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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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Elon Musk

Tesla buyers are buying for Full Self-Driving and not for the car, data shows

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(Credit: Tesla)

Tesla Full Self-Driving (Supervised) showed a record attach rate at delivery for new vehicles in the third quarter of 2026.

75 percent of new vehicle deliveries in North America included a subscription to FSD software, up from 55 percent in the prior quarter, a 20-percentage-point sequential gain in the company’s most mature market.

Tesla Q3 2026 Earnings results: in-line revenues, slight beat on EPS

Tesla shed light on the Q3 Shareholder Deck that 75 percent of new deliveries came with an FSD subscription:

“FSD (Supervised)⁴ attach rate continued to grow, reaching over 75% of new vehicle deliveries in North America – our most mature market – a nearly twenty percentage point sequential increase. We believe that FSD is driving demand in markets where it is available, and we continue to work with regulators to get it approved in other markets. “

The higher attach rate accompanied strong growth in the overall FSD consumer base, as active subscriptions rose to 1.75 million, a 67 percent year-over-year increase. For the first time, more than half of paid customers are on the monthly subscription, which is priced at $99 per month in the U.S.

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The transition to subscriptions has accelerated since Tesla discontinued the one-time purchase option in most markets earlier this year. The recurring model improves revenue visibility and margins compared with large upfront payments. With three-quarters of North American deliveries now including FSD, the software is now an evidently large contributor to Tesla’s economics and ancillary revenue.

Geographic expansion remains important for further gains. FSD is now available in nine countries in the EU, and more than 100,000 customers have driven over 160 million kilometers. Tesla is pursuing broader EU-wide approval, with a related vote expected in December. Similar progress in additional markets could support higher attach rates beyond North America.

These results came as Tesla had a strong quarterly delivery performance of 486,532 vehicles in the quarter, which came with its largest passenger-vehicle backlog in four years. Battery supply continued to limit volume, but the company has pointed to FSD as a clear difference-maker that is helping sustain demand. As supervised capabilities improve, the attach rate will likely continue to improve.

At face value, it is a key measure of how Tesla is converting sales into autonomy progress.

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Tesla Cybercab gets a for sale date at last

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Credit: Tesla

Update: 10/22 10:51a – Para 1 consumers changed to “customers” for accuracy.

Tesla Cybercab units finally got a definitive date for when they will be able to be purchased by customers, ending speculation regarding whether the fully autonomous vehicle would be available in the near term.

During Tesla’s third-quarter 2026 earnings call on October 21, Vice President of Engineering Lars Moravy said the company is aiming to begin delivering its purpose-built Cybercab robotaxi to customers before year-end.

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“We’re trying to get Cybercabs to customers by the end of this year, 2026,” Moravy said. He added that production is underway on the line at Gigafactory Texas, but “all of those are currently going to our own internal Robotaxi fleet.”

Moravy explained that as operations scale, Tesla will “mainly deliver fully designed autonomous vehicles to our customers,” with the Cybercab as the first such vehicle. Initial customer deliveries will start small while the company gains experience with delivery logistics, ownership models, fleet management, and operating autonomous vehicles outside its direct control.

CEO Elon Musk reinforced the limited nature of private sales, describing the Cybercab primarily as a “transport-as-a-service” offering rather than a personal ownership vehicle like the Model 3, Model Y, or upcoming Roadster. “The vast majority of the Cybercab stuff will be Tesla-owned and transport-as-a-service,” Musk said.

The Cybercab is a two-seater vehicle developed by Tesla without a steering wheel or pedals. It relies completely on Tesla’s Full Self-Driving suite and has been in production since February. Early units have been put in Tesla’s Robotaxi service as of early September, when the company launched rides to the public. Tesla previously indicated it would aim to sell Cybercabs for about $30,000.

Unsupervised Full Self-Driving is expected to ship to consumer cars during Q2 2027, Ashok Elluswamy, Tesla’s Head of AI, indicated during the call. Early buyers or fleet operators may receive vehicles whose autonomous operation remains geographically restricted due to lagging regulatory agencies. There are some hurdles that remain ahead of Cybercab deliveries.

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Tesla Q3 2026 Earnings results: in-line revenues, slight beat on EPS

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Tesla (NASDAQ: TSLA) reported its earnings for the third quarter of 2026, marking a reasonable performance on the various financial metrics. Tesla still plans to hold a call that will field investor questions at 5:30 p.m. ET, 4:30 p.m. CT.

Here’s where Earnings came in:

  • Total Revenues: $28.046 reported vs. $28.34B expected
  • Non-GAAP EPS: $0.48 reported vs. $0.45 expected
  • Operating Margin: 2.6 % reported vs. 2.5% expected
  • Operating Income: $718M reported vs. $721M expected
  • Free Cash Flow: $1.531B reported vs. ~-$4.51B expected

Major Takeaways

Full Self-Driving (Supervised)

“FSD (Supervised)⁴ attach rate continued to grow, reaching over 75% of new vehicle deliveries in North America – our most mature market – a nearly twenty percentage point sequential increase. We believe that FSD is driving demand in markets where it is available, and we continue to work with regulators to get it approved in other markets.”

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Tesla Semi

“We began volume production of Tesla Semi, our Class 8 heavy-duty truck. The top variant can go 500 miles at full 82,000 lbs gross combination weight while achieving an efficiency of 1.7 kWh/mile. That efficiency allows the Tesla Semi to use a third of the energy used by a comparable diesel truck to haul the same payload. In a transportation market where energy is one of the largest components of total cost per mile, this will provide a meaningful advantage to Tesla Semi operators.”

SI Compute

“We plan to reach 400 MW of SI training compute by the end of the year, supporting the development of both vehicle and humanoid robot autonomy software. Additionally, we continued construction for the Austin Fab, where we plan to start commissioning equipment in 2027.”

Robotaxi

“We began deployment of Cybercab into our Robotaxi fleet in Austin. We reached nearly two million cumulative unsupervised miles for our Robotaxi service as of the end of the quarter. Operating hours in Austin are now 6am to midnight, and we expect to reduce wait times via increased fleet supply and improvement of Robotaxi orchestration algorithms. Grok is available in Cybercab with access to Grok Bot and Connectors, which allows users to manage their inbox, calendars, files, chats and tasks – all hands free via voice command – making Cybercab a mode of transport, a productivity space and, with our entertainment options, a second living room.”

Interested in ordering a Tesla? Use my referral code for three free months of Full Self-Driving (Supervised) here.

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