New Sensors for Self-driving Cars

Soroush Salehian and Mina Rezk, of Aeva, a Silicon Valley start-up making new guidance systems for driverless vehicles. Credit Jason Henry for The New York Times
Soroush Salehian and Mina Rezk, of Aeva, a Silicon Valley start-up making new guidance systems for driverless vehicles. Credit Jason Henry for The New York Times
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New Sensors for Self-driving Cars

Soroush Salehian and Mina Rezk, of Aeva, a Silicon Valley start-up making new guidance systems for driverless vehicles. Credit Jason Henry for The New York Times
Soroush Salehian and Mina Rezk, of Aeva, a Silicon Valley start-up making new guidance systems for driverless vehicles. Credit Jason Henry for The New York Times

Soroush Salehian raised both arms and spun in circles as if celebrating a touchdown.

Across the room, perched on a tripod, a small black device monitored this little dance and streamed it to a nearby laptop. Mr. Salehian appeared as a collection of tiny colored dots, some red, some blue, some green. Each dot showed the precise distance to a particular point on his body, while the colors showed the speed of his movements. As his right arm spun forward, it turned blue. His left arm, spinning away, turned red.

“See how the arms are different?” said his business partner, Mina Rezk, pointing at the laptop. “It’s measuring different velocities.”

Messrs. Salehian and Rezk are the founders of a new Silicon Valley start-up called Aeva, and their small black device is designed for self-driving cars. The veterans of Apple’s secretive Special Projects Group aim to give these autonomous vehicles a more complete, detailed and reliable view of the world around them — something that is essential to their evolution.

Today’s driverless cars under development at companies like General Motors, Toyota, Uber and the Google spinoff Waymo track their surroundings using a wide variety of sensors, including cameras, radar, GPS antennas and lidar (short for “light detection and ranging”) devices that measure distances using pulses of light.

But there are gaps in the way these sensors operate, and combining their disparate streams of data is difficult. Aeva’s prototype — a breed of lidar that measures distances more accurately and also captures speed — aims to fill several of these sizable holes.

“I don’t even think of this as a new kind of lidar,” said Tarin Ziyaee, co-founder and chief technology officer at the self-driving taxi start-up Voyage, who has seen the Aeva prototype. “It’s a whole different animal.”

Founded in January and funded by the Silicon Valley venture capital firm Lux Capital, among others, Aeva joins a widespread effort to build more effective sensors for autonomous vehicles, a trend that extends from start-ups like Luminar, Echodyne and Metawave to established hardware makers like the German multinational Robert Bosch.

The company’s name, Aeva, is a play on “Eve,” the name of the robot in the Pixar movie “WALL-E.”

The market for autonomous vehicles will grow to $42 billion by 2025, according to research by the Boston Consulting Group. But for that to happen, the vehicles will need new and more powerful sensors. Today’s autonomous cars are ill prepared for high-speed driving, bad weather and other common situations.

The recent improvements in self-driving cars coincided with the improvements offered by new lidar sensors from a Silicon Valley company called Velodyne. These sensors gave cars a way of measuring distances to nearby vehicles, pedestrians and other objects. They also provided Google and other companies with a way of mapping urban roadways in three dimensions, so that cars will know exactly where they are at any given moment — something GPS cannot always provide.

But these lidar sensors have additional shortcomings. They can gather information only about objects that are relatively close to them, which limits how fast the cars can travel. Their measurements aren’t always detailed enough to distinguish one object from another. And when multiple driverless cars are close together, their signals can become garbled.

Other devices can pick up some of slack. Cameras are a better way of identifying pedestrians and street signs, for example, and radar works over longer distances. That’s why today’s self-driving cars track their surroundings through so many different sensors. But despite this wide array of hardware — which can cost hundreds of thousands of dollars per vehicle — even the best autonomous vehicles still have trouble in so many situations that humans can navigate with ease.

