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Tesla Autopilot and artificial intelligence: The unfair advantage
Serial tech entrepreneur and Tesla CEO Elon Musk has had a longstanding fear of artificial intelligence, but his company’s investments in artificial intelligence have been noted as an attempt to keep track of developments in the field of AI. In an interview for Vanity Fair in April 2017, he outright expressed his concerns with AI and claimed that one of the reasons for the development of SpaceX was that it could be an interplanetary escape route for humanity if artificial intelligence goes rogue. However, even Musk realizes the importance of AI in real-world applications, specifically for self-driving cars. At the end of June, Musk hired Andrej Karpathy as the new Director of Artificial Intelligence at Tesla, and MIT Technology Review claims it is the start of a plan to rethink automated driving at Tesla.
Karpathy comes from OpenAI, a non-profit company founded by Musk that focuses on “discovering and enacting the path to safe artificial general intelligence.” Afterwards, he moved on to intern at DeepMind, a place that spotlighted reinforcement learning with AI. Karpathy’s previous research focuses are on image understanding and recognition, which directly translates into applying proven image recognitions algorithms in Tesla’s Autopilot.
Recently, the popular question of morality was brought up in context to AI learning in Autopilot cars. It’s very interesting to consider how to teach technology to respond to an innately human moral problem. The Moral Machine, hosted by Massachusetts Institute of Technology, is a platform built to “gather human perspectives on moral decisions made by machine intelligence, such as self-driving cars.” It questions how the machine would act in human decisions such as whether to crash the driver or keep driving into a pedestrian that is crossing the street where there are no traffic regulators. How exactly do you teach a logical machine the mechanisms of ethical decision-making?
Although Musk and Tesla are the leaders in the self-driving field, a number of other companies are also entering into the competition sphere. Google, Uber, and Intel’s Mobileye have all been considering the application of reinforcement learning in the context of self-driving cars. Uber, Waymo, GM (Cruise Automation), Mobileye (camera supplier), Mercedes and Velodyne (LiDAR Supplier) could be potential competitors in the realm of self-driving vehicles. However, most of the technology does not encompass full self-driving, which is Musk’s aim. While other companies are investing heavily in autonomous fleets, Tesla far outpaces them in terms of data collection and release of finished product.
What are the differentiators for Tesla in the growing field of AI directed driverless cars?
Historically, Musk has focused on “narrow AI” which can enable the car to make decisions without driver interference. The vehicles would increasingly rely on radar as well as ultrasonic technology for sensing and data-gathering to form the basis for Tesla’s Autopilot algorithms. A technology that isn’t derived from LiDAR, the combination of radar and camera system said to outperform LiDAR especially in adverse weather conditions such as fog.
With the introduction of Autopilot 2.0 and Tesla’s “Vision” system, and billions of miles real-world driving data collected by Model S and Model X drivers, Tesla continues to create a detailed 3D map of the world that has increasingly finer resolution as more vehicles are purchased, delivered and placed onto roadways. The addition of GPS allows Tesla to put together a visual driving map for AI vehicles to follow, paving the path for newer and more advanced vehicles.
The addition of Karpathy will be a notable asset for Tesla’s Autopilot team. In specific, the team will be able to apply Karpathy’s deep knowledge of reinforcement learning systems. Reinforcement learning for AI is similar to teaching animals via repetition of a behavior until a positive outcome is yielded. This type of machine learning will allow Tesla Autopilot to navigate complex and challenging scenarios. For example, AI will allow cars to determine in real-time how to navigate a four-way stop, a busy intersection or other difficult situations present on city streets. By making cars smarter with the way they navigate drivers, Tesla will put itself ahead of the curve with a fully-thinking, fully self-driving car.
Tesla is expected to demonstrate a fully autonomous cross-country drive from California to New York by the end of this year as a showcase for its upcoming Full Self-driving Capability. If you’re buying a Tesla Model 3, or an existing Model S or Model X owner, just know that you’re contributing to a self-driving future, mile by mile.
Tesla has added a notable improvement to its Dashcam feature after complaints from owners have pushed the company to make a drastic change.
Perhaps one of the biggest frustrations that Tesla owners have communicated regarding the Dashcam feature is the lack of ability to retain any more than 60 minutes of driving footage before it is overwritten.
It does not matter what size USB jump drive is plugged into the vehicle. 60 minutes is all it will hold until new footage takes over the old. This can cause some issues, especially if you were saving an impressive clip of Full Self-Driving or an incident on the road, which could be lost if new footage was recorded.
