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.
Tesla released Full Self-Driving version 14.3.7 yesterday, and after about 90 miles of testing today, it is evident there are some definite fixes from version 14.3.6, which I wrote about last week and called a regression.
Within the first 40 minutes of my drive on v14.3.7, it saved me from getting into an accident with an unaware Dodge Charger driver, and some of the things Tesla seemed to miss in v14.3.6 were definitely improved. All in all, the release so far has some really great performance, and I’m looking forward to testing it further.
For now, here’s everything I noticed with v14.3.7:
Overall Improvement
Just generally speaking from a ride perspective, this was a really great experience. A lot of the hesitancy I experienced on v14.3.6 was gone. There were no instances of brake-stabbing, wheel-jerking, or any uncertain or unconfident movements. It was void of anything that I felt made it timid with v14.3.6.
The one thing I do hope to see down the road is a smaller need to adjust Speed Profiles so often. Because Tesla calls FSD “Supervised,” I’m okay with needing to hit the scroll wheel a few times a drive.
However, I hope that things can be incrementally improved upon with speed. Sometimes it’s too fast; other times it’s too slow. It’s a difficult thing to hone in and refine, but I hope it eventually gets there.
I didn’t notice any significant left lane camping or any behaviors that were completely out of line. I am hopeful that this opinion does not change, but after driving a few days with this version and putting it in a variety of different situations, you are exposed to more behaviors, some of which are not necessarily what I’d prefer.
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The big things to notice, at least in my experience thus far, are that the major issues with previous versions — meaning the braking stabbing and wheel jerking — simply weren’t there. That’s enough to already consider this progress compared to .6.
Manual Signal Override is More Responsive
On .6, I had quite a few issues with FSD ignoring my manually input turn signals. If Tesla wants to call it “Supervised,” then the car should not ignore any input the driver gives. If I touch the accelerator on FSD, the car speeds up.
🚨 Tesla FSD v14.3.7 obeying manual turn signals https://t.co/6eqToXpQfC pic.twitter.com/vHBlFQ4PDV
— TESLARATI (@Teslarati) August 2, 2026
The car did a great job of obeying my turn signals when I wanted it to change lanes, which is welcome.
Parking Lot Performance
Before .6, I traditionally took over in nearly every parking lot my car entered, because I knew it would not park somewhere that I wanted, and usually, it was just a tad too timid in this setting.
The one bright spot of .6 was how well it handled parking lots. This continued with v14.3.7:
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I’m always really happy to see progress at all, but once parking preferences come to FSD, as long as this performance is still around, that could potentially be the biggest improvement I’ve seen in FSD in the year I’ve been using it personally on a daily basis.
Full Self-Driving Averts Disaster
A Dodge Charger changed into my lane without checking if I was there, running me off the road. FSD made the initial avoidance maneuver; I grabbed the wheel out of instinct, looked in my side mirror to ensure I had nobody following closely behind, hit the brake, and straightened the car back up to avoid a curb:
🚨 Guys this is why you all NEED to stay vigilant behind the wheel, even on Tesla Full Self-Driving
Human drivers are UNHINGED and have no idea what they’re doing anymore. This was a kid obviously younger than 20 years old with zero awareness.
First drive with v14.3.7 https://t.co/1vTbCMpCn8 pic.twitter.com/lz7KKEF6bj
— TESLARATI (@Teslarati) August 2, 2026
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There have been quite a few responses to this video stating that I should never have grabbed the wheel. To be honest, I really wish I had not done so, because I do believe FSD would have avoided any sort of collision with anything, including the car or the curb.
However, this was the first time I had ever been this close to being hit while using FSD. My natural reaction was to take over. I think if I had had something like this happen before, my reaction might have been different.
Hitting the brake avoided hitting the curb, while FSD swerved to avoid the car. My concern after the car was clear of my front end was the curb. All in all, I’m really happy with how things turned out, and I think anyone could be a critic of how I handled it. I only had a split second to really make a decision, and thankfully, any damage was avoided.
It is clear FSD managed to avoid the car coming down before I was able to. I truly credit FSD for avoiding the collision.
What Needs to Improve
Better Recognition of Potholes, Uneven Roads, Sharp Changes in Roadway/Bumps
On Friday, my Fianceè and I were in the car, and FSD was driving us. We crossed over a roadway that has a traffic light, and FSD was traveling at 40 MPH on Standard, 5 MPH over the speed limit. Everything was more than reasonable.
However, the road we were crossing at the light has a major bump both as you start and finish crossing it. Without a speed reduction, your car can go airborne. The Tesla did just this on Friday on v14.3.6; it was an uncomfortable bounce that pretty much confirmed I would not ever let FSD go over again unless we were sitting at that intersection when there is a red light.
I even tried scrolling down into Sloth quickly, but I ended up just taking over:
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This is that big bounce that I mentioned in the quoted post.