With their new sensor, Messrs. Salehian and Rezk are working to change that. Mr. Rezk is an engineer who designed optical hardware for Nikon, and presumably, he was among those who handled optical sensors for Apple’s driverless car project, though he and Mr. Salehian declined to say which “special project” they worked on at the company. They left Apple late last year.

Where current lidar sensors send out individual pulses, Aeva’s device sends out a continuous wave of light. By reading the way this far more complex signal bounces off surrounding objects, Mr. Rezk said, the device can capture a far more detailed image while also tracking velocity. You can think of it as a cross between lidar, which is so good at measuring depth, and radar, which is so good at measuring speed.

Mr. Rezk also said the device’s continuous wave would provide greater range and resolution than existing lidar devices, deal better with weather and highly reflective objects like bridge railings, and avoid interference with other optical sensors.

Cars will continue to use multiple kinds of sensors, in part because redundancy helps ensure that these cars are safe. But Aeva aims to give these cars a better view of the world from a smaller and less expensive set of sensors.

Researchers at the University of California, Berkeley, have built similar hardware, and companies like Velodyne and the start-ups Oryx Vision and Quanergy say they are exploring similar ideas. Like these efforts, the Aeva prototype is still under development, and the company plans to sell devices next year. But it shows how autonomous car sensors need to evolve — and that they are indeed evolving.

Ultimately, new sensors will allow cars to make better decisions.

The New York Times



OpenAI Starts Testing Ads in ChatGPT

The OpenAI logo is seen in this illustration taken May 20, 2024. (Reuters)
The OpenAI logo is seen in this illustration taken May 20, 2024. (Reuters)
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OpenAI Starts Testing Ads in ChatGPT

The OpenAI logo is seen in this illustration taken May 20, 2024. (Reuters)
The OpenAI logo is seen in this illustration taken May 20, 2024. (Reuters)

OpenAI has begun placing ads in the basic versions of its ChatGPT chatbot, a bet that users will not mind the interruptions as the company seeks revenue as its costs soar.

"The test will be for logged-in adult users on the Free and Go subscription tiers" in the United States, OpenAI said Monday. The Go subscription costs $8 in the United States.

Only a small percentage of its nearly one billion users pay for its premium subscription services, which will remain ad-free.

"Ads do not influence the answers ChatGPT gives you, and we keep your conversations with ChatGPT private from advertisers," the company said.

Since ChatGPT's launch in 2022, OpenAI's valuation has soared to $500 billion in funding rounds -- higher than any other private company. Some analysts expect it could go public with a trillion-dollar valuation.

But the ChatGPT maker burns through cash at a furious rate, mostly on the powerful computing required to deliver its services.

Its chief executive Sam Altman had long expressed his dislike for advertising, citing concerns that it could create distrust about ChatGPT's content.

His about-face garnered a jab from its rival Anthropic over the weekend, which made its advertising debut at the Super Bowl championship with commercials saying its Claude chatbot would stay ad-free.


Social Media ‘Addicting the Brains of Children,’ Plaintiff’s Lawyer Argues in Landmark Trial

Teenagers pose for a photo while holding smartphones in front of a Meta logo in this illustration taken September 11, 2025. (Reuters)
Teenagers pose for a photo while holding smartphones in front of a Meta logo in this illustration taken September 11, 2025. (Reuters)
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Social Media ‘Addicting the Brains of Children,’ Plaintiff’s Lawyer Argues in Landmark Trial

Teenagers pose for a photo while holding smartphones in front of a Meta logo in this illustration taken September 11, 2025. (Reuters)
Teenagers pose for a photo while holding smartphones in front of a Meta logo in this illustration taken September 11, 2025. (Reuters)

Comparing social media platforms to casinos and addictive drugs, lawyer Mark Lanier delivered opening statements Monday in a landmark trial in Los Angeles that seeks to hold Instagram owner Meta and Google's YouTube responsible for harms to children who use their products.

Instagram's parent company Meta and Google's YouTube face claims that their platforms addict children through deliberate design choices that keep kids glued to their screens. TikTok and Snap, which were originally named in the lawsuit, settled for undisclosed sums.

