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Google staff question involvement in Pentagon’s AI initiative

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More than 4,000 employees at Google have signed a letter calling on the tech giant to stop participating in the Pentagon’s flagship artificial intelligence initiative — Project Maven — which is aimed at helping the military identify potential hostile targets from images captured by drones.

Project Maven, formally known as the Algorithmic Warfare Cross-Functional Team, was founded as a way to demonstrate how advanced technologies such as artificial intelligence and machine learning could help the US military in its operations. In a statement to WIRED, former deputy secretary of defense Bob Work, who established Project Maven in April 2017, stated that the initiative’s first mission was to come up with a more effective way to process images from drone video.

According to Work, the Pentagon’s analysis tools proved ineffective due to the massive amount of high-resolution images from the drones. The plan was to utilize machine learning that Google and other internet companies use to help the drones distinguish objects of interest such as people, buildings, and vehicles. According to Work, the target for the video processing tool’s rollout was December 2017 — a timeline that was easily met, and the technology has impressed ever since.

Back in December, the Department of Defense stated that algorithms from contractors were helping in the fight against ISIS. Earlier this month, Lt. Col. Garry Floyd noted that technology developed for Project Maven is currently being utilized in the military’s operations in the Middle East and Africa. William Carter, a deputy director from the Center for Strategic and International Studies, even stated that by “DoD standards,” the efficiency of AI-based military solutions were “literally a work of magic.”

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The AI-based image processing system developed for Project Maven is capable of automatically annotating objects such as trucks, buildings, and boats on digital maps. The algorithms are also capable of being retrained by analysts, if the system makes a mistake during its operations.

Neither Google nor the Pentagon has declared the exact role that the tech giant played in the development of Project Maven’s technologies. Google did admit, however, that it helped the initiative by allowing the Pentagon to use its TensorFlow machine learning software to train algorithms on drone imagery analysis. Google noted, however, that the technology it provided was limited to non-offensive uses. In a statement to WIRED, Google’s AI director described the work done with the Pentagon as “mundane.” Despite this, the company’s participation in Project Maven still incited protests from several thousand Google employees.

Regardless of Google’s participation, or lack thereof, Project Maven is set to expand. The Pentagon is currently aiming to extend its AI-based image processing capabilities to larger, high-altitude drones. Project Maven is also attempting to apply AI in other military operations, such as the retrieval of potentially sensitive information from captured hard drives.

The Pentagon has expressed its openness to the use of AI in its field operations. Earlier this month, US secretary of defense Michael Griffin noted that the military would likely have self-driving vehicles before civilian companies such as Waymo or Tesla could roll out autonomous cars in America’s streets. The use of AI-enabled machines has also been on the rise, as evidenced by the number of intelligent battlefield robots deployed during a recent military exercise between the United States and Britain.

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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 says your Tesla will start to learn your individual preferences

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Credit: Tesla

Elon Musk said today on X that Teslas will start to learn your individual preferences. This is something that he seemed to hint toward earlier this month when he said parking was by far the biggest reason drivers intervene with Full Self-Driving.

Musk made the comment in response to notable Tesla influencer Whole Mars, who said that his vehicle will sometimes disobey the settings he has enabled for his car. He responded to the post, stating that “The car will start to remember your specific interventions and match each person’s individual preferences.”

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This is something that could be perhaps one of the biggest ways Tesla could minimize or even work closer toward eliminating interventions altogether. While FSD does a lot of things really well, many people intervene a vast majority of the time not due to major or critical safety errors.

Instead, many take over because the car is doing something that they do not like as a preference; it might park in a parking spot that is not preferred by the driver, it might linger too long in the left lane on the highway (a personal favorite), or it could even take a route that the driver does not like.

These all lead to interventions, but they are not triggered by a major safety issue. Instead, it’s just preference.

READ OUR REVIEW OF TESLA’S LATEST FSD VERSION:

Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance

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If Teslas could start to learn the personal preferences of the person who owns them, interventions will truly begin to be less frequent. Some of this is already pretty evident, in my opinion. Teslas use a neural network to learn behaviors and accumulate data to improve performance.

For months now, we’ve tracked FSD’s performance at “Except Right Turn” stop signs, something that is very common in Pennsylvania, but many of our readers located in other parts of the U.S. have never heard of. FSD handles one Except Right Turn stop sign very well, one that I travel past frequently. Others that I do not navigate through as often do not have as confident a performance. It seems like the cars might already be doing this to an extent.

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That example is also for something that is a street sign and not necessarily a driver preference; however, I still feel it is worth mentioning because it only handles that commonly passed Except Right Turn stop sign with true confidence. Others it still seems to struggle with.

This could be one of Tesla’s big moves toward full autonomy, and it could be a pathway to truly unsupervised driving. Every day, millions of cars on the road travel at a human driver’s personal preferences with no incident. Why can’t autonomous vehicles still cater to a passenger’s preferences while being autonomous? Tesla seems to have the idea that it would be possible.

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Ron DeSantis calls out media bias in Tesla crash coverage

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Credit: ABC News

Florida Governor Ron DeSantis has sharply criticized legacy media outlets for what he describes as selective and biased reporting on vehicle accidents involving Tesla. In a recent X post, DeSantis questioned why headlines routinely spotlight the Tesla brand in crash stories, even when human error is the clear cause, while similar incidents with other automakers often receive generic treatment.

