Elon Musk’s Tesla unveils robotaxi with ‘black box’ artificial intelligence technology amid safety concerns

Tesla aimed to dazzle investors Thursday night with the unveiling of its long-awaited “robotaxis,” a potential milestone after a decade of Elon Musk’s unfulfilled promises to deliver self-driving vehicles.

The automaker unveiled a prototype called the “Cybercab” — which Musk described as capable of “fully supervised self-driving” — instead of a road-ready driverless taxi.

“There’s no steering wheel or pedals, so I hope this goes well,” the founder said as 20 of the cars drove around without people inside the event at Warner Brother Studios. “We will find out!

He said he expects the robotaxis to be out “before 2027” at a cost of under $30,000, he added.

Convincing regulators and passengers of the vehicle’s safety could be much more difficult and take much longer — while its main competitors, such as Alphabet’s Waymo, are expanding the fleet of robots already operating in cities. chosen today.

Elon Musk’s Tesla may have a hard time convincing regulators and passengers of the vehicle’s safety. Getty Images

Tesla has so far taken a different technology path than all of its main self-driving rivals — one with potentially higher rewards but also higher risks for its business and passengers, according to Reuters interviews with more than a dozen managers, consultants and academics. specializing in self-driving technology and three former Tesla autonomous vehicle engineers.

Tesla’s strategy relies solely on a combination of “computer vision,” which aims to use cameras the way humans use their eyes, with an artificial intelligence technology called end-to-end machine learning that instantly translates images in management decisions.

That technology already supports its “Full Self-Driving” driver assistance feature that, despite its name, cannot be safely used without a human driver. Musk has said that Tesla is using the same approach to develop fully autonomous robotaxis.

Tesla’s competitors — including Waymo, Amazon’s Zoox, General Motors’ Cruise and a host of Chinese firms — use the same technology, but typically layer redundant systems and sensors like radar, lidar and sophisticated maps to ensure safety. and gain regulatory approval for their driverless vehicles.

Tesla’s strategy is simpler and much cheaper, but it has two critical weaknesses, industry executives, autonomous vehicle experts and one of Tesla’s engineers told Reuters. Without the layered technologies used by its peers, Tesla’s system struggles more with so-called “edge cases” — rare driving scenarios that self-driving systems and their human engineers struggle to predict.

A Tesla Model 3 vehicle drives with FSD. Reuters

Another key challenge: End-to-end AI technology is a “black box,” the Tesla engineer said, making it “almost impossible” to “see what went wrong when it misbehaves and causes an accident.” The inability to accurately identify such failures, he said, makes it difficult to defend against them.

Tesla did not respond to a request for comment on its technology.

Nvidia founder and CEO Jensen Huang used the same “black box” description in an interview to describe the weaknesses of the end-to-end technology, without specifically addressing Tesla’s system. End-to-end AI involves training a computer to make decisions directly from raw data, without intermediate steps that require additional engineering or programming.

Nvidia, the world’s leading maker of AI computer chips, also uses the end-to-end technology in autonomous driving systems it is developing and plans to sell to automakers. But Nvidia, Huang told Reuters, combines that approach with more conventional computing systems and additional sensors such as radar and lidar.

End-to-end technology usually “but not always” makes the best driving decisions, Huang said, which is why Nvidia takes a more conservative approach. “We have to build the future step by step,” he said. “We cannot go directly into the future. It is very uncertain.â€

Nvidia, the world’s leading maker of AI computer chips, also uses the end-to-end technology in autonomous driving systems it is developing and plans to sell to automakers. CEO Jensen Huang, above. Getty Images

Robot pilot

Tesla’s ability to offer robotaxis has taken on added importance this year as its sales and profits have fallen due to softening demand for electric vehicles globally and stiff competition from growing Chinese electric vehicle makers.

If Tesla can overcome the technical challenges of its autonomous strategy, the payoff could be huge. While competitors like Waymo already have robotaxis on the road, they are operating much more expensive vehicles in relatively small, fully mapped areas.

Tesla aims to sell affordable robotaxis that can drive itself anywhere.

Musk has a long history of making bold promises about self-driving cars. In 2016, he predicted that drivers would be able to summon their vehicles from across the country within two years. In 2019, Musk predicted that Tesla would produce operational robotaxis by 2020.

Tesla’s ability to offer robotaxis has taken on added importance this year as its sales and profits have fallen due to softening demand for electric vehicles globally. Reuters

The announcement of this week’s robotax discovery came on April 5, the day Reuters exclusively reported that Tesla had abandoned plans to build a $25,000 electric vehicle for the masses known informally as the Model 2, initially sending Tesla shares lower. Musk responded by posting later that day on his social media platform X: “Robotaxi to be unveiled on 8/8,” sparking intense investor speculation. Tesla later postponed the event until this week.

That April day marked a fundamental shift in Musk’s stated priorities. He had previously promised to make Tesla a Toyota-sized EV behemoth, an expectation that fueled Tesla’s share price surge, making it the world’s most valuable automaker. Now he vowed to dominate self-driving technology.

Unexpected cost-cutting measures followed, including massive layoffs, as Musk diverted investment from EV production priorities such as battery development, gigabit transmission and expanding the automaker’s Supercharger network.

The retreat from mass-market EVs only intensified investor pressure on Tesla’s autonomous vehicle development. Musk bowed to the scrutiny, saying in April that anyone who doubts Tesla will “solve autonomy” should not invest in the company.

Nicholas Mersch, portfolio manager at Purpose Investments, a Tesla investor, said Musk “has a lot of convincing to do.”

Still, Mersch called Musk’s autonomy strategy a “really bold bet” with a potentially huge payoff, even if it takes much longer for Tesla to crack the code. “You have to keep in mind the big picture, in terms of how much innovation is going on” at Tesla, he said. “I wouldn’t discount them.”

Driven by data

For now, unlike its robotaxi competitors, Tesla only offers semi-autonomous solutions in its Autopilot and Full Self-Driving features. The naming and marketing of these systems has sparked investigations and lawsuits over whether Tesla put drivers at risk by overstating the capabilities of its self-driving cars.

A National Highway Traffic Safety Administration (NHTSA) investigation released in April found that 542 crashes, including 14 fatalities, occurred in Tesla vehicles with Autopilot or FSD engaged between January 2018 and August 2023.

The scene of a Tesla crash in Mountain View, California, in 2018. AP

However, deploying Autopilot and FSD in high-volume models gives Tesla a distinct competitive advantage: A vast trove of data, collected by cameras in millions of vehicles, that it can analyze and use to develop self-driving technology .

Two of Tesla’s former engineers said the relatively low cost of its technology enables a massive scale of its data collection, compared to the relatively small fleets of competitors such as Waymo. One of the engineers said Tesla’s high-resolution cameras cost much less than lidar and could eventually allow the automaker to produce fully autonomous vehicles that customers can afford.

Lidar uses lasers to produce three-dimensional images of a vehicle’s surroundings as it navigates around obstacles.

Speaking to analysts and investors this summer, Musk boasted of the “exponential” improvement and predicted that Tesla could achieve unattended driving “by the end of this year,” adding that he would be “shocked if I can’t let’s do it next year.” €

Sasha Ostojic – a former driverless car engineer and software development executive at Nvidia, Cruise and Zoox – said he believes Tesla will need at least “three more years” just to reach the level of autonomous driving that Waymo achieves today. Ostojic now advises a Palo Alto venture capital firm, Playground Global, on technology investments.

“I don’t see Tesla converging to true ‘mindless, mindless’ autonomous driving,” he said, “in the timeframes that Elon Musk has been promising.”

By postal wires

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