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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Tesla is not sparing any expense in ensuring the Cybercab is safe
Images shared by the longtime watcher showed 16 Cybercab prototypes parked near Giga Texas’ dedicated crash test facility.
The Tesla Cybercab could very well be the safest taxi on the road when it is released and deployed for public use. This was, at least, hinted at by the intensive safety tests that Tesla seems to be putting the autonomous two-seater through at its Giga Texas crash test facility.
Intensive crash tests
As per recent images from longtime Giga Texas watcher and drone operator Joe Tegtmeyer, Tesla seems to be very busy crash testing Cybercab units. Images shared by the longtime watcher showed 16 Cybercab prototypes parked near Giga Texas’ dedicated crash test facility just before the holidays.
Tegtmeyer’s aerial photos showed the prototypes clustered outside the factory’s testing building. Some uncovered Cybercabs showed notable damage and one even had its airbags engaged. With Cybercab production expected to start in about 130 days, it appears that Tesla is very busy ensuring that its autonomous two-seater ends up becoming the safest taxi on public roads.
Prioritizing safety
With no human driver controls, the Cybercab demands exceptional active and passive safety systems to protect occupants in any scenario. Considering Tesla’s reputation, it is then understandable that the company seems to be sparing no expense in ensuring that the Cybercab is as safe as possible.
Tesla’s focus on safety was recently highlighted when the Cybertruck achieved a Top Safety Pick+ rating from the Insurance Institute for Highway Safety (IIHS). This was a notable victory for the Cybertruck as critics have long claimed that the vehicle will be one of, if not the, most unsafe truck on the road due to its appearance. The vehicle’s Top Safety Pick+ rating, if any, simply proved that Tesla never neglects to make its cars as safe as possible, and that definitely includes the Cybercab.
Elon Musk
Tesla’s Elon Musk gives timeframe for FSD’s release in UAE
Provided that Musk’s timeframe proves accurate, FSD would be able to start saturating the Middle East, starting with the UAE, next year.
Tesla CEO Elon Musk stated on Monday that Full Self-Driving (Supervised) could launch in the United Arab Emirates (UAE) as soon as January 2026.
Provided that Musk’s timeframe proves accurate, FSD would be able to start saturating the Middle East, starting with the UAE, next year.
Musk’s estimate
In a post on X, UAE-based political analyst Ahmed Sharif Al Amiri asked Musk when FSD would arrive in the country, quoting an earlier post where the CEO encouraged users to try out FSD for themselves. Musk responded directly to the analyst’s inquiry.
“Hopefully, next month,” Musk wrote. The exchange attracted a lot of attention, with numerous X users sharing their excitement at the idea of FSD being brought to a new country. FSD (Supervised), after all, would likely allow hands-off highway driving, urban navigation, and parking under driver oversight in traffic-heavy cities such as Dubai and Abu Dhabi.
Musk’s comments about FSD’s arrival in the UAE were posted following his visit to the Middle Eastern country. Over the weekend, images were shared online of Musk meeting with UAE Defense Minister, Deputy Prime Minister, and Dubai Crown Prince HH Sheikh Hamdan bin Mohammed. Musk also posted a supportive message about the country, posting “UAE rocks!” on X.
FSD recognition
FSD has been getting quite a lot of support from foreign media outlets. FSD (Supervised) earned high marks from Germany’s largest car magazine, Auto Bild, during a test in Berlin’s challenging urban environment. The demonstration highlighted the system’s ability to handle dense traffic, construction sites, pedestrian crossings, and narrow streets with smooth, confident decision-making.
Journalist Robin Hornig was particularly struck by FSD’s superior perception and tireless attention, stating: “Tesla FSD Supervised sees more than I do. It doesn’t get distracted and never gets tired. I like to think I’m a good driver, but I can’t match this system’s all-around vision. It’s at its best when both work together: my experience and the Tesla’s constant attention.” Only one intervention was needed when the system misread a route, showcasing its maturity while relying on vision-only sensors and over-the-air learning.
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Tesla quietly flexes FSD’s reliability amid Waymo blackout in San Francisco
“Tesla Robotaxis were unaffected by the SF power outage,” Musk wrote in his post.
Tesla highlighted its Full Self-Driving (Supervised) system’s robustness this week by sharing dashcam footage of a vehicle in FSD navigating pitch-black San Francisco streets during the city’s widespread power outage.
While Waymo’s robotaxis stalled and caused traffic jams, Tesla’s vision-only approach kept operating seamlessly without remote intervention. Elon Musk amplified the clip, highlighting the contrast between the two systems.
Tesla FSD handles total darkness
The @Tesla_AI account posted a video from a Model Y operating on FSD during San Francisco’s blackout. As could be seen in the video, streetlights, traffic signals, and surrounding illumination were completely out, but the vehicle drove confidently and cautiously, just like a proficient human driver.
Musk reposted the clip, adding context to reports of Waymo vehicles struggling in the same conditions. “Tesla Robotaxis were unaffected by the SF power outage,” Musk wrote in his post.
Musk and the Tesla AI team’s posts highlight the idea that FSD operates a lot like any experienced human driver. Since the system does not rely on a variety of sensors and a complicated symphony of factors, vehicles could technically navigate challenging circumstances as they emerge. This definitely seemed to be the case in San Francisco.
Waymo’s blackout struggles
Waymo faced scrutiny after multiple self-driving Jaguar I-PACE taxis stopped functioning during the blackout, blocking lanes, causing traffic jams, and requiring manual retrieval. Videos shared during the power outage showed fleets of Waymo vehicles just stopping in the middle of the road, seemingly confused about what to do when the lights go out.
In a comment, Waymo stated that its vehicles treat nonfunctional signals as four-way stops, but “the sheer scale of the outage led to instances where vehicles remained stationary longer than usual to confirm the state of the affected intersections. This contributed to traffic friction during the height of the congestion.”
A company spokesperson also shared some thoughts about the incidents. “Yesterday’s power outage was a widespread event that caused gridlock across San Francisco, with non-functioning traffic signals and transit disruptions. While the failure of the utility infrastructure was significant, we are committed to ensuring our technology adjusts to traffic flow during such events,” the Waymo spokesperson stated, adding that it is “focused on rapidly integrating the lessons learned from this event, and are committed to earning and maintaining the trust of the communities we serve every day.”
Tesla is not sparing any expense in ensuring the Cybercab is safe
Tesla’s Elon Musk gives timeframe for FSD’s release in UAE
