Tesla Autopilot safety probe by federal vehicle regulators nears completion

Published

2 years ago

August 25, 2023

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A multi-year investigation into the safety of Tesla’s driver assistance systems by the National Highway Traffic Safety Administration, or NHTSA, is drawing near a close.

Reuters’ David Shepardson first reported on the latest developments Thursday, citing NHTSA acting administrator Ann Carlson. CNBC confirmed the report with the federal vehicle safety regulators.

A spokesperson for NHTSA declined to disclose further details, but told CNBC in an e-mail, “We confirm the comments to Reuters,” and “NHTSA’s Tesla investigations remain open, and the agency generally does not comment on open investigations.”

The agency initiated a safety probe of Tesla’s driver assistance systems — now marketed in the U.S. as Autopilot, Full Self-Driving and FSD Beta options — in 2021 after it identified a string of crashes in which Tesla drivers, thought to be using the company’s driver assistance systems, crashed into first responders’ stationary vehicles.

Despite their names, none of Tesla’s driver assistance features make their cars autonomous. Tesla cars cannot function as robotaxis like those operated by GM-owned Cruise or Alphabet‘s Waymo. Instead, Tesla vehicles require a human driver at the wheel, ready to steer or brake at any time. Tesla’s standard Autopilot and premium Full Self-Driving systems only control braking, steering and acceleration in limited circumstances.

Tesla CEO Elon Musk — who also owns and runs the social network X (formerly Twitter) — often implies Tesla cars are autonomous. For example, on July 23, an ex-Tesla employee who led the company’s AI software engineering posted on the social network about ChatGPT, and how much that generative AI tool impressed his parents when he showed it to them for the first time. Musk responded: “Same happens with Tesla FSD. I forget that most people on Earth have no idea cars can drive themselves.”

In its owners’ manuals, Tesla tells drivers who use Autopilot or FSD: “Keep your hands on the steering wheel at all times and be mindful of road conditions, surrounding traffic, and other road users (such as pedestrians and cyclists). Always be prepared to take immediate action. Failure to follow these instructions could cause damage, serious injury or death.”

The company’s cars feature a driver monitoring system which employs in-cabin cameras and sensors in the steering wheel to detect whether a driver is paying adequate attention to the road and driving task. The system will “nag” drivers with a chime and message on the car’s touchscreen to pay attention and put their hands on the wheel. But it’s not clear that this is a strong enough system to ensure safe use of Tesla’s driver assistance features.

Tesla has previously conducted voluntary recalls of its cars due to other problems with Autopilot and FSD Beta and promised to deliver over-the-air software updates that would remedy the issues. But in July, the agency required Elon Musk’s automaker to send more extensive data on the performance of their driver assistance systems to evaluate as part of its Autopilot safety investigations.

NHTSA publishes data regularly on car crashes in the U.S. that involved advanced driver assistance systems like Tesla Autopilot, Full Self Driving or FSD Beta, dubbed “level 2” under industry standards from SAE International.

The latest data from that Standing General Order crash report says there have been at least 26 incidents involving Tesla cars equipped with level 2 systems resulting in fatalities from August 1, 2019 through mid-July this year. In 23 of these incidents, the agency report says, Tesla’s driver assistance features were in use within 30 seconds of the collision. In three incidents, it’s not known whether these features were used.

Ford is the only other automaker reporting a fatal collision that involved one of its vehicles equipped with level 2 driver assistance. It was not known if the system was engaged preceding that crash, according to the NHTSA SGO report.

Tesla did not respond to a request for comment.

Technology

Spotify stock falls on revenue miss, lackluster guidance

Published

6 hours ago

July 29, 2025

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Spotify stock falls on revenue miss, lackluster guidance

Thomas Fuller | Lightrocket | Getty Images

Spotify shares dropped about 4% Tuesday after the music streaming platform fell short of Wall Street’s expectations and posted weak guidance for the current quarter.

Here’s how the company did versus LSEG estimates:

Loss: Loss of .42 euros vs earnings of 1.90 euros per share expected
Revenue: 4.19 billion euros vs. 4.26 billion expected

The Sweden-based music platform’s revenues rose 10% from about 3.81 billion euros in the year-ago period. The company posted a net loss of 86 million euros, or a loss of .42 euros per share, down from net income of 225 million euros, or 1.10 euros per share a year ago.

Third-quarter guidance came up short of Wall Street’s forecast.

The company expects revenues to reach 4.2 billion euros, compared to a 4.47 billion euro estimate from StreetAccount. Spotify said the forecast accounts for a 490-basis-point headwind due to foreign exchange rates.

Samsung backs South Korean AI chip startup Rebellions ahead of IPO

Published

9 hours ago

July 29, 2025

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The Rebel-Quad is the second-generation product from Rebellions and is made up of four Rebel AI chips. Rebellions, a South Korean firm, is looking to rival companies like Nvidia in AI chips.

Rebellions

South Korean artificial intelligence chip startup Rebellions has raised money from tech giant Samsung and is targeting a funding round of up to $200 million ahead of a public listing, the company’s management told CNBC on Tuesday.

