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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.
SpaceX’s Raptor engine family has steadily increased sea-level thrust while simultaneously reducing mass, turning iterative engineering gains into substantially higher performance for the Super Heavy booster. CEO Elon Musk shed more light on how powerful Raptor 4 will be, and it’s pretty crazy.
Raptor 1 delivered 185 metric tons of thrust at roughly 2,080 kilograms, while Raptor 2 raised that to 230 tons while cutting mass to about 1,630 kilograms. SpaceX data for Raptor 3 lists a target of 280 tons at 1,525 kilograms (with further reductions in associated vehicle hardware), while operational flight ratings have been cited near 250 tons.
This morning, Elon Musk stated that Raptor 4 is expected to reach 300 tons of sea-level thrust at roughly the same mass as Raptor 3. Across these versions, thrust has risen by more than 60 percent from the first engines while engine mass has fallen, producing a sharp improvement in thrust-to-weight ratio. This is a true testament to how great SpaceX engineering has been:
🚀 Elon says Raptor 4 will make 300 tons of thrust at sea level at roughly the same mass as Raptor 3.
How far Raptor has come:
Raptor 1: 185 tf, 2,080 kg
Raptor 2: 230 tf, 1,630 kg
Raptor 3: 250 tf, 1,525 kg
Raptor 4: 300 tf33 on Super Heavy = ~9,900 tf, nearly 3x Saturn V https://t.co/HQDswZhyvL
— TESLARATI (@Teslarati) October 26, 2026
With 33 engines on SuperHeavy, the jump from earlier versions to a 300-ton Raptor 4 would produce roughly 9,900 metric tons of total liftoff thrust, nearly three times the Saturn V’s approximately 3,400 metric tons from its five F-1 engines.
This is not just a larger number on a data sheet, either, as sea-level thrust is the force available the moment the vehicle leaves the pad. This is when it is heaviest and still deep in Earth’s gravity well and dense atmosphere.
Higher levels of sea-level thrust directly improves the initial thrust-to-weight ratio of the full stack. A higher ratio produces faster acceleration off the pad, which shortens the time the rocket has to spend fighting gravity, and gravity losses during the first minute or two of the flight are a major drain on total available delta-v. Every second shaved off of that early climb preserves more propellant energy for reaching orbital velocity or for carrying extra payload.
Because Super Heavy’s engine count is constrained by vehicle diameter and packing density, increasing thrust per engine is the most straightforward way to raise total liftoff performance without redesigning the booster structure or design.
The same-mass target for Raptor 4 is equally important. Holding engine mass roughly constant while raising thrust improves the engine’s own thrust-to-weight ratio and reduces the structural and propellant mass fraction that must be carried solely to support the engines.
Earlier Raptor iterations also simplified or eliminated extensive vehicle-side hardware such as heat shields. These gains compound: more force for less installed mass leaves additional capacity for propellant, payload, or operational margins such as engine-out capability.
For Starship’s architecture, the practical effects are large. Greater liftoff thrust supports heavier vehicles, larger propellant loads, and higher payloads to low Earth orbit, figures SpaceX has targeted in the 100-plus-ton reusable range. That capacity underpins orbital refueling, lunar missions, and eventual Mars cargo and crew flights.
Continued growth in sea-level thrust therefore tightens the gap between theoretical rocket performance and the high flight rates and reusability needed to make large-scale space transport practical.
Tesla has expanded its Tesla Assisted Driving (TAD) suite to its tenth European country, as Latvia joined a growing list of European Union member states authorizing the company’s advanced driver assistance technology.
Tesla Europe announced this morning that the system is now approved in Latvia, with a software rollout to begin soon.
The approval and rollout follow recognition of a provisional European type approval originally granted by the Netherlands’ RDW authority on April 10.
🚨 Latvia has just received approval for Tesla Full Self-Driving (Supervised)
This is the 10th country in the EU to gain approval:
1. Netherlands — 10 April 2026 (original RDW approval)
2. Lithuania — 20 May 2026
3. Estonia — 29 May 2026
4. Denmark — 9 June 2026
5. Belgium — 10 June 2026
6. Slovenia — 7 September 2026
7. Czechia — 21 September 2026
8. Croatia — 29 September 2026
9. Slovakia — 16 October 2026— TESLARATI (@Teslarati) October 26, 2026
Latvia’s Road Traffic Safety Directorate (CSDD) evaluated the Dutch documentation, coordinated with the other national authorities, and reviewed updates from Tesla. These included tightened limits on speed offsets, automatic resets of any manual speed adjustments after each trip, and stronger driver monitoring.
