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Stanford studies human impact when self-driving car returns control to driver

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Tesla Autopilot in 'Shadow Mode' will pit human vs computer

Researchers involved with the Stanford University Dynamic Design Lab have completed a study that examines how human drivers respond when an autonomous driving system returns control of a car to them. The Lab’s mission, according to its website, is to “study the design and control of motion, especially as it relates to cars and vehicle safety. Our research blends analytical approaches to vehicle dynamics and control together with experiments in a variety of test vehicles and a healthy appreciation for the talents and demands of human drivers.” The results of the study were published on December 6 in the first edition of the journal Science Robotics.

Holly Russell, lead author of study and former graduate student at the Dynamic Design Lab says, “Many people have been doing research on paying attention and situation awareness. That’s very important. But, in addition, there is this physical change and we need to acknowledge that people’s performance might not be at its peak if they haven’t actively been participating in the driving.”

The report emphasizes that the DDL’s autonomous driving program is its own proprietary system and is not intended to mimic any particular autonomous driving system currently available from any automobile manufacturer, such as Tesla’s Autopilot.

The study found that the period of time known as “the handoff” — when the computer returns control of a car to a human driver — can be an especially risky period, especially if the speed of the vehicle has changed since the last time the person had direct control of the car. The amount of steering input required to accurately control a vehicle varies according to speed. Greater input is needed at slower speeds while less movement of the wheel is required at higher speeds.

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People learn over time how to steer accurately at all speeds based on experience. But when some time elapses during which the driver is not directly involved in steering the car, the researchers found that drivers require a brief period of adjustment before they can accurately steer the car again. The greater the speed change while the computer is in control, the more erratic the human drivers were in their steering inputs upon resuming control.

“Even knowing about the change, being able to make a plan and do some explicit motor planning for how to compensate, you still saw a very different steering behavior and compromised performance,” said Lene Harbott, co-author of the research and a research associate in the Revs Program at Stanford.

Handoff From Computer to Human

The testing was done on a closed course. The participants drove for 15 seconds on a course that included a straightaway and a lane change. Then they took their hands off the wheel and the car took over, bringing them back to the start. After familiarizing themselves with the course four times, the researchers altered the steering ratio of the cars at the beginning of the next lap. The changes were designed to mimic the different steering inputs required at different speeds. The drivers then went around the course 10 more times.

Even though they were notified of the changes to the steering ratio, the drivers’ steering maneuvers differed significantly from their paths previous to the modifications during those ten laps. At the end, the steering ratios were returned to the original settings and the drivers drove 6 more laps around the course. Again the researchers found the drivers needed a period of adjustment to accurately steer the cars.

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The DDL experiment is very similar to a classic neuroscience experiment that assesses motor adaptation. In one version, participants use a hand control to move a cursor on a screen to specific points. The way the cursor moves in response to their control is adjusted during the experiment and they, in turn, change their movements to make the cursor go where they want it to go.

Just as in the driving test, people who take part in the experiment have to adjust to changes in how the controller moves the cursor. They also must adjust a second time if the original response relationship is restored. People can performed this experiment themselves by adjusting the speed of the cursor on their personal computers.

“Even though there are really substantial differences between these classic experiments and the car trials, you can see this basic phenomena of adaptation and then after-effect of adaptation,” says IIana Nisky, another co-author of the study and a senior lecturer at Ben-Gurion University in Israel “What we learn in the laboratory studies of adaptation in neuroscience actually extends to real life.”

In neuroscience this is explained as a difference between explicit and implicit learning, Nisky explains. Even when a person is aware of a change, their implicit motor control is unaware of what that change means and can only figure out how to react through experience.

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Federal and state regulators are currently working on guidelines that will apply to Level 5 autonomous cars. What the Stanford research shows is that until full autonomy becomes a reality, the “hand off” moment will represent a period of special risk, not because of any failing on the part of computers but rather because of limitations inherent in the brains of human drivers.

