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.
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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Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
News
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