A prime example is the June 19, 2026, fatal crash in Katy, Texas. A Tesla Model 3 driven by Michael Butler struck a brick home at high speed, killing 76-year-old Martha Avila inside. Initial reports and headlines prominently featured “Tesla crash” and referenced the driver’s claim that an automated driving-assistance system was engaged.

Many outlets quickly speculated that Full Self-Driving or Autopilot were the cause of the crash, immediately blaming the suites for the accident shortly after it happened.

However, Tesla responded shortly after the accident with vehicle data that showed Butler manually overrode the system by pressing the accelerator to 100 percent, reaching 73 MPH in a residential area, more than double the speed limit. The accelerator remained floored after impact.

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Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration

The National Transportation Safety Board (NTSB) later confirmed these findings, and Butler now faces manslaughter charges. His phone searches also included queries like “Tesla FSD too timid,” suggesting he may have intervened aggressively. Despite this, many headlines continued to center Tesla’s technology rather than the driver’s actions.

DeSantis highlighted a Washington Post headline, which was labeled, “Newly released photo shows wreckage of Tesla crash that killed grandmother.”

The subheadline noted the driver overrode assistance and floored the accelerator, yet the brand name dominated the framing. He asked whether legacy outlets typically name the make of a car in routine crashes or reserve that treatment for Tesla to push a narrative.

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This pattern appears widespread. Crashes involving Ford, Chevrolet, or Toyota vehicles frequently appear as “pickup truck slams into home” or “fatal car crash kills pedestrian” without brand specifics, especially absent new technology angles.

High-profile Ford F-150 or Chevy Silverado incidents tied to large sales volumes often escape brand-callout scrutiny. In contrast, Tesla stories consistently lead with the manufacturer, amplifying perceptions of risk despite data showing strong overall safety performance:

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Tesla’s own 2025 Impact Report indicates vehicles using FSD logged 0.19 major incidents per million miles, roughly eight times fewer than the U.S. average. Models like the Model Y also rank among the safest in IIHS and NHTSA testing for occupant protection. Critics argue disproportionate coverage ignores these statistics and driver behavior factors, such as younger or more aggressive Tesla owners in some studies.

DeSantis frames this as part of a broader political agenda against innovative American companies like Tesla. By consistently naming Tesla while downplaying others, media outlets risk eroding public trust and shaping perceptions detached from the evidence of human error in most cases.

As autonomous technology evolves across the industry, consistent and factual reporting will be essential to separate real safety concerns from narrative-driven coverage.

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Tesla enters two new markets on two different continents in one week

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Tesla entered two new markets this week by advancing its presence in Latvia (Europe) and officially launching operations in Uruguay (South America), marking a rapid dual-continent expansion.

These moves underscore the company’s strategy to tap into emerging EV markets with supportive policies, renewable energy grids, and growing demand for sustainable transport.

Latvia: Strengthening the Baltic Footprint

In Latvia, Tesla has built on its earlier registration of Tesla Latvia SIA in late 2025 with recent steps toward full operations, including job postings for a service center and representation in Riga. This aligns with broader Baltic expansion following Lithuania’s model of pop-up stores and service centers.

EV penetration in Latvia stands at around 7 percent for BEVs in new passenger car registrations. 2025 data showed 1,602 BEVs out of about 22,500 total, or 7.1 percent, with combined plug-ins nearing 19 percent. Growth has been steady but below the European average, supported by government subsidies and infrastructure development. Tesla models like the Model 3 lead local EV registrations.

Vehicles for the Latvian market will likely be sourced from Gigafactory Berlin or Gigafactory Shanghai. Charging infrastructure is robust for the region as well, with over 400- 2,000 public points, with Tesla Superchargers in Riga, Jūrmala, and along Via Baltica routes offering up to 250 kW.

Uruguay: Third South American Country

Tesla teased its Uruguay arrival with “Estamos llegando,” or, “We are arriving,” on social media, followed by an official presentation scheduled for mid-July.

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The company established Tesla Uruguay SAS, homologated Model 3 and Model Y (three versions each), and appointed local leadership. This makes Uruguay Tesla’s third official South American market after Chile and Colombia.

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Uruguay boasts one of Latin America’s highest EV penetrations, with battery-electric vehicles exceeding 20 percent market share recently, driven by tax incentives, high fuel prices, and a nearly 95-100 percent renewable electricity grid. Hundreds of Teslas already operate via grey imports, but official sales bring warranties, service, and support.

Vehicles will be imported from Gigafactory Shanghai, enabling competitive pricing for Model 3 and Model Y. Charging plans include Supercharger development alongside existing infrastructure, leveraging the country’s green energy advantage for affordable operation.

Tesla Superchargers follow Model 3 and Model Y to South American country

Tesla’s Dual Continent Expansion

Tesla’s simultaneous push into Latvia and Uruguay demonstrates efficient scaling: prioritizing service and infrastructure first, then direct sales in high-potential niches. In Europe, it fills Baltic gaps; in Latin America, it counters Chinese dominance while leveraging renewables.

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This dual move signals Tesla’s ambition to accelerate global EV adoption amid varying regional paces. By addressing local needs, like subsidies in Latvia or incentives and green grids in Uruguay, Tesla not only boosts volumes but advances its mission of sustainable energy.

For investors and consumers, it highlights resilience and opportunity in diverse markets, potentially paving the way for further growth in underserved regions. With strong fundamentals in both, these entries could yield long-term gains as EV transitions mature worldwide.

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