Last year, Rebellions merged with another startup in South Korea called Sapeon, creating a firm that is being positioned as one of the country’s promising rivals to Nvidia.

Rebellions is currently raising money and is targeting funding of between $150 million and $200 million, Sungkyue Shin, chief financial officer of the startup, told CNBC on Tuesday.

Samsung’s investment in Rebellions last week was part of that, Shin said, though he declined to say how much the tech giant poured in.

Since its founding in 2020, Rebellions has raised $220 million, Shin added.

The current funding round is ongoing and Shin said Rebellions is talking to its current investors as well as investors in Korea and globally to participate in the capital raise. Rebellions has some big investors, including South Korean chip giant SK Hynix, telecommunication firms SK Telecom and Korea Telecom, and Saudi Arabian oil giant Aramco.

AI chip startup Rebellions looks to raise up to $200 million ahead of IPO

Rebellions was last valued at $1 billion. Shin said the current round of funding would push the valuation over $1 billion but declined to give specific figure.

Rebellions is aiming for an initial public offering once this funding round has closed.

“Our master plan is going public,” Shin said.

Rebellions designs chips that are focused on AI inferencing rather than training. Inferencing is when a pre-trained AI model interprets live data to come up with a result, much like the answers that are produced by popular chatbots.

With the backing of major South Korean firms and investors, Rebellions is hoping to make a global play where it will look to challenge Nvidia and AMD as well as a slew of other startups in the inferencing space.

Samsung collaboration

Rebellions has been working with Samsung to bring its second-generation chip, Rebel, to market. Samsung owns a chip manufacturing business, also known as foundry. Four Rebel chips are put together to make the Rebel-Quad, the product that Rebellions will eventually sell. A Rebellions spokesperson said the chip will be launched later this year.

The funding will partly go toward Rebellions’ product development. Rebellions is currently testing its chip which will eventually be produced on a larger scale by Samsung.

“Initial results have been very promising,” Sunghyun Park, CEO of Rebellions, told CNBC on Tuesday.

South Korean AI startup Rebellions says tariffs could delay IPO by 'a little bit'

Park said Samsung invested in Rebellions partly because of the the good results that the chip has so far produced.

Samsung is manufacturing Rebellions’ semiconductor using its 4 nanometer process, which is among the leading-edge chipmaking nodes. For comparison, Nvidia’s current Blackwell chips use the 4 nanometer process from Taiwan Semiconductor Manufacturing Co. Rebellions will also use Samsung’s high bandwidth memory, known as HBM3e. This type of memory is stacked and is required to handle large data processing loads.

That could turn out to be a strategic win for Samsung, which is a very distant second to TSMC in terms of market share in the foundry business. Samsung has been looking to boost its chipmaking division. Samsung Electronics recently entered into a $16.5 billion contract for supplying semiconductors to Tesla.

If Rebellions manages to find a large customer base, this could give Samsung a major customer for its foundry business.

Technology

Europe sets its sights on multi-billion-euro gigawatt factories as it plays catch-up on AI

Published

12 hours ago

July 29, 2025

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Europe sets its sights on multi-billion-euro gigawatt factories as it plays catch-up on AI

Data storage tapes are stored at the National Energy Research Scientific Computing Center (NERSC) facility at the Lawrence Berkeley National Laboratory, which will house the U.S. supercomputer to be powered by Nvidia’s forthcoming Vera Rubin chips, in Berkeley, California, U.S. May 29, 2025.

Manuel Orbegozo | Reuters

Europe is setting its sights on gigawatt factories in a bid to bolster its lagging artificial intelligence industry and meet the challenges of a rapidly-changing sector.

Buzz around the concept of factories that industrialize manufacturing AI has gained ground in recent months, particularly as Nvidia CEO Jensen Huang stressed the importance of the infrastructure at a June event. Huang hailed a new “industrial revolution” at the GTC conference in Paris, France, and said his firm was working to help countries build revenue-generating AI factories through partnerships in France, Italy and the U.K.

For its part, the European Union describes the factories as a “dynamic ecosystem” that brings together computing power, data and talent to create AI models and applications.

The bloc has long been a laggard behind the U.S. and China in the race to scale up artificial intelligence. With 27 members in the union, the region is slower to act when it comes to agreeing new legislation. Higher energy costs, permitting delays and a grid in dire need of modernization can also hamper developments.

Henna Virkkunen, the European Commission’s executive vice president for tech sovereignty, told CNBC that the bloc’s goal is to bring together high quality data sets, computing capacity and researchers, all in one place.

“We have, for example, 30% more researchers per capita than the U.S. has, focused on AI. Also we have around 7,000 startups [that] are developing AI, but the main obstacle for them is that they have very limited computing capacity. And that’s why we decided that, together with our member states, we are investing in this very crucial infrastructure,” she said.

These are very big investments because they are four times more powerful when it comes to computing capacities than the biggest AI factories.

Henna Virkkunen

European Commission’s executive vice president for tech sovereignty

“We have everything what is needed to be competitive in this sector, but at the same time we want to build up our technological sovereignty and our competitiveness.”

