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Don’t think for one second that Elon Musk is an AI fear-monger

Flickr: NVIDIA

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Elon Musk’s cautionary statements about uncontrolled experimentation with artificial intelligence (AI) have caused some to ridicule him as a fear-monger, and have given many in the mainstream press the idea that he is opposed to using AI, which is very far from the truth. In fact, AI is a major component of Tesla’s Autopilot system, and the company applies it in several other areas as well.

It was only recently that Tesla publicly revealed that it is working on its own AI hardware. At the NIPS machine learning conference in December, Elon Musk announced that Tesla is “developing specialized AI hardware that we think will be the best in the world.” The company has offered few details, but it’s widely assumed that the main application will be processing the algorithms for Tesla’s Autopilot software.

As Bernard Marr reports in a recent article in Forbes, there’s little doubt that Tesla is way ahead of its potential rivals in the data-gathering department. Every Model S and X built with the Autopilot hardware suite, which was introduced in September 2014, has the potential to become self-driving, and all Tesla vehicles, Autopilot-enabled or not, continually gather data and send it to the cloud. The company has many more sensors on the roads than any of its Detroit or Silicon Valley rivals, and the number will mushroom when Model 3 production hits its stride.

Tesla is crowd-sourcing data not only from its vehicles, but could one day obtain data on its drivers through internal cameras that detect hand placement on instruments or a person’s state of alertness. The company uses the information not only to improve Autopilot by generating data-dense maps, but also to diagnose driving behavior. Many believe that this sort of data will prove to be a valuable commodity that could be sold to third parties (much as data on web-browsing habits is today). McKinsey and Company has estimated that the market for vehicle-gathered data could be worth $750 billion a year by 2030.

Forbes explains that the AI built into Tesla’s system operates at several levels. Machine learning in the cloud educates the entire fleet, while within each individual vehicle, “edge computing” can make decisions about actions a car needs to take immediately. There’s also a third level of decision-making, in which cars can form networks with other Tesla vehicles nearby in order to share local information. In the future, when there are lots of autonomous cars on the road, these networks could also interface with cars from other makers, and systems such as traffic cameras, road-based sensors, and mobile phones.

At this point, no one knows what new forms of AI technology the mad scientists in Palo Alto are cooking up, but Forbes found some clues on the Facebook page of Tesla’s hardware partner Nvidia: “In contrast to the usual approach to operating self-driving cars, we did not program any explicit object detection, mapping, path planning or control components into this car. Instead, the car learns on its own to create all necessary internal representations necessary to steer, simply by observing human drivers.”

This unsupervised learning model contrasts with the more familiar approach of supervised learning, in which algorithms are trained beforehand about right or wrong decisions. Each approach has its pros and cons, and it’s likely that Tesla’s strategy includes both.

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Forbes reports that Tesla’s use of AI is not limited to Autopilot – the company employs machine learning in the design and manufacturing processes, to process customer data, and even to scan the text in online forums for insights into commonly-reported problems. It’s ironic that some in the press choose to portray Elon Musk as an AI Luddite, when in fact Tesla may be one of the most sophisticated users of the technology.

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Note: Article originally published on evannex.com, by Charles Morris

Source: Forbes

EVANNEX carries aftermarket accessories, parts, and gear for Tesla owners. Its blog is updated daily with Tesla news.

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Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident

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Credit: Teslarati

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.

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:

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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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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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SpaceX’s biggest test yet arrives this week and it’s not a rocket launch

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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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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.

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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.

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.

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