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Uber patent filing reveals AI project that could deny drunks of a ride

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A recently-published patent application from Uber has revealed that the ride-sharing company is planning on using artificial intelligence to identify a passenger’s behavioral state, including being drunk, before being picked up. With this technology, Uber is hoping to better tailor its ride-sharing options for its ever-growing user base.

The patent, titled “Predicting user state using machine learning” describes a system that uses machine learning to study the usual behavior of Uber users. These behaviors include several factors, including location, the precision of users’ clicks on the app’s buttons, spelling accuracy when communicating with drivers, average walking speed, and how long it takes passengers to request for a ride. The usual time when users hail an Uber will also be included in the system.

According to Uber’s patent application:

“The user state model is trained to predict user state using past features in conjunction with previously-identified unusual user states. That is, the user state prediction module detects whether the user has input data in a way that is unusual for that particular user and/or in a way differing from normal user behavior that is similar to the differences for other users having unusual behavior.”

Thus, if an intoxicated user hails a ride while walking and typing clumsily, the ride-hailing company’s AI system would be able to make an assumption that the user is less than sober. Once the system detects that a user is likely drunk, it would “alter the parameters” of its service in order to match the passenger with drivers who have relevant experience and training. Based on the passenger’s state, Uber might also restrict a drunk user’s access to its shared ride services.

“the user may not be matched with any provider, or limited to providers with experience or training with users having an unusual state” reveals the patent application.

 

The patent is authored by members of Uber’s Trust & Safety Team, who are tasked with making the company’s service and products safer. Overall, the system stands to benefit both passengers and drivers, considering that intoxication has proven to be a problem for Uber so far. According to an investigation from CNN, at least 103 Uber drivers have been accused of abusing intoxicated passengers over the past four years. Uber drivers have also reported instances where they got assaulted by passengers who were drunk.

The use of AI systems is steadily gaining ground. In China alone, SenseTime, a company involved in mainstream smartphone applications such as AR filters, has been working with the Chinese government in developing AI solutions that are capable of matching footage from crime scenes to criminal database photos. After a funding round led by Chinese e-commerce giant Alibaba earlier this year, SenseTime’s total valuation rose to over $4.5 billion, making it one of the most valuable AI startups in the industry.

In the United States, AI is starting to get embraced by the US military, with self-driving vehicles and AI-powered weapons being in development. Just recently, Google saw protests from staff over the company’s participation in the Pentagon’s artificial intelligence initiative, Project Maven. According to reports, Google’s AI technology has been used to improve military drones’ image-processing capabilities, which has been helping the military fight threats in several regions such as the Middle East. Google, for its part, stated that its work with the Pentagon has been “mundane,” and that the technology it provided was limited only to non-offensive uses.  

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Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Elon Musk’s Boring Company opens Vegas Loop’s newest station

The Fontainebleau is the latest resort on the Las Vegas Strip to embrace the tunneling startup’s underground transportation system.

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Credit: The Boring Company/X

Elon Musk’s tunneling startup, The Boring Company, has welcomed its newest Vegas Loop station at the Fontainebleau Las Vegas.

The Fontainebleau is the latest resort on the Las Vegas Strip to embrace the tunneling startup’s underground transportation system.

Fontainebleau Loop station

The new Vegas Loop station is located on level V-1 of the Fontainebleau’s south valet area, as noted in a report from the Las Vegas Review-Journal. According to the resort, guests will be able to travel free of charge to the stations serving the Las Vegas Convention Center, as well as to Loop stations in Encore and Westgate.

The Fontainebleau station connects to the Riviera Station, which is located in the northwest parking lot of the convention center’s West Hall. From there, passengers will be able to access the greater Vegas Loop.

Vegas Loop expansion

In December, The Boring Company began offering Vegas Loop rides to and from Harry Reid International Airport. Those trips include a limited above-ground segment, following approval from the Nevada Transportation Authority to allow surface street travel tied to Loop operations.

Under the approval, airport rides are limited to no more than four miles of surface street travel, and each trip must include a tunnel segment. The Vegas Loop currently includes more than 10 miles of tunnels. From this number, about four miles of tunnels are operational.

