General Motors (GM) has announced some crucial details about its upcoming Ultra Cruise autonomous driving system.
With the mass proliferation of autonomous driving, thanks largely to Tesla, more and more companies have begun working on their own systems. This includes GM, which has already released its Super Cruise system but has now released details about its next iteration, Ultra Cruise.
In the design process of autonomous systems, two leaders with two very different design philosophies have emerged. Tesla is the first, heavily relying on AI while focusing on visual sensor systems to guide the vehicle. This has been seen most clearly in Tesla’s upcoming hardware 4, which eliminates ultra-sonic sensors, instead opting to dramatically increase the quality of the visual sensing systems around the vehicle. The second camp is currently headed by Mercedes.
Mercedes has taken the complete opposite approach to Tesla. While still relying on AI guidance, Mercedes uses a combination of three different sensor arrays, visual, ultra-sonic, and LiDAR, to help guide the vehicle.
That takes us to GM’s Ultra Cruise, which was revealed in detail today. Much like Mercedes, GM has chosen to use three sensor arrays; visual, ultra-sonic, and LiDAR. Further emulating the premium German auto group, GM’s system “will have a 360-degree view of the vehicle,” according to the automaker.
According to GM, this architecture allows redundancy and sensor specialization, whereby each sensor group will help focus on a single task. The camera and short-range ultra-sonic radar systems focus on object detection, primarily at low speeds and in urban environments. These systems will help the vehicle detect other vehicles, traffic signals and signs, and pedestrians. At higher speeds, the long-range radar and LiDAR systems also come into play, helping to detect vehicles and road features from further away.
GM also points out that, thanks to the capabilities of radar and LiDAR systems in poor visibility conditions, the system benefits from better overall uptime. GM aims to create an autonomous driving system allowing hands-free driving in 95% of situations.
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As for the Tesla approach, the leader in autonomous driving certainly has credibility in its design. According to Tesla’s blog post about removing the ultra-sonic sensor capabilities from its vehicles, “Tesla Vision” equipped vehicles perform just as well, if not better, in tests like the pedestrian automatic emergency braking (AEB) test. Though it should be noted that the lack of secondary sensors is also likely to help reduce vehicle manufacturing costs.
Ultra Cruise will first be available on the upcoming Cadillac Celestiq. Still, with a growing number of vehicles coming with GM’s Super Cruise, it’s likely only a matter of time before the more advanced ADAS system makes its way to mass market offerings as well.
“GM’s fundamental strategy for all ADAS features, including Ultra Cruise, is safely deploying these technologies,” said Jason Ditman, GM chief engineer, Ultra Cruise. “A deep knowledge of what Ultra Cruise is capable of, along with the detailed picture provided by its sensors, will help us understand when Ultra Cruise can be engaged and when to hand control back to the driver. We believe consistent, clear operation can help build drivers’ confidence in Ultra Cruise.”
With more and more automakers entering the autonomous driving space every year, it will be interesting to see which architecture they choose to invest in. But what could prove to be the defining trait is which system performs better in the real world. And as of now, it isn’t immediately clear who the victor is.
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In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
Tesla headlights have caused a recall of over 20,000 of the company’s two most popular vehicles, the Model 3 and Model Y, due to the low-beam bulb exceeding the maximum allowed intensity according to federal standards.
Tesla initiated the recall with the National Highway Traffic Safety Administration (NHTSA) this morning, stating that the low-beam output “exceeds the maximum allowed intensity in the outer upper-right and outer upper-left areas of the 10U and 90U zone, as prescribed in FMVSS No. 108.”
Tesla sourced the impacted headlights from Marelli Automotive Lighting, a Mexico-based company. The recall impacts 2020-2023 Model Y vehicles and 2017-2023 Model 3 vehicles. It is estimated that every VIN in this recall is impacted by the defect.
🚨 Tesla is recalling 20,349 2020-23 Model Y vehicles and 2017-23 Model 3 vehicles due to an excessively bright headlamp low beam.
Currently, there is no remedy plan in place, as it is still being developed. pic.twitter.com/y34cIO2U0B
— TESLARATI (@Teslarati) August 11, 2026
Typically, Tesla would remedy recalls of this nature through an Over-the-Air software update, which has been a major focus of criticism by the company and its supporters because the NHTSA still refers to it as a “recall,” even though it requires no action by the vehicle owner. The fix is shipped over the internet and downloaded to the car.
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However, there appears to be a potentially different solution for this problem. Tesla has not developed a remedy for this issue, so it could potentially be on the way. The big issue appears to be the fact that these recalled lamps are out of production, and this is an old body style for both vehicles. The headlights and front-end designs are completely different.
Tesla switched to another supplier when the affected headlight design was discontinued. It plans to begin notifying owners of their remedy options by September 15.
Tesla filed a petition protesting the recall to fix the vehicles’ headlight issue, but the NHTSA denied it. Now, Tesla will come up with a solution to fix it.
Tesla has one big financial question to answer for investors: Morgan Stanley
SpaceX AI investment gamble will make it a big winner, firm says
