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Google wants to make “good” AI with your help

Google office in Zurich [Credit: Google]

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As a company with a global presence to the tune of at least a billion people, Google is taking both its immense tech capabilities and social responsibility role very seriously. Namely, it has pledged to provide tangible support to organizations wanting to help address societal challenges using artificial intelligence through its just announced “AI Impact Challenge”. Whether an idea needs coaching, grant funding from a pool of $25 million available, or credit and consulting from cloud services, Google will be there to help.

Towards this effort, the company has already provided an educational guide to machine learning, the primary tool it wants organizations to utilize in its problem-solving. It might seem counterintuitive for a proposer to need training on the very thing it’s proposing, but this is part of the point of Google’s support. To quote Google’s project page directly, “We want people from as many backgrounds as possible to surface problems that AI can help solve, and to be empowered to create solutions themselves…We don’t expect applicants to be AI experts.” Submissions are open until January 22, 2019, and winners will be announced in spring 2019.

Need inspiration for an idea? Or, perhaps, some examples of the kinds of problems that artificial intelligence can help solve? Google’s page dedicated to its “AI for social good” mission has featured projects that are already working towards societally beneficial goals. Here’s a breakdown of some of them:

  • The “Smart Wildfire Sensor” is a device that identifies and predicts areas in a forest that are susceptible to wildfires. To do this, it uses data from tools measuring wind speed, wind direction, humidity, and temperature combined with Google’s open source machine learning tool TensorFlow for photographic analysis of biomass (accumulated fallen branches and trees).
  • Protecting whales from preventable accidents such as entanglement in fishing gear and collisions with vessels is a challenge being addressed using whale songs and machine learning to locate where they’re singing from. The National Oceanic and Atmospheric Administration (NOAA) uses underwater audio recordings to identify and mitigate the presence of dangers in the estimated areas where whales are present. The thousands of hours of recordings accumulated presented a data challenge well suited to Google’s existing sound classification AI to help meet NOAA’s needs with conservation efforts.
  • As a top cause of infant mortality in the world, birth asphyxia is a serious threat needing all the tools available to new parents. Using machine learning trained to recognize the cries of a newborn with this condition, the company Ubenwa has developed a mobile app enabling a recording of a baby’s cry to be uploaded and diagnosed.

“With great power comes great responsibility” is a familiar motto that applies to the state of modern tech just as much as superheroes. For example, the fast-paced field of artificial intelligence brings frequent developments that challenge our security as a society, thus needing caution. However, the massive companies driving the primary innovations being used among the public on a grand scale are one of the larger demonstrations of this where this motto really applies in today’s world.

Google sharply felt the weight of its responsibility recently when its role in assisting the US Department of Defense to analyze drone footage (Project Maven) was revealed. The “Don’t be evil” part of the company’s Code of Conduct at the time appeared to be violated through the military assistance, and renewal of the contract has since been canceled. Google’s further work on its Chinese search engine with censorship in accordance with the communist government’s requirements has also drawn protest from both inside and outside the company. Given this background, a new project focused on doing “good” things for the benefit of society might be seen as possible damage control. The timing might be suspect, but it’s worth noting that, as seen in the projects described above, Google has been working to help with societal needs for quite some time already.

Overall, headlines in recent years have demonstrated just how flexible AI can be when it comes to solving challenges that face our world. While the fears brought on by future “intelligent” computers may have a foundation in reality, it may do us a great amount of good to turn our focus on the hope such technology can also bring. Whatever Google’s motivation is for launching its “AI for social good project”, if good is achieved, it may just be a win for us all.

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Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Starlink is ‘biggest competitive advantage,’ but it’s temporary, United CEO says

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Credit: United Airlines

United Airlines CEO Scott Kirby said that SpaceX’s Starlink satellite internet is its leading competitive advantage in the U.S. airline industry. However, in recent comments, while he described the service as “the biggest competitive advantage” the carrier currently holds, he also acknowledged that the edge is temporary.

“…everybody eventually is going to have high-speed low earth orbit internet connectivity. It’s going to be a must-have. We are going to have a few years of being the only airline that has it at scale, and that’s our mission,” Kirby said. Until everyone has it, United aims to capitalize on its head start by converting trial users into long-term loyal customers.

United has moved faster than its rivals on Starlink installations. As of mid-to-late October 2026, the system was on roughly 43 percent of its fleet, with plans to reach 61 percent by year-end, 87 percent by June 2027, and full fleet coverage by the end of next year.

The airline already operates more Starlink-equipped flights than the rest of the U.S. industry combined. Los Angeles International Airport is scheduled to become United’s first 100 percent Starlink hub in the first half of 2027, and the carrier’s app will display the likelihood that any given flight has the service.

Kirby has pointed to early evidence that the offering influences booking decisions. Some passengers loyal to other airlines are already switching flights for Starlink connectivity, something the airline, along with American Airlines, has tried to leverage against competing airlines. Both companies used status-match programs, and some of those customers are pursuing company-specific credit cards, which signals an intent to stay.

Once onboard, these customers encounter the airline’s broader investments in aircraft, larger seat-back screens, oversized bins, connection tools, and a mobile app that Kirby says outperforms competitors. Wi-Fi satisfaction scores on Starlink-equipped planes have been reported to be nearly double those on aircraft with other systems.

Competitors are moving slowly to do the same. Southwest Airlines began installations in 2025 and expects to complete them soon. Delta is pursuing Amazon’s Leo system, while American expects to start Starlink work in early 2027 and has not yet detailed regional-fleet plans. This timeline gap gives United a multi-year window in which it remains the only major U.S. carrier offering Starlink at scale.

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Kirby has framed the strategy as pressing that advantage while simultaneously widening gaps in other technology areas so that customers who try United for the Wi-Fi remain for the overall experience.

