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.
Lifestyle
Tesla teases “Halloween Mode” update with Optimus rising from a graveyard
Tesla’s Halloween teaser hides a covered vehicle and an Optimus hand rising from the ground.
Tesla has started teasing a Halloween software update for its vehicles, with a short clip on X that reads, “Halloween is coming.” The clip opens on a glowing pumpkin before pulling back to the car’s center touchscreen, where the usual parked visualization has been replaced by a graveyard scene, and the vehicle draped with a white sheet so it reads as a cartoon ghost.
Halloween is coming pic.twitter.com/lM3ASUeOqX
— Tesla (@Tesla) October 1, 2026
The second detail is a robotic hand clawing its way out of the dirt like a zombie, which looks to be the hand of Tesla’s latest Optimus V3 humanoid robot. While Tesla still has not formally shown Optimus Gen 3 walking around in service, renders pulled from Tesla’s Android app last month gave the clearest look yet, including far more refined hands that Tesla has said carry 22 degrees of freedom. The hand has been the hardest part of the program. Musk has called it the majority of the robot’s engineering difficulty, and Tesla’s patents describe a design driven by tendons with the actuators moved into the forearm.
Tesla Optimus V3 hand and arm details revealed in new patents
Optimus also has a Halloween track record. Last October the robot handed out candy in Times Square, and a costumed “zombie” Optimus shuffled around the Tesla Diner in Los Angeles on Halloween night.
On the software side, Tesla’s 2025 Holiday Update expanded Santa Mode with a Santa sleigh, snowmen, snow effects, and a festive lock chime, so it wouldn’t be too far fetched if we saw something similar but themed for a Halloween Mode.
News
Tesla says fixes on Full Self-Driving’s two biggest issues are on the way
Tesla Full Self-Driving is set to receive improvements to address its two biggest issues, according to a company engineer.
Director of Engineering at Tesla AI, Phil Duan, revealed in a post on X that improvements to both pothole avoidance and navigation “are coming,’ something we have heard many times in the past. However, there are a few things that seem to hint that things might be different this time around.
Improvements on both are coming.
— Phil Duan (@pduan) October 1, 2026
Pothole avoidance, navigation, speed control, and left lane camping are some of the most prevalent and frequently mentioned shortcomings of the Full Self-Driving suite. These are a few of the biggest issues that have kept Tesla Full Self-Driving as a Supervised suite, meaning drivers must remain attentive during operation.
Pothole Avoidance
Pothole avoidance was first mentioned as an “Upcoming Improvement” with the Tesla Full Self-Driving v14.3 update back in early April of this year. It was listed alongside “Expand reasoning to all behaviors beyond destination handling.”
It’s been six months since we first saw pothole avoidance explicitly mentioned, and it has not moved beyond that and joined the main release notes yet.
Tesla has not shed any light on why pothole avoidance has been such an issue for it to solve, but it also has issues identifying large bumps much of the time, so its modeling of sudden changes in road conditions is likely pretty weak at this particular point. I’ve had more issues with large bumps than potholes, personally, but both are issues that need to be resolved.
This is that big bounce that I mentioned in the quoted post.
It’s just a tad too drastic to take at the speed FSD wants to go over it. You can see me quickly swipe down into Sloth, but I intervened. https://t.co/K20PK9ysBg pic.twitter.com/81Oc82ZJcZ
— TESLARATI (@Teslarati) August 2, 2026
It makes sense that things might be pretty close to being released to the public, as we are going on such an extensive period of time between it being mentioned and it actually being deployed.
Navigation
Navigation is likely the most painful part of using Full Self-Driving, as it routinely takes strange routes, has trouble with local rules (like Except Right Turn Stop Signs in Pennsylvania), and sometimes does not realize that maneuvers it is suggesting are against the law. Turning out of my neighborhood, you cannot turn left, yet my Model Y still suggests it roughly 70 percent of the time when I’m leaving.
However, Tesla might be close to a breakthrough on this. With the Summer Update, Tesla added “Preferred Routes” alongside “Automatic Navigation.”
Preferred Routes prioritized roads that the driver had actually taken before, instead of always defaulting to what the vehicle believes is the most efficient path. This has already solved many of my issues. Formerly, I would turn off the Online Routing setting, and that would eliminate most of my complaints with routing, but then you lose out later on the Live Traffic Visualization.
Tesla’s Navigation has improved tremendously thanks to the Preferred Routes release with the Summer Update, but it still could use some polishing, as it still suggests strange routes from time to time, and it also has a lot of issues getting out of a parking lot. I find that those truly confuse FSD sometimes.
News
SpaceX’s midnight spy satellite launch quietly set a new record
Falcon Heavy launched its first NRO mission while SpaceX landed four boosters in one day.
SpaceX closed out one of its busiest days ever with a midnight Falcon Heavy launch from Florida, and the rocket’s two side boosters came home to finish off a landing record the company had never set before.
Falcon Heavy lifted off from Launch Complex 39A at NASA’s Kennedy Space Center at 11:54 p.m. ET Thursday carrying NROL-97, a classified payload for the National Reconnaissance Office. It was the first time the NRO has flown on Falcon Heavy after 22 missions on Falcon 9, and the first NRO mission bought through the National Security Space Launch Phase 3 Lane 2 contract awarded in 2025, according to Spaceflight Now.
Falcon Heavy lifts off from pad 39A in Florida for the 14th time! pic.twitter.com/uuZLKNTdD7
— SpaceX (@SpaceX) October 2, 2026
Roughly eight minutes after liftoff, side boosters B1104 and B1072 touched down at Landing Zones 1 and 2 at Cape Canaveral Space Force Station, setting off double sonic booms across Brevard County. B1104 was flying for the second time and B1072 for the fourth. Both last flew on August 30 on NASA’s Nancy Grace Roman Space Telescope, making NROL-97 the quickest turnaround between Falcon Heavy missions to date. The brand new center core, B1106, was expended in the Atlantic so the payload could reach its high energy orbit, and SpaceX’s mission page noted the fairing had previously flown on the NROL-95 mission in July.
The two landings capped a record for SpaceX. Earlier Thursday, Falcon 9 booster B1101 returned to Landing Zone 40 after sending the Crew-13 astronauts to the International Space Station, and another Falcon 9 launched the Transporter-18 rideshare with 130 payloads from Vandenberg Space Force Base in California. Spaceflight Now reported it was the first time SpaceX has landed four boosters in a single day, wrapping up the triple header Teslarati previewed on Wednesday.
Falcon Heavy’s side boosters land on LZ-1 and LZ-2 pic.twitter.com/dBPcNeggFx
— SpaceX (@SpaceX) October 2, 2026
The mission also brought Landing Zone 1 back for what may be its final landing. SpaceX first landed an orbital class booster there in December 2015, but its lease on the former Launch Complex 13 site ended in 2025 as the company moved Florida landings to new pads at its own launch complexes. With LZ-40 already holding the Crew-13 booster, SpaceX brought LZ-1 back into service for one more night. Launch tracker Next Spaceflight listed NROL-97 as the final expected landing at the site.
NROL-97 adds to a fast growing stack of national security work for SpaceX. The company has flown four Space Force missions from Vandenberg since mid August, several believed to carry Starshield satellites, pushing its Pentagon contract total for 2026 past $8 billion. Elon Musk was also named this week to help lead the Pentagon’s Project Meridian study on the future of warfare.
The Florida doubleheader stood out for another reason. The Space Coast saw only one launch in all of September as SpaceX shifts more of its East Coast infrastructure toward Starship, which reached orbit for the first time on Flight 14 just three days earlier.