The best way to protect ourselves from that period of risk is to eliminate the “hand off” period entirely by ceding total control of driving to computers as soon as possible.

"I write about technology and the coming zero emissions revolution."

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Elon Musk

Tesla ditches India after years of broken promises

Tesla has ditched its plans to build a factory in India after years of failed negotiations.

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Tesla’s long-running effort to establish a manufacturing presence in India is officially over. India’s Minister of Heavy Industries H.D. Kumaraswamy confirmed on May 19, 2026 that Tesla has informed authorities it will not proceed with a manufacturing facility in the country.

Tesla first signaled serious interest in India around 2021, when it began hiring local staff and lobbying the Indian government for lower import tariffs. The ask was straightforward: reduce duties enough for Tesla to test the market with imported vehicles before committing capital to a local factory. India’s position was equally firm, with an ask of Tesla to commit to manufacturing first, then receive tariff relief. Neither side moved, and the talks quietly collapsed.

Tesla to open first India experience center in Mumbai on July 15

India had offered a policy that would reduce import duties from 110% down to 15% on EVs priced above $35,000, provided companies committed at least $500 million toward local manufacturing investment within three years. Tesla declined to participate. The tariff standoff was only part of the problem. Analysts pointed to significant gaps in India’s local supply chain, inadequate industrial infrastructure, and a mismatch between Tesla’s premium pricing and the purchasing power of India’s automotive market as additional factors that made the investment difficult to justify.

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First signs of an unraveling relationship came in April 2024, when Musk abruptly cancelled a planned trip to India where he was set to meet Prime Minister Modi and announce Tesla’s market entry. By July 2024, Fortune reported that Tesla executives had stopped contacting Indian government officials entirely. The government at that point understood Tesla had capital constraints and no plans to invest.

The more fundamental issue is that Tesla’s existing factories are currently operating at approximately 60% capacity, making a commitment to building new manufacturing capacity in a new market difficult to defend to investors. Tesla will continue selling imported Model Y vehicles through its existing showrooms in Mumbai, Delhi, Gurugram, and Bengaluru, but local production is no longer part of the plan.

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SpaceX reveals date for maiden Starship v3 launch

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Credit: SpaceX

SpaceX has revealed the date for the maiden voyage of Starship v3, its newest and most advanced version of the rocket yet.

Starship v3 represents a significant leap forward. At 124 meters tall when fully stacked, it stands taller than previous versions and boasts substantial upgrades.

The vehicle incorporates next-generation Raptor 3 engines, which deliver higher thrust, improved reliability, and simplified designs with fewer parts. Both the Super Heavy booster (Booster 19) and the Starship upper stage (Ship 39) feature these enhancements, along with structural improvements for greater payload capacity—exceeding 100 metric tons to low Earth orbit in reusable configuration.

SpaceX and its CEO Elon Musk have announced that the company aims to push the first launch of Starship v3 this Thursday. Musk included some clips of past Starship launches with the announcement.

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There are a lot of improvements to Starship v3 from past builds. Key hardware changes include a more robust heat shield, upgraded avionics, and modifications optimized for orbital refueling, a critical technology for future missions to the Moon and Mars. This flight marks the first launch from Starbase’s second orbital pad, allowing parallel operations and accelerating the cadence of tests.

This will be the 12th Starship launch for SpaceX. Flight 12 objectives include a full ascent profile, hot-staging separation, in-space engine relights, and reentry testing. The booster is expected to perform a controlled splashdown in the Gulf of Mexico, while the ship will deploy 20 Starlink simulator satellites and a pair of modified Starlink V3 units before attempting reentry.

Success would validate V3’s design for operational use, paving the way for rapid reusability and higher flight rates.

The rapid evolution from V2 to V3 underscores SpaceX’s iterative approach. Previous flights demonstrated booster catches, ship landings, and heat shield advancements. V3 builds on these with nearly every component refined, supported by an expanding production line at Starbase that churns out vehicles at an unprecedented pace.

