Chinese electric car company Xpeng will use LiDAR sensors in its mass-market vehicles that are produced in 2021. The announcement from Xpeng came on Friday and deviated the company away from the current lawsuit that Tesla has against one of its former employees who took Autopilot sourcing code to the Chinese car company.
LiDAR is a strategy that utilizes light detection and ranging to determine self-driving accuracy. The strategy is advantageous in certain environments that offer sufficient lighting, but an automaker has never used it before now. The waves it uses to capture imagery is more ideal for higher precision driving, but it is costly. Elon Musk, Tesla’s CEO, once called the use of LiDAR “a fool’s errand,” and has consistently cited it as the wrong approach to developing self-driving techniques. “[They are] expensive sensors that are unnecessary,” Musk added when talking about the use of LiDAR to develop self-driving cars.
Musk’s opinions won’t convince Xpeng to shy away from using it, however. CEO He Xiaopeng said the LiDAR tech is “a breakthrough in popularising autonomous driving.” Xpeng said in a statement that using the technology will “significantly improve” the accuracy of its tech by holding the ability to recognize vehicles and other objects, making it safer and more defined on the company’s quest to a fully self-driving car.
The company’s announcement regarding the use of LiDAR counteracts with the current lawsuit Tesla holds against one of its former employees who went to Xpeng. Cao Guangzhi, a former Tesla Autopilot team engineer, was accused of stealing sourcing code from the Silicon Valley-based automaker and giving it to Xpeng for money. The lawsuit hit a standstill when Tesla was denied access to grand jury materials related to a former Apple employee, Zhang Xiaolang, who left the tech company for Xpeng.
But Xpeng’s adoption of LiDAR shows that Tesla’s sourcing code may not have been desirable to the Chinese automaker. Either that or the company couldn’t figure out what Tesla was doing with AP, as it is extremely complex and constantly improving thanks to the Neural Network. Musk stated in a Tweet on Friday morning that Xpeng has an old version of Tesla’s software, which is outdated, less complex, and not as functional as the current versions of AP. Additionally, Xpeng does not have the advantages of a Neural Network, which uses data compiled from every mile driven to improve its self-driving performance.
They have an old version of our software & don’t have our NN inference computer
— Elon Musk (@elonmusk) November 20, 2020
Musk made it clear that Xpeng was the only Chinese company that attempted to utilize Tesla’s AP source code, which was not open-sourced and was taken without the automaker’s consent.
Regardless, Xpeng is happy with using LiDAR as it believes it will offer a “nearly tenfold increase in computing power” and “centimeter-level accuracy.” While Xpeng will be the first car company to use LiDAR, it will not be the first autonomous driving entity to utilize the tech. Waymo uses the tech and is selling its own LiDAR systems as of 2019.
The expensive cost of LiDAR is sure to drive up Xpeng’s vehicles’ price, but the company did not want to indicate how much its 2021 vehicles that will equip the technology will set back consumers.
Originally reported by the South China Morning Post.
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.”
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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.