Jurors got their first glimpse into what will be a lengthy trial characterized by dueling narratives from the plaintiffs and the two remaining defendants.

Meta lawyer Paul Schmidt spoke of the disagreement within the scientific community over social media addiction, with some researchers believing it doesn’t exist, or that addiction is not the most appropriate way to describe heavy social media use.

‘Addicting the brains of children’

Lanier, the plaintiff's lawyer, delivered lively first remarks where he said the case will be as “easy as ABC” — which stands for “addicting the brains of children.” He said Meta and Google, “two of the richest corporations in history,” have “engineered addiction in children’s brains.”

He presented jurors with a slew of internal emails, documents and studies conducted by Meta and YouTube, as well as YouTube’s parent company, Google. He emphasized the findings of a study Meta conducted called “Project Myst” in which they surveyed 1,000 teens and their parents about their social media use.

The two major findings, Lanier said, were that Meta knew children who experienced “adverse events” like trauma and stress were particularly vulnerable for addiction; and that parental supervision and controls made little impact.

He also highlighted internal Google documents that likened some company products to a casino, and internal communication between Meta employees in which one person said Instagram is “like a drug” and they are “basically pushers.”

At the core of the Los Angeles case is a 20-year-old identified only by the initials “KGM,” whose case could determine how thousands of other, similar lawsuits against social media companies will play out. She and two other plaintiffs have been selected for bellwether trials — essentially test cases for both sides to see how their arguments play out before a jury.

Plaintiff grew up using YouTube, Instagram

KGM made a brief appearance after a break during Lanier’s statement and she will return to testify later in the trial. Lanier spent time describing KGM's childhood, focusing particularly on what her personality was like before she began using social media.

She started using YouTube at age 6 and Instagram at age 9, Lanier said. Before she graduated elementary school, she had posted 284 videos on YouTube.

The outcome of the trial could have profound effects on the companies' businesses and how they will handle children using their platforms.

Lanier said the companies’ lawyers will “try to blame the little girl and her parents for the trap they built,” referencing the plaintiff. She was a minor when she said she became addicted to social media, which she claims had a detrimental impact on her mental health.

Lanier said that despite the public position of Meta and YouTube being that they work to protect children, their internal documents show an entirely different position, with explicit references to young children being listed as their target audiences.

The attorney also drew comparisons between the social media companies and tobacco firms, citing internal communication between Meta employees who were concerned about the company’s lack of proactive action about the potential harm their platforms can have on children and teens.

“For a teenager, social validation is survival,” Lanier said. The defendants “engineered a feature that caters to a minor’s craving for social validation,” he added, speaking about “like” buttons and similar features.

Meta pushes back

In his opening statement representing Meta, Schmidt said the core question in the case is whether the platforms were a substantial factor in KGM’s mental health struggles. He spent much of his time going through the plaintiff’s health records, emphasizing that she had experienced many difficult circumstances in her childhood, including emotional abuse, body image issues and bullying.

Schmidt presented a clip from a video deposition from one of KGM‘s mental health providers, Dr. Thomas Suberman, who said social media was “not the through-line of what I recall being her main issues,” adding that her struggles seemed to largely stem from interpersonal conflicts and relationships.

He painted a picture — with KGM’s own text messages and testimony pointing to a volatile home life — of a particularly troubled relationship with her mother.

Schmidt acknowledged that many mental health professionals do believe social media addiction can exist, but said three of KGM’s providers — all of whom believe in the form of addiction — have never diagnosed her with it, or treated her for it.

Schmidt stressed to the jurors that the case is not about whether social media is a good thing or whether teens spend too much time on their phones or whether the jurors like or dislike Meta, but whether social media was a substantial factor in KGM’s mental health struggles.

A reckoning for social media and youth harms

A slew of trials beginning this year seek to hold social media companies responsible for harming children's mental well-being. Executives, including Meta CEO Mark Zuckerberg, are expected to testify at the Los Angeles trial, which will last six to eight weeks.

