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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.
News
Tesla Australia Exec: No regulatory barriers for FSD release
Tesla’s FSD demonstrations have been quite impressive as of late.

Recent comments from Tesla’s Country Director for Australia and New Zealand Thom Drew have provided an exciting update for Full Self Driving’s upcoming release in Australia. As per the executive, there is currently no regulatory barrier to FSD being rolled out to Australian roads.
Drew’s comments came on the heels of a video demonstration featuring FSD Supervised navigating Melbourne’s central business district.
Tesla FSD’s Australia Demo
Shared by the Tesla AI team’s official account on social media platform X, FSD Supervised’s demonstration in Melbourne’s central business district sparked a lot of conversations online. Electric vehicle enthusiasts on X were quite impressed with the system’s capabilities to handle the city’s busy and crowded streets. Even more were pleasantly surprised when FSD Supervised performed a smooth hook turn in its demonstration.
In a comment to News.com.au, Drew emphasized that FSD’s global expansion is a priority for Tesla. “That’s Elon’s push. We have a global engineering team that are working across markets around a lot of FSD… actively working across all our markets to roll it out,” the executive noted.
No Regulatory Barriers
Interestingly enough, Drew also stated that there is no regulatory barrier to FSD hitting Australia’s roads. This suggests that FSD may be released in Australia once Tesla is satisfied with the local calibration and performance of the system on the country’s inner city streets.
“There’s currently no blockers in Australia to releasing Full Self Driving Supervised, as we have in North America. It’s something our business is working on releasing. I don’t have a timeline currently for you, but it’s certainly very exciting to be able to bring that to a market that doesn’t have a regulatory blocker,” Drew stated.
Tesla’s FSD demonstrations have been quite impressive as of late, with the company also publishing a video showing the system navigating France’s Arc de Triomphe, one of Europe’s most complicated roundabouts, recently. Over in China, a Tesla Model 3 owner also used FSD to travel almost 2,485 miles from the Henan Province to the base camp of Mt. Everest.
News
Tesla China registrations bounce back to 11.1k vehicles in May’s 2nd full week
Tesla China’s domestic vehicle registrations have been volatile in recent weeks.

Tesla reported 11,130 insurance registrations in China in the week of May 12-18, 2025. These represent a 262.5% increase from 3,070 registrations that the company saw in the week ending May 11.
Tesla China’s domestic vehicle registrations have been volatile in recent weeks, suggesting that Giga Shanghai may still be exporting Model 3 and Model Y vehicles to foreign territories this month.
Tesla China’s Registrations
In the week ending May 4, Tesla China saw 7,300 new vehicle registrations. This was not that surprising considering that Tesla may still be allocating Gigafactory Shanghai’s output to vehicle exports. In the week ending May 11, however, industry watchers were quite surprised to see just 3,070 registrations from Tesla China.
The 262.54% bounce in vehicle registrations in the week ending May 18 is thus a pleasant update from the world’s biggest and most competitive electric vehicle market. Even with these results, however, industry watchers still note that Tesla China’s registrations this 2025 are still down 6.5% year-over-year.
Tesla China does not report its weekly sales figures, though the company’s overall performance in the domestic automotive sector can be inferred through new vehicle registration data. Fortunately, these registrations are closely tracked by industry watchers, as well as local automakers such as Li Auto.
Domestic Sales and Exports
Following the start of domestic deliveries of the new Model Y in China, expectations were high that the company would see a steady rise in registrations this second quarter. Giga Shanghai does not only supply vehicles to the domestic Chinese market, after all, as the facility also serves as the company’s primary vehicle export hub, providing Model 3 sedans and Model Y crossovers to several territories.
Tesla China sold 28,731 vehicles domestically and exported 29,728 vehicles in April. In comparison, the company saw 74,127 domestic registrations and 4,701 exports in March 2025, as per data compiled by CNEV Post. Considering Tesla China’s registrations this May, it would not be surprising if the company’s exports this month would exceed March’s 4,701 units.
News
xAI receives more Tesla Megapacks for Colossus 2

xAI is bolstering its Colossus 2 data center in Memphis with 168 Tesla Megapacks, enhancing the energy infrastructure for its ambitious AI supercomputer expansion. The deployment underscores xAI’s push to lead AI innovation while addressing environmental concerns.
The first Colossus site is connected to a 150 megawatts (MW) substation powered by MLGW and TVA. It is supported by approximately 156 Megapacks, providing 150 MW of stored energy backup to xAI’s supercomputer. The 168 Tesla Megapacks recently delivered to xAI’s Memphis site will provide battery storage backup to Colossus 2.
In December 2024, xAI doubled the capacity of Colossus to 200,000 Nvidia H100 GPUs, which consumes 250 MW of power–enough to energize 250,000 homes. In March 2025, the AI company bought a 1-million-square-foot site in Whitehaven, Memphis, for $80 million. xAI’s Whitehaven site could host up to 350,000 GPUs with the potential to deploy the largest number of Tesla Megapacks for backup power.
xAI plans to scale Colossus up to 1 million GPUs to create the world’s largest AI supercomputer. A 1-million-GPU setup would require over 1 gigawatt, about one-third of Memphis’s peak summer demand.
Initially reliant on natural gas turbines, Colossus faced criticism for nitrogen oxide emissions. The 150 MW substation, completed in early 2025, reduced turbine use by half, with Megapacks providing cleaner backup power. By fall 2025, xAI expects the second substation to come online. Once the second substation is online, the remaining turbines will only be used for backup, reducing the project’s carbon footprint.
Tesla Energy’s Q1 2025 performance, with a 156% year-over-year increase and 10.4 GWh of storage deployed, supports xAI’s needs. Tesla’s Megapack factory in Waller County, Texas, set to create 1,500 jobs, signals further commitment to scaling energy solutions for projects like Colossus.
xAI’s rapid expansion, backed by Tesla Megapacks, positions it to rival AI leaders like OpenAI and Google. The Colossus 2 deployment reflects a strategic blend of cutting-edge AI and sustainable energy. As Memphis’ infrastructure adapts to unprecedented power demands, xAI and Tesla are reshaping the AI landscape with a focus on efficiency and environmental responsibility.
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