PATENT DROP: Tesla looks inward
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PATENT DROP: Tesla looks inward
Plus: Chase automates match-making, Mastercard seeks approval
Happy Thursday and welcome to Patent Drop!
This morning, we’ll dive into Tesla’s plan to get a really good look at its passengers, Chase’s business Tinder for investment bankers, and Mastercard’s AI balancing act.
Let’s take a look.
#1. Tesla’s vehicle endoscope
Tesla wants to get to inspect every inch of your car… and the people inside it.
The auto manufacturer is seeking to patent tech for a “personalization system” based on passenger location and “body portions.” Essentially, an image capture device that Tesla refers to as a “selfie camera” for facial recognition, and “control circuitry” captures biometric data like height, facial features and other body proportions. It also captures where occupants are sitting and where they move within a vehicle.
Using this data and taking user preferences into account, Tesla adjusts in-vehicle systems like audio output or climate control in real-time. For example, if a passenger is sitting in the back seat right next to a heating vent, this system may adjust the vent’s temperature or location so that they don’t overheat. Tesla noted that this system’s facial recognition tech can capture and store data on who has been in a vehicle and when, giving repeat passengers “custom audio greetings” for what Tesla calls (unironically, we assume) a “humanized in-vehicle experience.”
Tesla said the purpose of this is to better the “overall in-vehicle comfort and entertainment experience for the vehicle occupants,” as well as direct vehicle resources in an “efficient manner.”
“Vehicle occupant experience and personalization is an important aspect for creating a positive vehicle experience,” Tesla said in the filing. “Maximizing the comfort felt by the vehicle occupants allows fewer resources to be used, thereby decreasing energy usage and increasing vehicle range.”
Tesla hyper-personalizing its rides is a pretty predictable move given all the other outlandish features that Teslas come with (see Dog Mode, streaming while parked and at one point the ability to turn your horn into a fart noise – before that got recalled by the NHTSA.) But this feature represents more than just another cushy add-on. According to Bob Bilbruck, tech analyst and CEO of consulting firm Captjur, it actually shows Tesla’s commitment to making fully autonomous vehicles a reality.
This patent application stresses Tesla’s goal to make in-vehicle entertainment as comfortable as possible. Given the company’s commitment to its self-driving feature, that entertainment likely won’t be off limits to the person in the driver’s seat.
“This is based on their ideology around how their vehicles, probably within the next two or three years, are going to be completely autonomous,” Bilbruck told me. “Passengers will be passengers, there won't be a driver anymore.”
And because this patent application is so wide-ranging, if it’s granted, Bilbruck wouldn’t be surprised if Tesla tries to license this tech to other companies working on autonomous vehicles, like Nvidia, Baidu or Alphabet-owned Waymo.
But Tesla has more than a few hurdles to overcome if it wants to make its autonomous dreams a reality. Tesla’s self-driving software has been linked to fatal accidents and crashes multiple times. And the company has faced recall after recall related to its self-driving feature, including one from January which affected 363,000 vehicles that had Full Self Driving installed.
Regarding the recall, the National Highway Traffic Safety Administration noted that the feature “led to an unreasonable risk to motor vehicle safety based on insufficient adherence to traffic safety laws.”
Another potential hurdle? Tesla customers may not be so keen on allowing in-car surveillance for the sake of comfort after the recent report that the automaker’s employees passed around personal videos from owners’ vehicles, including graphic crashes, road rage incidents and embarrassing scenes. If Tesla really wants to look inward, it has some reflecting to do first.
#2. JPMorgan Chase’s robo-investor
JPMorgan Chase wants to get its bankers “on the apps,” or, more precisely, its app.
The company is seeking to patent a method for “matching investors with companies.” First, this system collects a whole lot of data. On the company side, this system will collect information on factors like a company’s focus and market size, existing capital raised, its age and location. On the investor side, this system will take into account factors like an investor’s industry preferred “funding style.”
Then, using an AI-based algorithm, this tech then spits out a “similarity metric” to tell whether a company-investor pair will make a good match, as well as a rationale as to why the algorithm decided they were a good fit. Think of it like a dating app with much higher stakes. It’s still unclear if interest in “long walks on the beach” will be factored in.
JPMorgan noted that this tech has the potential to save time and money on the manual match-making process, taking out the need for human labor to analyze companies’ track records and performance, or source inventors. Basically, it’s financial Tinder but for due diligence.
“Matching investors and companies and providing explanations is typically very expensive … it also brings about human errors and the results are often dependent on the individual experience and expertise of humans involved in this process,” JPMorgan said in its filing.
