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GM buys LIDAR company for self-driving car program to take Tesla head-on
General Motors issued a press release on Monday announcing that it will acquire Strobe, a California-based technology startup that makes affordable chip-scale LIDAR technology for self-driving cars. An 11-person team from Strobe will be joining GM’s Cruise Automation unit as part of the acquisition.
With more affordable and higher accuracy LIDAR sensors coming to market, automakers that are looking to transition to all-electric fleets are assessing the strategic value with investing into self-driving technology. GM’s purchase of Strobe can be seen as just that. Acquiring a small and nimble startup that has a core focus on developing the key sensor used in autonomous vehicles allows the Detroit-based auto giant to speed its path to market with a self-driving car.
Kyle Vogt, GM’s Cruise Automation Founder and CEO, said through a press release, “Strobe’s LIDAR technology will significantly improve the cost and capabilities of our vehicles so that we can more quickly accomplish our mission to deploy driverless vehicles at scale.”
While GM continues to charge forward with implementing LIDAR technology into its self-driving program, the company also complements its technology with radar sensors to create a fault-tolerant sensing suite. Tesla CEO Elon Musk has famously touted LIDAR as ‘unnecessary’ in the context of an autonomous car due to its high cost. Instead, Tesla has opted to use a combination of cameras, radars and ultrasonic sensors to form the foundation for its Autopilot system. But as pricing for LIDAR technology continues to drop, could we see a change of core design in future versions of Autopilot?
Good thing about radar is that, unlike lidar (which is visible wavelength), it can see through rain, snow, fog and dust
— Elon Musk (@elonmusk) July 15, 2016
Vogt asserts that radar can operate under more challenging weather conditions, however it lacks the precision needed when making critical maneuvers at speed. “Strobe’s LIDAR sensors provide both accurate distance and velocity information, which can be checked against similar information from a RADAR sensor for redundancy. RADARs typically also provide distance and velocity information and operate under more challenging weather conditions, but they lack the angular resolution needed to make certain critical maneuvers at speed. When used together, cameras, LIDARs, and RADARs can complement each other to create a robust and fault-tolerant sensing suite that operates in a wide range of environmental and lighting conditions.” said Vogt in a blog post on Medium.
LIDAR on the other hand uses laser or concentrated light to map a high resolution 3D view of a the world, which arguably provides a higher precision view of a self-driving car’s surroundings. GM’s Director of autonomous vehicle integration has recently spoken up against Musk’s narrative that Tesla Autopilot will be fully autonomous and capable of piloting a car from California to New York on its own by the end of the year.
“The level of technology and knowing what it takes to do the mission, to say you can be a full level five with just cameras and radars is not physically possible,” said Miller about Tesla’s Autopilot suite. “Could you do it with what’s in a current Tesla Model S? I don’t think so.”
As the race to produce a fully autonomous car continues to heat up between Tesla, GM, Uber, and Google, and hardware prices decline, it’s only a matter of time before a tried and true combination of hardware will become the de-facto self-driving hardware suite. What will it be?
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.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