This has now been changed, as Tesla has shown in the Release Notes for an upcoming Software Update in China. It will likely expand to the U.S. market in the coming weeks, and was first noticed by NotaTeslaApp.
The release notes state:
“Dashcam Dynamic Recording Duration – The dashcam dynamically adjusts the recording duration based on the available storage capacity of the connected USB drive. For example, with a 128 GB USB drive, the maximum recording duration is approximately 3 hours; with a 1 TB or larger USB drive, it can reach up to 24 hours. This ensures that as much video as possible is retained for review before it gets overwritten.”
Tesla Adds Dynamic Recording
Instead of having a 60-minute cap, the new system will now go off the memory in the USB drive. This means with:
- 128 GB Jump Drive – Up to Three Hours of Rolling Footage
- 1TB Jump Drive – Up to 24 Hours of Rolling Footage
This is dependent on the amount of storage available on the jump drive, meaning that if there are other things saved on it, it will take away from the amount of footage that can be retained.
While the feature is just now making its way to employees in China, it will likely be at least several weeks before it makes its way to the U.S., but owners should definitely expect it in the coming months.
It will be a welcome feature, especially as there will now be more customization to the number of clips and their duration that can be stored.
With the news of a merger between SpaceX and xAI being confirmed earlier this week by CEO Elon Musk directly, the first moves of an umbrella company that combines all of the serial tech entrepreneur’s companies have been established.
The move aims to combine SpaceX’s prowess in launches with xAI’s expanding vision in artificial intelligence, as Musk has detailed the need for space-based data centers that will require massive amounts of energy to operate.
It has always been in the plans to bring Musk’s companies together under one umbrella.
“My companies are, surprisingly in some ways, trending toward convergence,” Musk said in November. With SpaceX and xAI moving together, many are questioning when Tesla will be next. Analysts believe it is a no-brainer.
SpaceX officially acquires xAI, merging rockets with AI expertise
Dan Ives of Wedbush wrote in a note earlier this week that there is a “growing chance” Tesla could be merged in some form with the new conglomeration over the next 12 to 18 months.
“In our view, there is a growing chance that Tesla will eventually be merged in some form into SpaceX/xAI over time. The viewis this growing AI ecosystem will focus on Space and Earth together… and Musk will look to combine forces,” Ives said.
Let’s take a look at the potential.
The Case for Synergies – Building the Ultimate AI Ecosystem
A triple merger would create a unified “Musk Trinity,” blending Tesla’s physical AI with Robotaxi, Optimus, and Full Self-Driving, SpaceX’s orbital infrastructure through Starlink and potential space-based computer, and xAI’s advanced models, including Grok.
This could accelerate real-world AI applications, more specifically, ones like using satellite networks for global autonomy, or even powering massive training through solar-optimized orbital data centers.
The FCC welcomes and now seeks comment on the SpaceX application for Orbital Data Centers.
The proposed system would serve as a first step towards becoming a Kardashev II-level civilization and serve other purposes, according to the applicant. pic.twitter.com/TDnUPuz9w7
— Brendan Carr (@BrendanCarrFCC) February 4, 2026
This would position the entity, which could ultimately be labeled “X,” as a leader in multiplanetary AI-native tech.
It would impact every level of Musk’s AI-based vision for the future, from passenger use to complex AI training models.
Financial and Structural Incentives — and Risks
xAI’s high cash burn rate is now backed by SpaceX’s massive valuation boost, and Tesla joining the merger would help the company gain access to private funding channels, avoiding dilution in a public-heavy structure.
The deal makes sense from a capital standpoint, as it is an advantage for each company in its own specific way, addressing specific needs.
Because xAI is spending money at an accelerating rate due to its massive compute needs, SpaceX provides a bit of a “lifeline” by redirecting its growing cash flows toward AI ambitions without the need for constant external fundraising.
Additionally, Tesla’s recent $2 billion investment in xAI also ties in, as its own heavy CapEx for Dojo supercomputers, Robotaxis, and Optimus could potentially be streamlined.
Musk’s stake in Tesla and SpaceX, after the xAI merger, is also uneven. His ownership in Tesla equates to about 13 percent, only increasing as he achieves each tranche of his most recent compensation package. Meanwhile, he owns about 43 percent of the private SpaceX.
A triple merger between the three companies could boost his ownership in the combined entity to around 26 percent. This would give Musk what he wants: stronger voting power and alignment across his ventures.
It could also be a potential facilitator in private-to-public transitions, as a reverse merger structure to take SpaceX public indirectly via Tesla could be used. This avoids any IPO scrutiny while accessing the public markets’ liquidity.