The fact that JPMorgan is working on this tech makes sense given the company’s massive investment in creating tech in-house. Despite the shaky market conditions, the institution sought to hire around 2,000 engineers back in September. In January, the company ranked at the top of Evident AI’s index for AI integration among global banks, taking the No. 1 spot for categories like talent, innovation and transparency.
CEO Jamie Dimon has also been loud about his support for the tech, saying that JPMorgan will spend “hundreds of millions of dollars per year” on A.I. efforts across the bank. In the company’s letter to shareholders released in early April, Dimon said the company already has more than 300 AI use cases in production, including “risk, prospecting, marketing, customer experience and fraud prevention,” as well as throughout payments processing.
“AI and the raw material that feeds it, data, will be critical to our company’s future success — the importance of implementing new technologies simply cannot be overstated,” Dimon said.
While the tech in this patent filing will likely be deployed internally, the company could also make a solid paycheck by packaging this tech as AI-enabled investment support for other financial partners, like venture capital firms, private equity firms or angel investors, Captjur’s Bob Bilbruck told me.
“Institutional investors are looking for investments that are can’t-misses,” said Bilbruck “They may be looking at licensing that to all their downstream finance partners that are looking for more intelligence around those investments and ways to do that research.”
And though this tech isn’t terribly complicated, it’s another example of AI integrating into industries that traditionally required human expertise, taking over everything from doctors calls to data centers. Maybe deploying the shrewd eye of an AI algorithm might help JPMorgan stay away from, well, investment missteps.
#3. Mastercard sees double
Mastercard really wants to get your approval – so much so that it’s using double the AI to sniff out what’s fraud and what isn’t.
The company filed a patent for neural network tech to increase approval rates of payment transactions. This tech uses two neural network-based models to correctly identify fraud. First, a payment goes through a fraud AI model to compare the features of the transaction (i.e., time, location, amount or currency) to historical payment data which then determines whether or not a transaction was fraudulent.
The transaction then goes through the approval model, which determines recommended “unutilized transaction features” – or explanations of why a certain transaction may seem unusual – to decide whether or not it’s approved or declined.
For instance, if you use a new card to buy a train ticket in Europe, but you live in Los Angeles and haven’t used the card for any other international purchases, this system might take into account the time and location that this purchase was made to let it through. Essentially, this tech cuts down on the gray area between what is and isn’t labeled as fraud.
“Due to fraudsters, the payment transactions are not completely secure and the merchants are advised to take additional precautions when accepting the payment transactions to avoid any liabilities such as chargeback,” Mastercard noted. “Issuers also utilize certain authentication models or fraud scoring models for payment transactions that may sometimes decline legitimate payment transactions.”
It’s not news that credit card companies and financial institutions are using AI to fight fraud: PayPal is using AI to similarly track transaction features and keep customers' money out of the wrong hands, and Mastercard itself is working on neural networks to teach users to spot phishing attempts.
But this patent filing almost does the opposite, as it tries to pull back the reins on oversensitive AI by sniffing out when things aren’t fraud. Given the company makes its money through credit card transaction fees, AI that’s ready to decline transactions at the slightest provocation isn’t exactly helpful.
Mastercard pointed out in the patent application that declining legitimate payment transactions “leads to significant losses in financial revenue for everyone in the payment ecosystem,” including the merchant, the card issuer and the financial institution. Additionally, the company noted that wrongfully declining transactions can have intangible adverse effects, as it may discourage a customer from using that card for future payments.
“Cardholders may avoid using a particular payment card, if they experience many such declinations,” Mastercard said in the filing. “Eroding cardholder trust thus, leads them to stay away from using the particular payment card from the issuer for months or more, and they may even never use that particular payment card again.”
If Mastercard’s patent tells you one thing, it’s that implementing AI is a balancing act that financial institutions and beyond are still trying to master.
Extra Drops
A few other fun tidbits before you head off.
Apple wants to know if you’re going to take a spill. The company wants to patent tech for “assessing fall risk” of mobile device users, with the goal of helping its older users.
Walmart is working on tech that can hyper-inspect your groceries. The company filed a patent for automated food selection using “hyperspectral sensing,” which essentially uses special imaging to select the freshest produce for your online orders without using human labor.
Meta wants to keep the metaverse from overheating IRL. The company wants to patent a system for “thermal management” in extended reality that monitors environmental factors like room or surrounding temperature and workload.
What else is new?
SpaceX’s Starship rocket launched for the first time, but exploded mid-flight. Elon Musk hinted at another test launch in a few months.
Tesla’s net income and earnings fell more than 20% year over year, though automotive revenue was up 18% in the same period.
Huawei is working on enterprise IT tech that can replace Oracle’s, aiming to reduce its alliance on U.S. tech companies.
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