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Tesla Autopilot and artificial intelligence: The unfair advantage

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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.

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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.

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Celebrating SpaceX’s Falcon Heavy Tesla Roadster launch, seven years later (Op-Ed)

Seven years later, the question is no longer “What if this works?” It’s “How far does this go?”

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SpaceX's first Falcon Heavy launch also happened to be a strategic and successful test of Falcon upper stage coast capabilities. (SpaceX)

When Falcon Heavy lifted off in February 2018 with Elon Musk’s personal Tesla Roadster as its payload, SpaceX was at a much different place. So was Tesla. It was unclear whether Falcon Heavy was feasible at all, and Tesla was in the depths of Model 3 production hell.

At the time, Tesla’s market capitalization hovered around $55–60 billion, an amount critics argued was already grossly overvalued. SpaceX, on the other hand, was an aggressive private launch provider known for taking risks that traditional aerospace companies avoided.

The Roadster launch was bold by design. Falcon Heavy’s maiden mission carried no paying payload, no government satellite, just a car drifting past Earth with David Bowie playing in the background. To many, it looked like a stunt. For Elon Musk and the SpaceX team, it was a bold statement: there should be some things in the world that simply inspire people.

Inspire it did, and seven years later, SpaceX and Tesla’s results speak for themselves.

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Credit: SpaceX

Today, Tesla is the world’s most valuable automaker, with a market capitalization of roughly $1.54 trillion. The Model Y has become the best-selling car in the world by volume for three consecutive years, a scenario that would have sounded insane in 2018. Tesla has also pushed autonomy to a point where its vehicles can navigate complex real-world environments using vision alone.

And then there is Optimus. What began as a literal man in a suit has evolved into a humanoid robot program that Musk now describes as potential Von Neumann machines: systems capable of building civilizations beyond Earth. Whether that vision takes decades or less, one thing is evident: Tesla is no longer just a car company. It is positioning itself at the intersection of AI, robotics, and manufacturing.

SpaceX’s trajectory has been just as dramatic.

The Falcon 9 has become the undisputed workhorse of the global launch industry, having completed more than 600 missions to date. Of those, SpaceX has successfully landed a Falcon booster more than 560 times. The Falcon 9 flies more often than all other active launch vehicles combined, routinely lifting off multiple times per week.

Falcon Heavy successfully clears the tower after its maiden launch, February 6, 2018. (Tom Cross)

Falcon 9 has ferried astronauts to and from the International Space Station via Crew Dragon, restored U.S. human spaceflight capability, and even stepped in to safely return NASA astronauts Butch Wilmore and Suni Williams when circumstances demanded it.

Starlink, once a controversial idea, now dominates the satellite communications industry, providing broadband connectivity across the globe and reshaping how space-based networks are deployed. SpaceX itself, following its merger with xAI, is now valued at roughly $1.25 trillion and is widely expected to pursue what could become the largest IPO in history.

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And then there is Starship, Elon Musk’s fully reusable launch system designed not just to reach orbit, but to make humans multiplanetary. In 2018, the idea was still aspirational. Today, it is under active development, flight-tested in public view, and central to NASA’s future lunar plans.

In hindsight, Falcon Heavy’s maiden flight with Elon Musk’s personal Tesla Roadster was never really about a car in space. It was a signal that SpaceX and Tesla were willing to think bigger, move faster, and accept risks others wouldn’t.

The Roadster is still out there, orbiting the Sun. Seven years later, the question is no longer “What if this works?” It’s “How far does this go?”

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Tesla launches Cybertruck vehicle-to-grid program in Texas

The initiative was announced by the official Tesla Energy account on social media platform X.

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Credit: Tesla

Tesla has launched a vehicle-to-grid (V2G) program in Texas, allowing eligible Cybertruck owners to send energy back to the grid during high-demand events and receive compensation on their utility bills. 

The initiative, dubbed Powershare Grid Support, was announced by the official Tesla Energy account on social media platform X.

Texas’ Cybertruck V2G program

In its post on X, Tesla Energy confirmed that vehicle-to-grid functionality is “coming soon,” starting with select Texas markets. Under the new Powershare Grid Support program, owners of the Cybertruck equipped with Powershare home backup hardware can opt in through the Tesla app and participate in short-notice grid stress events.

During these events, the Cybertruck automatically discharges excess energy back to the grid, supporting local utilities such as CenterPoint Energy and Oncor. In return, participants receive compensation in the form of bill credits. Tesla noted that the program is currently invitation-only as part of an early adopter rollout.

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The launch builds on the Cybertruck’s existing Powershare capability, which allows the vehicle to provide up to 11.5 kW of power for home backup. Tesla added that the program is expected to expand to California next, with eligibility tied to utilities such as PG&E, SCE, and SDG&E.

Powershare Grid Support

To participate in Texas, Cybertruck owners must live in areas served by CenterPoint Energy or Oncor, have Powershare equipment installed, enroll in the Tesla Electric Drive plan, and opt in through the Tesla app. Once enrolled, vehicles would be able to contribute power during high-demand events, helping stabilize the grid.

Tesla noted that events may occur with little notice, so participants are encouraged to keep their Cybertrucks plugged in when at home and to manage their discharge limits based on personal needs. Compensation varies depending on the electricity plan, similar to how Powerwall owners in some regions have earned substantial credits by participating in Virtual Power Plant (VPP) programs.

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Samsung nears Tesla AI chip ramp with early approval at TX factory

This marks a key step towards the tech giant’s production of Tesla’s next-generation AI5 chips in the United States.

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Tesla-Chips-HW3-1
Image used with permission for Teslarati. (Credit: Tom Cross)

Samsung has received temporary approval to begin limited operations at its semiconductor plant in Taylor, Texas.

This marks a key step towards the tech giant’s production of Tesla’s next-generation AI5 chips in the United States.

Samsung clears early operations hurdle

As noted in a report from Korea JoongAng Daily, Samsung Electronics has secured temporary certificates of occupancy (TCOs) for a portion of its semiconductor facility in Taylor. This should allow the facility to start operations ahead of full completion later this year.

City officials confirmed that approximately 88,000 square feet of Samsung’s Fab 1 building has received temporary approval, with additional areas expected to follow. The overall timeline for permitting the remaining sections has not yet been finalized.

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Samsung’s Taylor facility is expected to manufacture Tesla’s AI5 chips once mass production begins in the second half of the year. The facility is also expected to produce Tesla’s upcoming AI6 chips. 

Tesla CEO Elon Musk recently stated that the design for AI5 is nearly complete, and the development of AI6 is already underway. Musk has previously outlined an aggressive roadmap targeting nine-month design cycles for successive generations of its AI chips.

Samsung’s U.S. expansion

Construction at the Taylor site remains on schedule. Reports indicate Samsung plans to begin testing extreme ultraviolet (EUV) lithography equipment next month, a critical step for producing advanced 2-nanometer semiconductors.

Samsung is expected to complete 6 million square feet of floor space at the site by the end of this year, with an additional 1 million square feet planned by 2028. The full campus spans more than 1,200 acres.

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Beyond Tesla, Samsung Foundry is also pursuing additional U.S. customers as demand for AI and high-performance computing chips accelerates. Company executives have stated that Samsung is looking to achieve more than 130% growth in 2-nanometer chip orders this year.

One of Samsung’s biggest rivals, TSMC, is also looking to expand its footprint in the United States, with reports suggesting that the company is considering expanding its Arizona facility to as many as 11 total plants. TSMC is also expected to produce Tesla’s AI5 chips. 

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