It’s just a tad too drastic to take at the speed FSD wants to go over it. You can see me quickly swipe down into Sloth, but I intervened. https://t.co/K20PK9ysBg pic.twitter.com/81Oc82ZJcZ
— TESLARATI (@Teslarati) August 2, 2026
A few people have said it remains related to the vision-based approach and its difficulty comprehending 3D. This is a huge issue because this can cause serious damage at certain speeds.
Navigation
Nothing new here. I still turn off “Online Routing” quite frequently to get the car to take logical routes from time to time.
Auto Wipers
Auto Wipers are just plain bad. I really hope Tesla just uses a rain sensor. I thought they had improved at one point, but I still get dry wipes, Speed 4 on a drizzle, and Speed 2 on a steady rain. In reality, these should be switched.
You can watch our full review of Tesla Full Self-Driving v14.3.7 below:
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🚨 Tesla Full Self-Driving v14.3.7 saved me from an accident! FULL REVIEW: https://t.co/1vTbCMpCn8 pic.twitter.com/9mHmKVoMVA
— TESLARATI (@Teslarati) August 2, 2026
SpaceX will report second quarter results after the market closes on Tuesday, August 4, marking the first time the company has opened its books to the public since its record IPO in June. Management will host a live audio only webcast at 4:30 p.m. ET, streamed on X, with no dial in option.
The debut carries more weight than a typical first quarter as a public company. Two trading days after the release, on August 6, the first tranche of SpaceX’s lockup expires, freeing roughly 911.5 million insider and employee shares, worth well over $100 billion at current prices and the largest such release in Wall Street history. A second, larger tranche tied to the stock trading 30 percent above its $135 IPO price never triggered, since shares have spent most of July trading below that price.
Wall Street’s models point to revenue near $6.9 billion for the quarter, up sharply from the $4.69 billion SpaceX reported in the first quarter, with a narrower per share loss than the $1.27 posted three months earlier, according to estimates compiled by Motley Fool. Those numbers will be the first look at how SpaceX’s three segments, Starlink, launch and AI, are performing independently.
SpaceX scores another massive Pentagon deal to support military satellites
Investors heading into the call have a specific list of questions. How many net new Starlink subscribers did SpaceX add after ending March with 10.3 million, and is average revenue per user holding up as the service expands into lower income markets. How much of the AI segment’s revenue reflects contract signings with Anthropic, Google and Reflection AI this year, deals that combined could annualize to nearly $28 billion if fully ramped. Whether capital expenditures, which nearly doubled in the AI segment alone between 2024 and 2025, are still accelerating or starting to plateau. And whether management offers any forward guidance at all, something SpaceX has never done publicly.
The report will also land days after Elon Musk publicly denied a Wall Street Journal report describing internal planning to separate Tesla’s China business ahead of a potential Tesla-SpaceX merger. Whether Musk or SpaceX executives address that speculation on the call, even indirectly, maybe something investors will be listening for on Tuesday.
As Teslarati reported after Musk’s own warning to short sellers last week, the CEO has made clear he expects skeptics to be proven wrong over time. Tuesday will be the first chance for the numbers themselves to make that case.
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Elon Musk
SpaceX’s Starship just got filmed by its own cargo
SpaceX released new footage of Starship in space captured by the Starlink satellites it deployed.
SpaceX released a new video Friday evening showing Starship from an angle showcased by its own Starlink satellites, watching the rocket drift away in orbit.
The 65 second clip, posted on X, stitches together footage from four cameras mounted on a single Starlink V3 satellite. It opens with a close view of Starship’s 171 foot upper stage, still catching sunlight, then pulls back as the two spacecraft separate.
The footage comes from Starship’s 13th flight test, which launched July 24 from Starbase after a scrubbed attempt and an abort caused by an engine issue the week before. When Flight 13 finally flew, it carried the first batch of functional Starlink V3 satellites Starship has ever deployed, twenty of them, with six equipped with cameras meant to scan the ship’s heat shield during reentry.
View of Starship in space from a Starlink V3 satellite on Flight 13.
This composite is made of imagery from four separate cameras on a single satellite. Six of the satellites were equipped with cameras to scan Starship’s heat shield and transmit imagery down to operators to… pic.twitter.com/sNTHHz5vLr
— SpaceX (@SpaceX) July 31, 2026
Flight 13 checked most of its boxes. Starship deployed all 20 satellites, relit a Raptor engine in space, and splashed down softly in the Indian Ocean off Western Australia. Musk’s longer term plan calls for a Starlink V3 constellation of 100,000 satellites, according to a recent FCC filing, with Starship as the only vehicle capable of launching them at the volume that requires. Each Starship flight is designed to carry up to 60 V3 satellites once the vehicle reaches routine service, well beyond what Falcon 9 can carry in a single mission.
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Starship is next expected to fly with an attempt at catching the ship itself with the launch tower’s mechanical arms, a maneuver SpaceX has so far reserved for the Super Heavy booster.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
SpaceX’s biggest test yet arrives this week and it’s not a rocket launch
