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.
Elon Musk
Tesla Semi finally has an FSD timeline and it’s waiting on the Cybercab
Elon Musk told investors Semi self-driving should start working by early 2027, per today’s earnings.
During Wednesday’s’ Tesla Q2 earnings call, an analyst asked Elon Musk when Tesla would look at autonomy for the Semi. His answer set a real timeline for the first time, noting that self-driving on the Tesla Semi is expected to start working “around the end of this year or early next year”.
Musk framed the delay as a matter of priority, not capability. Tesla’s self-driving team is currently focused on Model 3, Model Y, and Cybercab, the vehicles that make up the overwhelming majority of Tesla’s fleet. Since Semi trucks on the road remain a small fraction of that total even after the recent Nevada factory ramp, Musk said it made more sense to keep the software team’s attention on what he called “the march of nines of safety” for the higher volume vehicles first. Autonomous Semi development is “taking a bit of a backseat for the next six months or so,” he said, before adding that it “will definitely be working next year and in time for the scale-up to high production of the Tesla Semi.”
Tesla Semi’s official battery capacity leaked by California regulators
The timeline lines up with what’s already been showing up on public roads. In June, a Tesla Semi was spotted in Sunnyvale wearing a full validation rig, the same rooftop sensor array Tesla mounts on vehicles ahead of an FSD milestone.
A second unit was seen near Fremont days later with a matching camera suite and lens washers. Separately, Tesla analyst Nic Cruz Patane posted video this month of the production Semi’s exterior camera array, ten AI4 based units built directly into the truck rather than added later.
Tesla Semi AI4 cameras. The production version has 10 cameras on its exterior.
These trucks are designed to be autonomous. pic.twitter.com/GH3BamxIBQ
— Nic Cruz Patane (@niccruzpatane) April 14, 2026
Musk also gave the reason autonomy on the Semi matters in the first place, a persistent shortage of qualified truck drivers. “There is a really serious shortage of truckers,” he said on the call, framing a self-driving Semi as important both for addressing that shortage and for improving safety and comfort for the drivers running the truck today.
The timing also tracks with the Semi’s production reality. Tesla’s Q2 shareholder letter, dropped language promising the Semi would reach volume production this year. Musk pointed to 4680 battery cell output as the near-term constraint on Semi and Cybercab production. A software timeline landing in early 2027 gives Tesla’s autonomy team room to work while the hardware ramp catches up behind it.
It’s worth nothing that this isn’t necessarily a promise the Semi ships driverless next year. Musk’s own language, self-driving “working” by early 2027, describes internal validation catching up to hardware already riding on every production truck, not a public unsupervised rollout.
Investor's Corner
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.
The earnings results come after Tesla reported a massive beat on vehicle deliveries for the second quarter, delivering 489,126 vehicles and building 451,758 cars during the three-month span.
This was a major shock for those on Wall Street as they anticipated somewhere around 400,000 deliveries for the quarter, and showed Tesla still has plenty of demand for its vehicles around the world and in the U.S. despite losing the $7,500 EV Tax Credit last year.
Tesla Q2 2026 Earnings Results
- Non-GAAP EPS – $0.33 reported vs. $0.53 expected
- Revenues – $28.236 billion reported vs. $26.4 billion expected
- Free Cash Flow- -$1.092B
- Profit -$ 4.751B
Tesla (beat/missed) analyst expectations, so the market response to the company’s quarter is what we will look for next.
Tesla shares closed today down just over 1 percent, trading at $374.01.
In the past, it has been anyone’s guess with what Tesla shares will do after they report earnings. Strong quarters have resulted in sharp drops, while lackluster quarters have seen the stock shoot up considerably.
Tesla will hold its Q2 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.
You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.
Q2 2026 Earnings Call https://t.co/zZS6ii2TWK
— Tesla (@Tesla) July 22, 2026
Elon Musk
Tesla is about to make parking in busy lots less stressful than ever
Tesla is about to make parking in busy parking lots at businesses and other points of interest less stressful than ever by allowing drivers more control over where they park and how, CEO Elon Musk confirmed on X.
Tesla has been working to improve the parking performance of vehicles utilizing the Full Self-Driving suite, but now it is looking to add more customization, allowing drivers to choose the specific space they park in, but also potentially the orientation the car pulls into the spot:
It’s coming soon
— Elon Musk (@elonmusk) July 21, 2026
Musk has reiterated on X twice over the past several weeks that Tesla is working to make things with the FSD suite based more on the driver’s specific preferences and behaviors that were seen in past drives.
Essentially, it sounds like if you tend to park away from a business to avoid other vehicles, Tesla FSD will soon recognize that preference of yours and start parking further away as well. Additionally, the prospect of assigned parking spaces has been something many owners have voiced concerns about.
Living in a community with assigned parking spaces makes using FSD incredibly difficult as it will rarely park in the correct spot when there are so many to choose from. This is also pertinent in work settings where there are sometimes assigned parking spaces.
The updates to Tesla’s Full Self-Driving suite in terms of listening to driver preferences with parking are also extending to routing. Tesla announced yesterday that with the release of its 2026 Summer Update, it was adding Automatic Navigation and Preferred Routes:
Tesla reveals 2026 Summer Update with crazy fixes to Nav and more
Tesla has always maintained the idea that any human input is bad input, and that, ideally, Tesla Full Self-Driving will always make the right decision. Of course, this is all in theory, but the issue is that so many of Tesla’s interventions have come because it does something that is not necessarily wrong, but perhaps not what the driver would prefer.
Taking these preferences into account will help Tesla alleviate some of the potentially unnecessary interventions that drivers perform.
