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Musk outlines cost-cutting plan for Boring Co: cheaper, faster tunnel digging
One of the large reveals made by Tesla and SpaceX Chief Elon Musk at TED2017 was his plan to create a multi-layer high-speed tunnel infrastructure to support mobility by way of electric skates and Hyperloop tubes.
A key point that he drove home for the underground tunnel network was the integration of the system into cities.
“You have to be able to integrate the entrance and exit of the tunnel seamlessly into the fabric of the city. So, by having an elevator, sort of a car skate that is on an elevator, you can integrate the entrance and exits to the tunnel network just by using 2 parking spaces.”
Musk shared a video demonstrating how skate elevators would be integrated into city streets where they await vehicles looking to be transported through the underground labyrinth of tunnels. The serial tech entrepreneur envisions loading docks wherein vehicles would simply pull into the skate, get lowered into the tunnel network, and be sent along a slot car-like track at speeds of 200 km/h ( 124 mph). The Boring Company’s tunnel network won’t simply alleviate surface congestion, it will completely transform the way we move cars, people and freight, says Musk.
It is worth noting that The Boring Company and Tesla are under control of Musk, while the Hyperloop project has been open sourced, but with support from SpaceX.
Eliminating human drivers allows the skates to move at much faster speeds than human-controlled vehicles. Fixed routes within the tunnel network further improve safety beyond the dynamic nature of human-determined driving routes. The tunnel network is also infinitely scalable. “You can alleviate any arbitrary level of open congestion with a 3D tunnel network.” and that “There’s no real limit to how many levels of tunnels you can have.”, says Musk from TED2017.
The key barrier to creating tunnels today is the exorbitant cost. The recent 2.5 mile expansion to the Los Angeles subway system came at a cost of nearly $1 billion per mile. Musk and team at the Boring Company hope to cut the cost of tunneling by a significant amount by streamlining the tunneling process and reinventing the machines that help facilitate the digging.
https://www.youtube.com/watch?v=u5V_VzRrSBI
Building Tunnels For Less
First, the team is looking to cut the diameter of the tunnels they dig, moving from the traditional tunnel diameter for passenger vehicles of 26 to 28-feet to a 12-foot standard diameter which would be sufficient for the Tesla skate. On the surface, this might not seem like a lot, but cutting the diameter by 50% cuts the cross sectional area by a factor of four. This is significant as the speed and cost of tunneling is largely driven by the amount of cross sectional area to dig. Being able to cut out 75% of the time associated with digging comes with enormous cost savings.
Second, the team plans to attack head-on the way tunneling machines currently dig. Traditional machines dig, slowly and incrementally, then stop to install reinforcements to support the newly exposed earthen walls. Musk and team are working to install the reinforcements continuously thus eliminating the need to pause operations. This integration is expected to increase the speed of the overall process by as much as 50%.
The Boring Company tunneling machine spotted in front of SpaceX in April, 2017
Finally, the team believes that current digging machines are nowhere near their power and thermal limits, and is looking to ‘jack up the power’ to the digging machines. Doing this, the team hopes to increase the speed by a factor of 4 or 5 on top of the other improvements being suggested by Musk.
Musk also revealed that The Boring Company has a pet snail named Gary who can currently travel at 14 times the speed of existing tunneling machines. While this is more a testament about how slow the boring process is than the amazing speed of Gary, it is a fun target for the team, to be able to build tunnels quicker than Gary can crawl, and continues the comedic spin on the new company.
These tunnels could be kept at or near a vacuum to reduce or eliminate air resistance for all the moving objects within it. Curiously, Musk shared that,
“To withstand the water table, you have to design a wall to be able to withstand 5 or 6 atmospheres. To go to vacuum, you only need to be able to withstand 1 atmosphere.”
It is clear that Musk is very excited about this new Boring Company. He indicated during his sit down at TED2017 that he spends 2-3% of his time on the project, noting that it’s essentially being run as not much more than an intern project with a used boring machine and a few people dedicating partial effort to it.
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
