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.
Elon Musk
Elon Musk rips ABC News over fatal NYC Tesla crash report
Musk pushed back on NYC Tesla crash coverage, pointing to a pattern of premature blame.
Elon Musk pushed back overnight against media framing of a fatal Tesla crash in Midtown Manhattan, telling a user on X that “it wasn’t the car” and that the vehicle’s Autopilot system had nothing to do with the wreck.
The crash happened just before 3 a.m. Wednesday, when a 2024 Tesla Model Y struck a sidewalk shed outside 315 Madison Ave., a bus stop pole and a mailbox on East 42nd Street, according to the NYPD. The car kept moving several more blocks before stopping near Second Avenue. Both women inside, each 27, were taken to Bellevue Hospital, where the passenger was pronounced dead. The driver was charged with vehicular manslaughter, driving while ability impaired and leaving the scene of an accident.
Police have not attributed the crash to Autopilot or Full Self-Driving in any public statement. The charges point to impairment, not software. Musk’s response followed a since-deleted ABC News post that he said mischaracterized the incident. Replying to a user on X, Musk wrote that if Autopilot had been engaged, “they would not have crashed,” and added that “the legacy media will never forgive Tesla for failing to advertise with them,”
The legacy media will never forgive Tesla for failing to advertise with them
— Elon Musk (@elonmusk) September 9, 2026
It’s a familiar cycle for Tesla. In June, headlines from several national outlets described a fatal crash in Katy, Texas, as happening while the car was “on autopilot,” based on the driver’s own account to police after his Model 3 struck a home and killed a 76-year-old woman. Tesla’s data told a different story when Ashok Elluswamy, Tesla’s head of AI, said the driver had pressed the accelerator to 100% and reached 73 mph in a residential zone. Harris County prosecutors later confirmed the human override and the driver was charged with manslaughter.
Florida Gov. Ron DeSantis pointed to that same Katy crash last month to argue that outlets routinely name Tesla in crash headlines while leaving other automakers unnamed, even after a driver’s own actions are shown to be the cause. A similar pattern played out in 2024, when Musk had to clarify that FSD was never even downloaded onto the Model 3 involved in a fatal Colorado DUI crash, despite a passenger’s claim that an “auto drive feature” was in use.
Tesla has not issued a separate statement on the Manhattan crash beyond Musk’s posts on X. The NYPD’s investigation is ongoing, and no cause for the driver losing control has been released.
News
Tesla’s two defunct flagship models are getting a big upgrade
Tesla’s two recently-defunct flagship models, the Model S and Model X, are getting a big upgrade, according to the company’s Head of AI, Ashok Elluswamy.
Older Hardware 3 Model S and Model X vehicles have been the last major holdouts in Tesla’s Full Self-Driving v14 Lite rollout, and that wait now appears to be ending.
Tesla brings closure to flagship ‘sentimental’ models, Musk confirms
At Tesla’s Cybercab launch, AI chief Ashok Elluswamy told Ryan McCaffrey that he thought the S and X build “was supposed to go out last week.” Evidently, Elluswamy expects the suite to be rolled out to those HW3 Model S and Model X very soon:
For my @Tesla friends – and specifically Model S & X owners with HW3 who are waiting on FSD v14 Lite – I spoke to @aelluswamy at the Cybercab launch, & when I asked for an ETA on v14 Lite for S/X owners, he said, “Oh, I thought it was supposed to go out last week.”
So: soon! 🙌
— Ryan McCaffrey (@DMC_Ryan) September 7, 2026
Those cars are not the current Model S and Model X, which already ship with Hardware 4. They are the pre-refresh flagships built around Tesla’s older Autopilot computer, often called HW3 or AI3.
Tesla stopped putting that computer in new vehicles years ago, which is why owners treat these S and X cars as a closed generation. Model 3 and Model Y vehicles on the same computer began receiving v14 Lite in late June 2026 and saw a wider North American expansion in July. South Korea followed as an early international market. The S and X versions of the same software never joined that wave.
v14 Lite is Tesla’s way of squeezing the current v14 driving stack onto hardware that cannot run the full AI 4 model. The company describes the process as distillation: behaviors learned on the newer computer, including reinforcement learning and offline models, are compressed so the older chip and cameras can use them as a guide.