The Boring Company President Steve Davis previously told the Review-Journal that the University Center Loop segment, which is currently under construction, is expected to open in the first quarter of 2026. That extension would allow Loop vehicles to travel beneath Paradise Road between the convention center and the airport, with a planned station located just north of Tropicana Avenue.

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Tesla leases new 108k-sq ft R&D facility near Fremont Factory

The lease adds to Tesla’s presence near its primary California manufacturing hub as the company continues investing in autonomy and artificial intelligence.

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Credit: Tesla

Tesla has expanded its footprint near its Fremont Factory by leasing a 108,000-square-foot R&D facility in the East Bay. 

The lease adds to Tesla’s presence near its primary California manufacturing hub as the company continues investing in autonomy and artificial intelligence.

A new Fremont lease

Tesla will occupy the entire building at 45401 Research Ave. in Fremont, as per real estate services firm Colliers. The transaction stands as the second-largest R&D lease of the fourth quarter, trailing only a roughly 115,000-square-foot transaction by Figure AI in San Jose.

As noted in a Silicon Valley Business Journal report, Tesla’s new Fremont lease was completed with landlord Lincoln Property Co., which owns the facility. Colliers stated that Tesla’s Fremont expansion reflects continued demand from established technology companies that are seeking space for engineering, testing, and specialized manufacturing.

Tesla has not disclosed which of its business units will be occupying the building, though Colliers has described the property as suitable for office and R&D functions. Tesla has not issued a comment about its new Fremont lease as of writing.

AI investments

Silicon Valley remains a key region for automakers as vehicles increasingly rely on software, artificial intelligence, and advanced electronics. Erin Keating, senior director of economics and industry insights at Cox Automotive, has stated that Tesla is among the most aggressive auto companies when it comes to software-driven vehicle development.

Other automakers have also expanded their presence in the area. Rivian operates an autonomy and core technology hub in Palo Alto, while GM maintains an AI center of excellence in Mountain View. Toyota is also relocating its software and autonomy unit to a newly upgraded property in Santa Clara.

Despite these expansions, Colliers has noted that Silicon Valley posted nearly 444,000 square feet of net occupancy losses in Q4 2025, pushing overall vacancy to 11.2%.

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Tesla winter weather test: How long does it take to melt 8 inches of snow?

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Credit: Teslarati

In Pennsylvania, we got between 10 and 12 inches of snow over the weekend as a nasty Winter storm ripped through a large portion of the country, bringing snow to some areas and nasty ice storms to others.

I have had a Model Y Performance for the week courtesy of Tesla, which got the car to me last Monday. Today was my last full day with it before I take it back to my local showroom, and with all the accumulation on it, I decided to run a cool little experiment: How long would it take for Tesla’s Defrost feature to melt 8 inches of snow?

Tesla Model Y Performance set for new market entrance in Q1

Tesla’s Defrost feature is one of the best and most underrated that the car has in its arsenal. While every car out there has a defrost setting, Tesla’s can be activated through the Smartphone App and is one of the better-performing systems in my opinion.

It has come in handy a lot through the Fall and Winter, helping clear up my windshield more efficiently while also clearing up more of the front glass than other cars I’ve owned.

The test was simple: don’t touch any of the ice or snow with my ice scraper, and let the car do all the work, no matter how long it took. Of course, it would be quicker to just clear the ice off manually, but I really wanted to see how long it would take.

Tesla Model Y heat pump takes on Model S resistive heating in defrosting showdown

Observations

I started this test at around 10:30 a.m. It was still pretty cloudy and cold out, and I knew the latter portion of the test would get some help from the Sun as it was expected to come out around noon, maybe a little bit after.

I cranked it up and set my iPhone up on a tripod, and activated the Time Lapse feature in the Camera settings.

The rest of the test was sitting and waiting.

It didn’t take long to see some difference. In fact, by the 20-minute mark, there was some notable melting of snow and ice along the sides of the windshield near the A Pillar.

However, this test was not one that was “efficient” in any manner; it took about three hours and 40 minutes to get the snow to a point where I would feel comfortable driving out in public. In no way would I do this normally; I simply wanted to see how it would do with a massive accumulation of snow.

It did well, but in the future, I’ll stick to clearing it off manually and using the Defrost setting for clearing up some ice before the gym in the morning.

Check out the video of the test below:

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