News
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 rolled out a new Supercharging safety feature in the United States, one that will answer concerns that some owners may have if they need to leave in a pinch.
It is also a suitable alternative for non-Tesla chargers, like third-party options that feature J1772 or CCS to NACS adapters.
The feature has been available in Europe for some time, but it is now rolling out to Model 3 and Model Y owners in the U.S.
With Software Update 2026.2.3, Tesla is launching the Unlatching Charge Cable function, which will now utilize the left rear door handle to release the charging cable from the port. The release notes state:
“Charging can now be stopped and the charge cable released by pulling and holding the rear left door handle for three seconds, provided the vehicle is unlocked, and a recognized key is nearby. This is especially useful when the charge cable doesn’t have an unlatch button. You can still release the cable using the vehicle touchscreen or the Tesla app.”
The feature was first spotted by Not a Tesla App.
This is an especially nice feature for those who commonly charge at third-party locations that utilize plugs that are not NACS, which is the Tesla standard.
For example, after plugging into a J1772 charger, you will still be required to unlock the port through the touchscreen, which is a minor inconvenience, but an inconvenience nonetheless.
Additionally, it could be viewed as a safety feature, especially if you’re in need of unlocking the charger from your car in a pinch. Simply holding open the handle on the rear driver’s door will now unhatch the port from the car, allowing you to pull it out and place it back in its housing.
This feature is currently only available on the Model 3 and Model Y, so Model S, Model X, and Cybertruck owners will have to wait for a different solution to this particular feature.
News
LG Energy Solution pursuing battery deal for Tesla Optimus, other humanoid robots: report
Optimus is expected to be one of Tesla’s most ambitious projects, with Elon Musk estimating that the humanoid robot could be the company’s most important product.
A recent report has suggested that LG Energy Solution is in discussions to supply batteries for Tesla’s Optimus humanoid robot.
Optimus is expected to be one of Tesla’s most ambitious projects, with Elon Musk estimating that the humanoid robot could be the company’s most important product.
Humanoid robot battery deals
LG Energy Solution shares jumped more than 11% on the 28th after a report from the Korea Economic Daily claimed that the company is pursuing battery supply and joint development agreements with several humanoid robot makers. These reportedly include Tesla, which is developing Optimus, as well as multiple Chinese robotics companies.
China is already home to several leading battery manufacturers, such as CATL and BYD, making the robot makers’ reported interest in LG Energy Solution quite interesting. Market participants interpreted the reported outreach as a signal that performance requirements for humanoid robots may favor battery chemistries developed by companies like LG.
LF Energy Solution vs rivals
According to the report, energy density is believed to be the primary reason humanoid robot developers are evaluating LG Energy Solution’s batteries. Unlike electric vehicles, humanoid robots have significantly less space available for battery packs while requiring substantial power to operate dozens of joint motors and onboard artificial intelligence processors.
LG Energy Solution’s ternary lithium batteries offer higher energy density compared with rivals’ lithium iron phosphate (LFP) batteries, which are widely used by Chinese EV manufacturers. That advantage could prove critical for humanoid robots, where runtime, weight, and compact packaging are key design constraints.
News
Tesla receives approval for FSD Supervised tests in Sweden
Tesla confirmed that it has been granted permission to test FSD Supervised vehicles across Sweden in a press release.
Tesla has received regulatory approval to begin tests of its Full Self-Driving Supervised system on public roads in Sweden, a notable step in the company’s efforts to secure FSD approval for the wider European market.
FSD Supervised testing in Sweden
Tesla confirmed that it has been granted permission to test FSD Supervised vehicles across Sweden following cooperation with national authorities and local municipalities. The approval covers the Swedish Transport Administration’s entire road network, as well as urban and highways in the Municipality of Nacka.
Tesla shared some insights into its recent FSD approvals in a press release. “The approval shows that cooperation between authorities, municipalities and businesses enables technological leaps and Nacka Municipality is the first to become part of the transport system of the future. The fact that the driving of the future is also being tested on Swedish roads is an important step in the development towards autonomy in real everyday traffic,” the company noted.
With approval secured for FSD tests, Tesla can now evaluate the system’s performance in diverse environments, including dense urban areas and high-speed roadways across Sweden, as noted in a report from Allt Om Elbil. Tesla highlighted that the continued development of advanced driver assistance systems is expected to pave the way for improved traffic safety, increased accessibility, and lower emissions, particularly in populated city centers.
Tesla FSD Supervised Europe rollout
FSD Supervised is already available to drivers in several global markets, including Australia, Canada, China, Mexico, New Zealand, and the United States. The system is capable of handling city and highway driving tasks such as steering, acceleration, braking, and lane changes, though it still requires drivers to supervise the vehicle’s operations.
Tesla has stated that FSD Supervised has accumulated extensive driving data from its existing markets. In Europe, however, deployment remains subject to regulatory approval, with Tesla currently awaiting clearance from relevant authorities.
The company reiterated that it expects to start rolling out FSD Supervised to European customers in early 2026, pending approvals. It would then be unsurprising if the company secures approvals for FSD tests in other European territories in the coming months.
Tesla rolls out new Supercharging safety feature in the U.S.
LG Energy Solution pursuing battery deal for Tesla Optimus, other humanoid robots: report
