Connect with us

News

Tesla Autopilot and artificial intelligence: The unfair advantage

Published

on

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.

Advertisement
-

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.

Advertisement
Comments

Elon Musk

Elon Musk teases TSMC as potential Terafab partner

Published

on

SpaceX Terafab rendering
SpaceX Terafab rendering

Elon Musk has acknowledged that early discussions with Taiwan Semiconductor Manufacturing Company (TSMC) could bring the company into his ambitious Terafab semiconductor project, signaling a possible partnership with the world’s leading contract chipmaker.

Musk confirmed that early talks are underway, but as of right now, they are “just discussions.” There is no confirmation of a deal nor dismissal of the possibility of one, leaving open the prospect of one of the largest advanced-chip collaborations under discussion in the U.S.

The report that speculated on potential discussions between Terafab and TSMC comes from Tim Culpan, who outlined a few ways the collaboration could operate. One is TSMC using the project as an “anchor customer” for future facilities in Texas, potentially contributing process expertise, operational know-how, or capacity while Terafab provides capital, long-term purchase commitments, or both.

Tesla and SpaceX jointly developed the Terafab project, with Intel already participating on the tech side. Elon Musk announced the project in March, and it intends to produce more than one terawatt of AI compute capacity annually once fully built.

Advertisement
-

Elon Musk’s Terafab project locks up massive new partner

Company statements place the first phase at approximately $16.8 billion in cost, with later filings pointing to a total that could reach well into the tens of billions across multiple stages.

Intel joined the effort in April 2026 and is expected to supply its 14A manufacturing process for the full-scale plant.

Musk has said existing suppliers, including Samsung and TSMC, remain important for near-term needs; Tesla already has production arrangements with Samsung for AI5 and AI6 chips, but that future demand from Optimus robots, Cybercab vehicles, and planned space-based data centers will eventually exceed what the global industry can currently deliver.

Terafab is positioned as the long-term answer to that projected shortfall, and Tesla did something similar during COVID to avoid a chip shortage. This is just a much larger-scale solution.

If the partnership were to materialize, it would add TSMC’s industry-leading strategies to a project that already combines Tesla’s and SpaceX’s capital and offtake with Intel’s process technology. For now, the only public confirmation is Musk’s brief acknowledgement that conversations are occurring.

Advertisement
-
Continue Reading

News

Tesla reveals early Robotaxi charging strategy, showing scrappy DNA

Published

on

Credit: Tesla

Tesla’s early strategy for charging units operating within its Robotaxi fleet reveals that the company surely has not lost any of that scrappy DNA that took it from an unlikely success story to the most valuable carmaker in the world.

An observer at a Tesla Supercharger in Austin spotted ten total Robotaxi vehicles arrive: one Cybercab and nine Model Y units. A Tesla employee was waiting at the lot and allowed each unit to park itself; every car that arrived had nobody in it.

Tesla wins FCC approval for wireless Cybercab charging system

The Tesla employee would walk around and plug each car in, adjusting the parking if needed:

Advertisement
-

It’s a very interesting strategy, but extremely understandable at this early point in the Robotaxi program. It’s only been out for about 15 months, and Cybercab just entered the fleet in early September.

On top of that, Tesla is still working tirelessly on its wireless charging apparatus, and a new patent was just published regarding that product last week.

However, this is just another example of how Tesla still has plenty of that scrappy DNA leftover from the “production hell” days, when CEO Elon Musk slept on the floor of the factory, employees were working crazy hours, Tesla was building Sprung Structures to build cars in, and the company was tiptoeing on the brink of bankruptcy.

For now, Tesla is utilizing a simple system for recharging its ride-hailing vehicles, and that is a Tesla employee doing it manually until another solution presents itself. Sure, it’s not the most high-tech thing, and it certainly is not what people might have expected at this point in time, but it works, and it’s keeping the entire suite running.

Advertisement
-
Continue Reading

News

Tesla Robotaxi expands hours, Musk explains why it’s been a challenge

Published

on

Credit: Tesla

Tesla is expanding its Robotaxi service hours by pushing the time back by one hour, keeping the ride-hailing service operational until 11 p.m., one hour later than previously.

CEO Elon Musk confirmed the change and offered a specific reason the expansion has been gradual: the system still needs to reliably avoid small pets that are difficult to see after dark, as they commonly blend into the color of the road, especially when they’re grey.

The latest adjustment restores only a fraction of the operating window the service once held. When paid Robotaxi rides began in Austin on June 22, 2025, vehicles ran from 6 a.m. to midnight.

Tesla Robotaxi will be a 24/7 service: here’s when

In September 2025, Tesla lengthened the day to a 2 a.m. close, producing a 20-hour window that stayed in place for most of the following year. By early August of this year, the cutoff had already been pulled back; an August 26 update formalized hours of 6 a.m. to 10 p.m. across Austin and several other markets.

The October move to 11 p.m. therefore leaves the Austin day one hour shorter than the original launch schedule and three hours shorter than the 2025 peak.

Advertisement
-

Musk addressed the constraint directly after the announcement. “The main thing we’re trying to solve is making sure that we don’t run over pets when they’re hard to see at night,” he wrote. “Literally trying to avoid grey kittens on grey tarmac in the dark.”

The example points to a low-contrast perception problem in which a small animal can blend into the road surface under limited lighting.

Tesla’s vehicles rely on cameras and neural-network processing rather than lidar; Musk has previously argued that advanced vision software can extract useful information even in low light by analyzing photon counts, but the pet-detection case remains the stated limiter in later hours.

Advertisement
-

The modest schedule change arrives alongside faster growth in the purpose-built Cybercab fleet. Texas registration data tracked by observers showed the Austin Cybercab count rising sharply in recent weeks, reaching 169 vehicles after more than 100 were added in a short span.

Tesla has indicated that a broader shift toward 24-hour operation is tied to the upcoming FSD v15 software release expected this month on Robotaxi vehicles. Until that capability is validated for the edge cases Musk described, the company continues to add service time incrementally rather than jumping straight to overnight coverage.

The one-hour extension gives Austin riders a later option for evening trips while the underlying detection work continues.

Continue Reading