The approach reflects a calculated bet that superior in-flight connectivity can accelerate share gains and support longer-term financial targets, including a 10 percent pre-tax margin goal.

High-speed internet is particularly valued by premium and business travelers who can work or stream reliably. As low-Earth-orbit service becomes ubiquitous, the temporary nature of the pure connectivity edge means United’s retention will depend on whether its other product and operational improvements keep pace.

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Tesla Cybercab’s unorthodox paint process explained

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Credit: Tesla

Tesla Cybercab skips the traditional paint shop entirely, marking an unorthodox process for coloring the fully autonomous vehicle. However, the decision was a smart one, as it slashed factory costs, floor space utilization, and complexity, since Tesla relied on specialized alloys and in-mold coloring.

Munro Live was given the opportunity to do a factory walkthrough with Tesla Vice President of Vehicle Engineering Lars Moravy, who explained and detailed how Cybercab production at Giga Texas eliminates one of the automotive manufacturing industry’s most expensive and space-hungry elements.

A conventional paint line can cost hundreds of millions of dollars and require a million man-hours to build. Moravy framed the choice around Tesla’s core rule: “Question the requirements: why do you need paint?”

The structural answer lies in material selection. The aluminum alloys used in Cybercab’s front and rear castings do not oxidize and lose strength over time, the way many common automotive aluminum alloys do. Only the side modules, built around hot-stamped boron-steel door rings, receive an anti-corrosion e-coat, or dip coat. Front and rear modules skip coating altogether.

Model Y and Model 3 bodies, by contrast, are fully coated and painted.

Exterior colors come from the plastics shop, which Tesla engineers described as “our paint shop” for the Cybercab. Body panels are produced via reaction injection molding, referred to as RIM. Color is then mixed into a polyurethane resin at the mix head immediately before injection, so the panel emerges already colored with a Class-A surface.

Robots trim overflow to control sink marks and flow lines. The process avoids conventional spray-paint defects like orange peel and paint bleed. Scratches can still be repaired with compatible coatings that behave “basically like paint.” Because color is integral rather than a surface layer, shallow scratches do not expose a contrasting undercoat.

The secret behind Tesla’s Cybercab Gold goes well beyond just the color

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Tesla has also explored related approaches, including in-mold lamination and painted films on stamped panels.

The manufacturing payoff is substantial because removing the paint shop, combined with the “unboxed” modular process that builds and tests front, rear, side, and center modules in parallel before a short final assembly, cuts factory floor space per vehicle by about 50 percent.

Final assembly itself uses only about 25 automated stations, far fewer than the typical Model Y line, and the overall line runs at about 78 percent automation, Moravy said. The approach also eliminates volatile organic compound emissions associated with traditional spray painting for these panels and shortens the coloring cycle from hours to minutes.

Cybercab’s paint strategy is clearly less about aesthetics than about systematically deleting capital-intensive, energy-heavy, and space-consuming steps once material science and process design make them unnecessary. It is a concrete example of Tesla applying first-principles questioning to one of the auto industry’s most entrenched factory requirements.

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Tesla has a Cybercab problem nobody saw coming

Tesla’s Cybercab line now builds robotaxis faster than Tesla can deploy them, Lars Moravy says.

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Tesla’s Cybercab line in Texas can now build the two seat robotaxi faster than the company can put it into service, according to Lars Moravy, Tesla’s Vice President of Vehicle Engineering. “We don’t run every day because the line can run so fast. It’s currently outpacing our deployments,” Moravy said in a new Cybercab deep dive from Munro Live. “So, it’s a bit of a race right now. Who’s going to go faster? Right now the manufacturing line’s ahead.”

Tesla’s official Robotaxi account shared a Cybercab analysis video on X on Monday, calling it a “Cybercab engineering deep dive.” Moravy’s comments go further than what he told analysts on the Q3 earnings call last week, when he said the Cybercab line’s listed capacity of more than 125,000 units a year undersells what it can actually run.

The tour shows where that speed comes from. Tesla’s unboxed process splits the Cybercab into front, rear, side and center modules that are built and tested on their own before they meet on a short final line. That final line has just 25 fully automated stations, which Tesla’s team estimated is a fifth to a tenth of what a Model Y needs. The full line is about 78% automated, the framing line is already at 100%, and the layout uses roughly 50% less floor space per vehicle. The stated goal is “100% automation in 10 second cycle time,” or one finished Cybercab every 10 seconds.

Tesla also deleted the paint shop. Only the side modules are coated, and the exterior panels get their color inside the molding machine. Engineers said the car is designed to run at least 500,000 miles, which matters for a vehicle that will spend most of its day carrying riders.

The battery got the same treatment. The Cybercab uses an 88S6P pack of 4680 cells in a steel enclosure, a first for Tesla, with each module potted separately so a single failed module can be swapped instead of the whole pack. Wireless battery management boards replace a wiring harness, and new contactors are fast enough to drop the pyro fuse entirely. Tesla’s battery director graded the pack an A minus, compared with a D for the Model Y structural pack and a B minus for Cybertruck. Up front, the drive unit runs an 11:1 gear ratio versus roughly 9:1 on most Teslas, since the Cybercab does not need a high top speed.

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The deployment side is now the bottleneck Moravy described. Tesla had more than 50 Cybercabs working the Formula 1 weekend in Austin, and Texas records show 463 Cybercabs registered. Tesla said on its earnings call that Cybercab service will launch in Dallas next month, and Moravy said the company is aiming to get Cybercabs to customers by the end of 2026. Every unit built so far has gone into Tesla’s own fleet since the line moved into volume production in April.

Munro Live also asked when it could get a Cybercab to tear down. Tesla’s answer: “Not yet.”

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