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NVIDIA and Bosch partner on AI self-driving car supercomputer
NVIDIA CEO Jen-Hsun Huang announced to attendees at the Bosch Connected World conference in Berlin this week that they have partnered with Bosch to producing an artificial intelligence supercomputer aimed at the self-driving car industry.
“I’m so proud to announce that the world’s leading tier-one automotive supplier — the only tier one that supports every car maker in the world — is building an AI car computer for the mass market,” said Huang. “We’ve really supercharged our roadmap to autonomous vehicles. We’ve dedicated ourselves to build an end-to-end deep learning solution. Nearly everyone using deep learning is using our platform.”
The announcement made by NVIDIA comes on the heels of this week’s announcement that the world’s leading chipmaker Intel will be acquiring ex-Tesla Autopilot partner Mobileye for $15 billion.
NVIDIA’s Drive PX platform with Xavier technology can process up to 30 trillion deep learning operations a second while drawing just 30 watts of power. It is intended to provide Level 4 autonomy, where a vehicle equipped with the technology can drive on its own.
Huang noted that a wide variety of companies are actively working on self-driving solutions. From carmakers like Audi, Ford, BMW, and Tesla, to technology companies such as Waymo, Uber and China’s Baidu.
As the self-driving car industry continues to take shape, vehicles will require an unprecedented level of computing power to make instantaneous decisions on nearly an infinite number of scenarios that can take place in a real world environment. Though vehicles on the road today are equipped with driving-assist features like Tesla Autopilot that allows the car to detect object and handle acceleration and braking when needed, the requirements for autonomous driving are dramatically more demanding. Cars that stray from their lanes, objects that fall onto the roadway, rapid shifts in weather conditions, deer that dart across the road. The permutations are endless, said Huang.
Despite the positive outlook on a self-driving future being presented at Bosch Connected World, the conference also revealed a significant difference of opinion between the companies in attendance regarding when they expect full Level 5 autonomy – when a vehicle can drive entire on its own without human involvement – to become widely available. Huang told the conference he expects to have chips available that will permit Level 3 automated driving which still requires a human driver to intervene, by the end of this year. He sees those chips being incorporated into customers’ cars and on the road by the end of 2018. The following year will see chips capable of Level 4 full autonomy on the road. The distinction between Level 4 and Level 5 full autonomy is that Level 4 does not cover every driving scenario.
Elmar Frickenstein, the head of autonomous driving at BMW, told the conference his company will be ready to offer cars with Level 3 capability in 2021 with Level 4 and Level 5 autonomy following shortly thereafter. He thinks self-driving cars may first be produced in small numbers for fleet customers like Uber, Waymo, and Baidu.
Surprisingly, Bosch CEO Volkmar Denner told the attendees his timeline for fully self-driving cars for mainstream customers is not before 2025, if then.
Fully self driving cars that can operate in all environments require enormous computing power, Huang told the conference. “No human could write enough code to capture the vast diversity and complexity that we do so easily, called driving,” he said.
The conference highlighted the differences between traditional car companies, which think full autonomy is still 7 to 10 years away, and chip companies like NVIDIA who see a much shorter timeline. Huang thinks companies like his will drive the pace of change faster than predicted. “In the near future, you’re going to see these schedules pull in,” he says.
Tesla, which uses a supercomputer made by NVIDIA on Model S, Model X and the upcoming Model 3 that are equipped with Autopilot 2.0 full self-driving hardware, is perhaps the most optimistic of all when it comes to having fully autonomous vehicles on the road. Elon Musk believes every car equipped with the Hardware 2 package will begin seeing Full Self-Driving capabilities as early as this year, barring regulatory approval.
Tesla’s Full Self-Driving Capability to arrive in 3 months, “definitely” by 6 months, says Musk
Tesla is accumulating driving data from billions of miles of real world driving each day and using that information to improve its algorithm for Autopilot.
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