Early descriptions put the distilled network at roughly 15 percent of the original size. The result is still supervised Level 2 driving. Tesla has been clear that HW3 cannot support unsupervised Full Self-Driving or robotaxi operation because of memory and bandwidth limits.
The feature list is what made the wait so frustrating for S and X owners, as plenty of new features are to be shipped with it.
Official notes for the first Lite build, firmware 2026.20.5.1, added parking, unparking, and reversing; arrival options for a parking lot, street, driveway, or curbside; speed profiles that stay available at all times; and start-from-park engagement. Tesla also claimed better handling of merges, forks, pedestrians, traffic lights, and cut-ins, plus fewer false slowdowns and smoother lane centering.
A mid-July follow-on build, 2026.20.6.10, added more of the Hardware 4 interface, including a standalone Self-Driving app and the ability to start a trip from Park without a brake-pedal confirmation.
Elluswamy called that version the one “likely going to wide release.”
That wide release already reached most other HW3 cars in the United States and Canada. International timing still depends on regional validation and regulatory approval. For S and X owners, the remaining work appears to be model-specific validation rather than a new software stack.
There is no official Tesla changelog or build number for those two models yet, only Elluswamy’s offhand timeline. Some HW3 drivers who already have Lite report large gains over v12.6; others have described new indecision or phantom braking. The next test will be whether the same software lands cleanly on the older flagships that have waited the longest.
Cybertruck
This tiny Tesla Cybertruck adjustment has big advantages
Yesterday, we reported on Tesla Cybertruck getting some major adjustments from a manufacturing standpoint in an effort to make the all-electric pickup more cost-effective, more reliable, more serviceable, and more easily produced.
Tesla Cybertruck engineer reveals new changes in ‘constantly evolving’ pickup
One of those changes was the addition of a self-reinforcing polypropylene aero shield that sits underneath the truck. Previously, Tesla utilized aluminum for this, but the self-reinforcing polypropylene was more durable while also being cheaper and lighter.
Tesla has revealed another small change it made to the Cybertruck, and it has to do with the side repeater cameras.
Tesla does not wait for a new model year to improve its vehicles. On September 8, Cybertruck lead engineer Wes Morrill posted side-by-side photos of an updated side repeater camera housing now rolling off the line at Gigafactory Texas.
The triangular camera pod mounted on the front fender looks almost identical at first glance. A closer look reveals a revised contour that uses the air already flowing around the truck to keep the lens clearer in rain and road spray.
The side repeater camera was updated – the version on the left is the newer part which uses passive geometry to create airflow disturbance that better keep water off the lens while driving. No cost penalty, just pure vision improvement. pic.twitter.com/wAbXtcL1Jf
— Wes (@wmorrill3) September 8, 2026
The side repeater cameras sit in an exposed position on the Cybertruck’s angular stainless-steel body.
In wet weather, they readily collect water droplets that can degrade the image Autopilot and Full Self-Driving use for lane changes and blind-spot monitoring. Early production trucks sometimes left owners wiping lenses by hand or accepting temporary restrictions on driver-assistance features.
Tesla has added washers to cameras on certain other models and on Cybercab prototypes, but those active systems add cost, complexity, and extra potential leak points.
The new housing solves the problem with passive geometry. Subtle changes in the surround create localized airflow disturbances as the vehicle moves. Those eddies physically push water droplets away from the optical surface. Morrill called the result “pure vision improvement” achieved at “no cost penalty.” Once the production mold is updated, every subsequent part costs the same as the original.
The advantages compound quickly. Clearer cameras in rain improve the reliability of driver-assistance features precisely when they are needed most. The design consumes no extra energy and introduces no new failure modes.
New Cybertrucks built after the tooling changeover receive the updated part automatically. Some owners of trucks delivered as late as June 2026 have already confirmed they received the revised housing. Retrofit questions have appeared in replies, and the cameras appear electrically compatible, though Tesla has not announced an official service program.
A few millimeters of reshaped housing will not make headlines the way a new battery pack does, but these changes are incremental and increase the Cybertruck’s effectiveness as a vehicle over time.
This improvement illustrates how Tesla continues to refine the Cybertruck after volume production began. Better wet-weather vision, zero added cost, and no extra hardware add up to a meaningful gain in everyday usability and safety.