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Starship V3 is here putting SpaceX closer to Mars than it has ever been

This launch comes amid growing momentum for SpaceX’s ambitious goals. Starship is central to NASA’s Artemis program for lunar landings and Elon Musk’s vision of making humanity multiplanetary. A successful V3 debut would boost confidence in achieving orbital refueling and crewed missions in the coming years.

As excitement builds, enthusiasts and engineers alike await liftoff. Weather and technical readiness will determine the exact timing, but the community is optimistic. Starship V3 is poised to push the boundaries of spaceflight once again, bringing reusable interplanetary transport closer to reality.

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Elon Musk breaks silence on OpenAI trial decision

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Gage Skidmore, CC BY-SA 4.0 , via Wikimedia Commons

Elon Musk broke his silence regarding the jury decision to throw out the case against OpenAI and Sam Altman. The Tesla, SpaceX, and xAI frontman has already indicated that an appeal will be filed regarding the decision, which went against him yesterday.

A Federal jury dismissed this high-profile lawsuit after less than two hours of deliberation due to a statute-of-limitations issue.

In a strongly worded post on X on May 18, Musk addressed the federal jury’s dismissal of his high-profile lawsuit against OpenAI, vowing to appeal the ruling to the Ninth Circuit Court of Appeals. The decision, according to Musk, was centered not on the substantive claims but on a statute-of-limitations technicality.

Musk’s lawsuit, filed in 2024, accused OpenAI co-founders Sam Altman and Greg Brockman of breaching the organization’s original nonprofit mission. OpenAI was established in 2015 as a non-profit dedicated to developing artificial intelligence for the benefit of all humanity, with Musk as a key early donor and co-founder before departing in 2018.

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Musk alleged that Altman and Brockman improperly shifted the company toward a for-profit model, enriched themselves through massive valuations and partnerships (including with Microsoft), and betrayed founding agreements.

In his post, Musk emphasized that the judge and jury “never actually ruled on the merits of the case, just on a calendar technicality.” He stated unequivocally: “There is no question to anyone following the case in detail that Altman & Brockman did in fact enrich themselves by stealing a charity. The only question is WHEN they did it!”

Musk argued that allowing such actions to stand without review sets a dangerous precedent. “I will be filing an appeal with the Ninth Circuit, because creating a precedent to loot charities is incredibly destructive to charitable giving in America,” he wrote. He reiterated OpenAI’s founding purpose: “OpenAI was founded to benefit all of humanity.”

The jury’s unanimous advisory verdict found that Musk’s claims of breach of charitable trust and unjust enrichment were filed outside California’s three-year statute of limitations. U.S. District Judge Yvonne Gonzalez Rogers adopted the finding and dismissed the case. OpenAI hailed the outcome as vindication, while Musk’s legal team immediately signaled plans to appeal.

The trial, which featured testimony from Musk, Altman, Brockman, Microsoft CEO Satya Nadella, and others, exposed deep rifts in Silicon Valley over AI’s direction.

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Musk has long warned that profit-driven AI development, especially with closed models and powerful corporate ties, risks endangering humanity—contrasting it with OpenAI’s original open, safety-focused charter. OpenAI countered that the suit stemmed from business rivalry and that Musk himself had explored for-profit paths earlier.

Musk’s appeal could prolong the saga, potentially affecting OpenAI’s valuation (reportedly over $800 billion) and IPO ambitions. Supporters view his stance as defending nonprofit integrity, while critics see it as sour grapes from a competitor whose own xAI is racing in the AI arena.

Regardless of the legal outcome, the case has spotlighted critical questions about trust, governance, and mission drift in the rapidly evolving AI industry. Musk’s willingness to fight on suggests this chapter is far from closed, with broader implications for how charitable organizations—and the tech giants born from them—operate in the future.

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