Experts have drawn similarities to the Big Tobacco trials that led to a 1998 settlement requiring cigarette companies to pay billions in health care costs and restrict marketing targeting minors.

A separate trial in New Mexico, meanwhile, also kicked off with opening statements on Monday. In that trial, Meta is accused of failing to protect young users from sexual exploitation, following an undercover online investigation. Attorney General Raúl Torrez in late 2023 sued Meta and Zuckerberg, who was later dropped from the suit.

A federal bellwether trial beginning in June in Oakland, California, will be the first to represent school districts that have sued social media platforms over harms to children.

In addition, more than 40 state attorneys general have filed lawsuits against Meta, claiming it is harming young people and contributing to the youth mental health crisis by deliberately designing features on Instagram and Facebook that addict children to its platforms. The majority of cases filed their lawsuits in federal court, but some sued in their respective states.

TikTok also faces similar lawsuits in more than a dozen states.


AI No Better Than Other Methods for Patients Seeking Medical Advice, Study Shows

AI (Artificial Intelligence) letters and a robot hand are placed on a computer motherboard in this illustration created on June 23, 2023. (Reuters)
AI (Artificial Intelligence) letters and a robot hand are placed on a computer motherboard in this illustration created on June 23, 2023. (Reuters)
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AI No Better Than Other Methods for Patients Seeking Medical Advice, Study Shows

AI (Artificial Intelligence) letters and a robot hand are placed on a computer motherboard in this illustration created on June 23, 2023. (Reuters)
AI (Artificial Intelligence) letters and a robot hand are placed on a computer motherboard in this illustration created on June 23, 2023. (Reuters)

Asking AI about medical symptoms does not help patients make better decisions about their health than other methods, such as a standard internet search, according to a new study published in Nature Medicine.

The authors said the study was important as people were increasingly turning to AI and chatbots for advice on their health, but without evidence that this was necessarily the best and safest approach.

Researchers led by the University of Oxford’s Internet Institute worked alongside a group of doctors to draw up 10 different medical scenarios, ranging from a common cold to a life-threatening hemorrhage causing bleeding on the brain.

When tested without human participants, three large-language models – Open AI's Chat GPT-4o, ‌Meta's Llama ‌3 and Cohere's Command R+ – identified the conditions in ‌94.9% ⁠of cases, ‌and chose the correct course of action, like calling an ambulance or going to the doctor, in an average of 56.3% of cases. The companies did not respond to requests for comment.

'HUGE GAP' BETWEEN AI'S POTENTIAL AND ACTUAL PERFORMANCE

The researchers then recruited 1,298 participants in Britain to either use AI, or their usual resources like an internet search, or their experience, or the National Health Service website to ⁠investigate the symptoms and decide their next step.

When the participants did this, relevant conditions were identified in ‌less than 34.5% of cases, and the right ‍course of action was given in ‍less than 44.2%, no better than the control group using more traditional ‍tools.

Adam Mahdi, co-author of the paper and associate professor at Oxford, said the study showed the “huge gap” between the potential of AI and the pitfalls when it was used by people.

“The knowledge may be in those bots; however, this knowledge doesn’t always translate when interacting with humans,” he said, meaning that more work was needed to identify why this was happening.

HUMANS OFTEN GIVING INCOMPLETE INFORMATION

The ⁠team studied around 30 of the interactions in detail, and concluded that often humans were providing incomplete or wrong information, but the LLMs were also sometimes generating misleading or incorrect responses.

For example, one patient reporting the symptoms of a subarachnoid hemorrhage – a life-threatening condition causing bleeding on the brain – was correctly told by AI to go to hospital after describing a stiff neck, light sensitivity and the "worst headache ever". The other described the same symptoms but a "terrible" headache, and was told to lie down in a darkened room.

The team now plans a similar study in different countries and languages, and over time, to test if that impacts AI’s performance.

The ‌study was supported by the data company Prolific, the German non-profit Dieter Schwarz Stiftung, and the UK and US governments.