Timeline and Triggers for a Public Announcement
As previously mentioned, Ives believes a 12-18 month timeline is realistic, fueled by Musk’s repeated hints at convergence between his three companies. Additionally, the recent xAI investment by Tesla only points toward the increased potential for a conglomeration.
Of course, there is speculation that the merger could happen in the shorter term, before June 30 of this year, which is a legitimate possibility. While this possibility exists but remains at low probability, especially when driven by rapid AI/space momentum, longer horizons, like 2027 or later, allow for key milestones like Tesla’s Robotaxi rollout and Cybercab ramp-up, Optimus scaling, or regulatory clarity under a favorable administration.
Credit: Grok Imagine
The sequencing matters: SpaceX-xAI merger as “step one” toward a unified stack, with a potential SpaceX IPO setting a valuation benchmark before any Tesla tie-up.
Full triple convergence could follow if synergies prove out.
Prediction markets are also a reasonable thing to look at, just to get an idea of where people are putting their money. Polymarket, for example, sits at between a 12 and 24 percent chance that a Tesla-SpaceX merger is officially announced before June 30, 2026.
Looking Ahead
The SpaceX-xAI merger is not your typical corporate shuffle. Instead, it’s the clearest signal yet that Musk is architecting a unified “Muskonomy” where AI, space infrastructure, and real-world robotics converge to solve humanity’s biggest challenges.
Yet the path is fraught with execution risks that could turn this visionary upside into a major value trap. Valuation mismatches remain at the forefront of this skepticism: Tesla’s public multiples are unlike any company ever, with many believing they are “stretched.” On the other hand, SpaceX-xAI’s private “marked-to-muth” pricing hinges on unproven synergies and lofty projects, especially orbital data centers and all of the things Musk and Co. will have to figure out along the way.
Ultimately, the entire thing relies on a high-conviction bet on Musk’s ability to execute at scale. The bullish case is transformative: a vertically integrated AI-space-robotics giant accelerates humanity toward abundance and multi-planetary civilization faster than any siloed company could.
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IM Motors co-CEO apologizes to Tesla China over FUD comments
Liu said later investigations showed the accident was not caused by a brake failure on the Tesla’s part, contrary to his initial comments.
Liu Tao, co-CEO of IM Motors, has publicly apologized to Tesla China for comments he made in 2022 suggesting a Tesla vehicle was defective following a fatal traffic accident in Chaozhou, China.
Liu said later investigations showed the accident was not caused by a brake failure on the Tesla’s part, contrary to his initial comments.
IM Motors co-CEO issues apology
Liu Tao posted a statement addressing remarks he made following a serious traffic accident in Chaozhou, Guangdong province, in November 2022, as noted in a Sina News report. Liu stated that based on limited public information at the time, he published a Weibo post suggesting a safety issue with the Tesla involved in the crash. The executive clarified that his initial comments were incorrect.
“On November 17, 2022, based on limited publicly available information, I posted a Weibo post regarding a major traffic accident that occurred in Chaozhou, suggesting that the Tesla product involved in the accident posed a safety hazard. Four hours later, I deleted the post. In May 2023, according to the traffic police’s accident liability determination and relevant forensic opinions, the Chaozhou accident was not caused by Tesla brake failure.
“The aforementioned findings and opinions regarding the investigation conclusions of the Chaozhou accident corrected the erroneous statements I made in my previous Weibo post, and I hereby clarify and correct them. I apologize for the negative impact my inappropriate remarks made before the facts were ascertained, which caused Tesla,” Liu said.
Investigation and court findings
The Chaozhou accident occurred in Raoping County in November 2022 and resulted in two deaths and three injuries. Video footage circulated online at the time showed a Tesla vehicle accelerating at high speed and colliding with multiple motorcycles and bicycles. Reports indicated the vehicle reached a speed of 198 kilometers per hour.
The incident drew widespread attention as the parties involved provided conflicting accounts and investigation details were released gradually. Media reports in early 2023 said investigation results had been completed, though the vehicle owner requested a re-investigation, delaying the issuance of a final liability determination.
The case resurfaced later in 2023 following a defamation lawsuit filed by Tesla China against a media outlet. According to a court judgment cited by Shanghai Securities News, forensic analysis determined that the fatal accident was unrelated to any malfunction on the Tesla’s braking or steering systems. The court also ruled that the media outlet must publish an apology, address the negative impact on Tesla China’s reputation, and pay a penalty of 30,000 yuan.
Tesla adds notable improvement to Dashcam feature
Will Tesla join the fold? Predicting a triple merger with SpaceX and xAI
