FSD computer while its closest competitor in terms of optimal peak utilization is just coming to market.
Nvidia is a prominent and highly successful leader in computer chip design, and Tesla already uses its products for Hardware 2.5, the computer currently running the electric car maker’s Autopilot features. That said, the industry giant has three self-driving-focused chips in its lineup: Xavier (in production), Pegasus (readying for production) and Orin (still pending an official announcement).
Pegasus is a Level 5 self-driving computer, as is Tesla’s FSD; however, it has twice as many chips as FSD, consumes seven times more power than FSD, and is too big and expensive for the Model 3. Since Nvidia designs chips for a wide range of hardware manufacturers, much like the Windows and Android operating systems are designed to be flexible enough for different computer and smartphone hardware suites, their functionality cannot be overly streamlined for one system over another. In contrast, Tesla (like Apple hardware/software) can focus all of its autonomy efforts on its specific hardware and software needs, thus achieving a greater output than Nvidia’s product.
In a follow up to Tesla’s Autonomy Day presentation wherein FSD was compared to Nvidia’s Xavier computer, a chip designed for semi-autonomous driving only, the chip manufacturer published a company blog piece drawing attention to Pegasus’ capabilities as a better measure for analysis. As pointed out in Wang’s analysis, the FSD and Pegasus still do not achieve the same metrics, leaving Tesla well positioned amongst its self-driving computer peers. Despite the issue, though, Nvidia’s conclusion was a positive response to the car maker’s achievement: Tesla has raised the bar on self-driving and other car manufacturers need to get on board before falling too far behind.
During the Autonomy Day presentation, Tesla CEO Elon Musk crowned FSD as “objectively best in the world”, and James Wang’s analysis is yet another outline of why that is arguably the case. Tesla’s Full Self-Driving Computer (formerly known as Hardware 3) is currently being installed in all new production vehicles, and owners who purchased Full Self-Driving for a car produced in 2016 or later will receive a free upgrade to the FSD computer in the near future. Musk has further predicted that Tesla’s full self-driving software will be complete by the end of this year and fully operational by the second quarter of next year.
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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.
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.
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.
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:
Ride in Robotaxi through 8/23 for a shot to attend our Cybercab launch event
More rides = better odds pic.twitter.com/NxA4H9sWF2
— Tesla Robotaxi (@robotaxi) August 18, 2026
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.
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.”
I hope AI is nice to us https://t.co/NefIRrrg96
— Elon Musk (@elonmusk) August 15, 2026
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.
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.
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.
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.
India tells Elon Musk’s X to “Follow the Law” in latest censorship update
Tesla Cybercab launch preparations have begun