So far, the EU has put up 10 billion euros ($11.8 billion) in funding to set up 13 AI factories and 20 billion euros as a starting point for investment in the gigafactories, marking what it says is the “largest public investment in AI in the world.” The bloc has already received 76 expressions of interest in the gigafactories from 16 member states across 60 sites, Virkkunen said.

The call for interest in gigafactories was “overwhelming,” going far beyond the bloc’s expectations, Virkkunen noted. However, in order for the factories to make a noteworthy addition to Europe’s computing capacity, significantly more investment will be required from the private sector to fund the expensive infrastructure.

‘Intelligence revolution’

The EU describes the facilities as a “one-stop shop” for AI firms. They’re intended to mirror the process carried out in industrial factories, which transform raw materials into goods and services. With an AI factory, raw data goes into the input, and advanced AI products are the expected outcome.

It’s essentially a data center with additional infrastructure related to how the technology will be adopted, according to Andre Kukhnin, equity research analyst at UBS.

“The idea is to create GPU [graphics processing units] capacity, so to basically build data centers with GPUs that can train models and run inference… and then to create an infrastructure that allows you to make this accessible to SMEs and parties that would not be able to just go and build their own,” Kukhnin said.

How the facility will be used is key to its designation as an AI factory, adds Martin Wilkie, research analyst at Citi.

“You’re creating a platform by having these chips that have insane levels of compute capacity,” he said. “And if you’ve attached it to a grid that is able to get the power to actually use them to full capacity, then the world is at your feet. You have this enormous ability to do something, but what the success of it is, will be defined by what you use it for.”

Telecommunications firm Telenor is already exploring possible use cases for such facilities with the launch of its AI factory in Norway in November last year. The company currently has a small cluster of GPUs up and running, as it looks to test the market before scaling up.

Telenor’s Chief Innovation Officer and Head of the AI Factory Kaaren Hilsen and EVP Infrastructure Jannicke Hilland in front of a Nvidia rack at the firm’s AI factory

Telenor

“The journey started with a belief — Nvidia had a belief that every country needs to produce its own intelligence,” Telenor’s Chief Innovation Officer and Head of the AI Factory Kaaren Hilsen told CNBC.

Hilsen stressed that data sovereignty is key. “If you want to use AI to innovate and to make business more efficient, then you’re potentially putting business critical and business sensitive information into these AI models,” she said.

The company is working with BabelSpeak, which Hilsen described as a Norwegian version of ChatGPT. The technology translates sensitive dialogues, such as its pilot with the border police who can’t use public translation services because of security issues.

We’re experiencing an “intelligence revolution” whereby “sovereign AI factories can really help advance society,” Hilsen said.

Billion-euro investments

Virkkunen said the region’s first AI factory will be operational in coming weeks, with one of the biggest projects launching in Munich, Germany in the first days of September. It’s a different story for the gigafactories.

“These are very big investments because they are four times more powerful when it comes to computing capacities than the biggest AI factories, and it means billions in investments. Each of these need three to five billion [euros] in investment,” the commissioner said, adding that the bloc will look to set up a consortium of partners and then officially open a call for investment later this year.

Bertin Martens, senior research fellow at Bruegel, questioned why such investments needed to subsidized by government funds.

“We don’t know yet how much private investment has been proposed as a complement to the taxpayer subsidy, and what capacity and how big these factories are. This is still very much unclear at this stage, so it’s very hard to say how much this will add in terms of computing capacity,” he said.

Power consumption is also a key issue. Martens noted that building an AI gigafactory may take one to two years — but building a power generation of that size requires much more time.

“If you want to build a state-of-the-art gigafactory with hundreds of thousands of Nvidia chips, you have to count on the power consumption of at least one gigawatt for one of those factories. Whether there’s enough space in Europe’s electricity grid in all of these countries to create those factories remains to be seen… this will require major investment in power regeneration capacity,” he told CNBC.

UBS forecasts that the current installed global data center capacity of 85 GW will double due to soaring demand. Based on the EU’s 20-billion-euro investment and the plan for each factory to run 100,000 advanced processors, UBS estimates each factory could be around 100-150 MW with a total capacity for all of the facilities of around 1.5-2 GW.

That could add around 15% to Europe’s total capacity — a sizeable boost, even when compared to the U.S., which currently owns around a third of global capacity, according to the data.

Following the announcement of the EU-U.S. trade framework, EU chief Ursula von der Leyen said Sunday that U.S. AI chips will help power the bloc’s AI gigafactories in a bid to help the States “maintain their technological edge.”

“One could argue that it’s relatively easy, provided you have the money. It’s relatively easy to buy the chips from Nvidia and to create these hardware factories, but to make it run and to make it economically viable is a completely different question,” Martens told CNBC.

He said that the EU will likely have to start at a smaller scale, as the region is unable to immediately build its own frontier models in AI because of their expense.

“I think in time, Europe can gradually build up its infrastructure and its business models around AI to reach that stage, but that will not happen immediately,” Martens said.