In Europe, the feature is marketed as Tesla Assisted Driving after a recent rule change that labeled the name “Full Self-Driving” as misleading.
The system remains an SAE Level 2 driver assistance tool, not unsupervised autonomy. It can control speed, steering, braking, lane changes, and intersections while following a navigation route. Drivers need not keep their hands on the wheel at all times, yet they must continuously monitor the road and be prepared to intervene immediately.
The sequence of EU recognitions began with the Netherlands in April and continued through Lithuania, Estonia, Denmark, Belgium, Slovenia, Czechia, Croatia, and Slovakia. Most have relied on mutual recognition of the single Dutch provisional approval rather than independent national testing.
These national clearances do not yet constitute bloc-wide authorization. An EU-wide decision requires a qualified majority in the Technical Committee on Motor Vehicles: at least 15 of 27 member states representing 65 percent of the EU population. Larger markets, like Germany, France, and Italy, remain under review, and a vote is expected this December.
However, for Latvian Tesla owners with compatible vehicles and software, the imminent rollout expands access to the supervised system while underscoring that attentive human oversight remains essential.
Tesla expanded its Robotaxi geofence in Houston, Texas, today, enlarging the service area and drawing a new rocket-shaped boundary across the city’s northwestern and central parts.
Although CEO Elon Musk said it was just a coincidence, the expansion seems to be an ode to SpaceX and its potential merger with Tesla.
🚨 Tesla has just expanded its Robotaxi geofence in Houston
It looks a lot like a rocket — we all remember the shape in Austin 🤣 https://t.co/cFOPEuiJ4u
— TESLARATI (@Teslarati) October 26, 2026
The official Tesla Robotaxi account announced the change with the lines “Houston, we have liftoff” and “Bigger service area now live,” pairing them with a map overlay.
The prior white geofence, roughly 25 square miles covering Jersey Village, Harvest Bend, and the Willowbrook corridor along U.S. 290 and State Highway 249, now sits inside a larger blue zone that stretches southeast toward Bellair and closer to central Houston.
Houston’s Robotaxi service launched on April 18, 2026, the same day as Dallas, as Tesla’s first unsupervised public expansion beyond Austin. From the start, the vehicles were Model Ys running without anyone in the front seats, booked through the dedicated Tesla Robotaxi app and open to the public inside the geofence.
Trackers measured the initial zone at about 25 square miles; by late September it had not grown substantially. Community and registry data indicated a modest local fleet of unsupervised Model Ys, while dozens to nearly 200 Cybercabs, the purpose-built, steering-wheel-free two-seaters, have been spotted staging and testing in Houston lots, though public Cybercab rides remain limited to Austin for now.
Across the broader Robotaxi program, Tesla began public Robotaxi rides in Austin in June 2025, as a small geofence and vehicles with safety monitors became available for a ride-hailing service. Later on, Tesla removed the monitors and steadily expanded the service area until it covered most of the Austin metro area.
Unsupervised Robotaxi services now run in six cities: Austin, Dallas, Houston, Miami, Orlando, and Tampa. Cumulative driverless miles reported by the company have reached several million. The Cybercab entered public service in Austin in early September 2026 and has scaled rapidly there. The company has also said that Dallas is next for Cybercab rides in November, with further cities and 24/7 hours targeted by year-end, plus fleet-operator sales of the vehicle.
Waymo also operates a fully driverless service in Houston, which has been open to the public since August of this year.
The Houston expansion continues Tesla’s pattern of starting with tightly controlled validation zones before widening coverage as real-world data accumulates, while the rocket motif on the map underscores the company’s habit of injecting visual flair into its autonomy rollout.
Riders inside the new boundary can request unsupervised Model Y trips in the Robotaxi app; exact operating hours and further Cybercab availability remain subject to app updates and company statements.
How SpaceX Is raising Raptor’s sea-level thrust while holding engine mass steady
Tesla Assisted Driving expands to tenth EU country
