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Adoption of Tesla’s electric truck will be driven by regulation
It’s expected that the commercial trucking industry will begin to transform in the same way that the passenger automotive industry has. Fuel efficiency has become a new priority and electrification is now the go-to plan for achieving higher MPGs in heavy trucking. In much the same way that regulations pushed trucking towards lower pollution at the expense of efficiency in the 1970s, today’s trucking paradigm is seeing a push for more efficiency. At what expense?
A new report from Ravi Shanker at Morgan Stanley urges investors to consider electric and self-driving commercial trucking as an opportunity. Shanker says that regulations and economics will drive the industry towards electrification and autonomous technologies. The analyst says that this could happen as early as 2020, which is when new federal fuel economy regulations on heavy-duty vehicles begin to really gather steam. Although efficiency gains will be had with electrification and self-driving, Shanker makes it clear that this will be secondary to the demand created by regulatory pressure.
As usual, we look to California for a glimpse of what could be coming. California’s Sustainable Freight Action Plan calls for 100,000+ zero-emissions trucks to be on the road by 2030 in that state. There is debate as to whether this plan is realistic, but federal standards are also playing a large role. The U.S. Environmental Protection Agency (EPA) and the National Highway Traffic Safety Administration (part of the federal Department of Transportation) have proposed emissions and fuel economy standards for heavy-duty vehicles. The first of these began with the 2014 model year.
For our purposes, the regulations affecting “combination tractors” (aka “tractor-trailer” or “18 wheeler”) models are pertinent. The 2018 standards are relatively loose and most in the industry believe they are achievable, but the EPA and NHTSA have proposed further standards to begin in 2021, with incremental increases thereafter through to 2027. The goals are largely aimed towards lower CO2 emissions with reductions of about four percent (depending on the vehicle type) being the goal. The reduction is not the issue with industry insiders, however, it’s the test cycle to be used, which some argue is less realistic and which disfavors other emissions that also have requirements to be met. This Phase 2 of the federal efficiency standards for heavy trucks is not yet finalized, but will very likely be the driving force behind national changes in trucks.
Equating these changes into standard numbers that the general public would understand is difficult. Heavy-duty trucks can range in fuel efficiency from 20 mpg or better down to 2-3 mpg. For most tractor-trailer combinations, MPG averages of 4-9 mpg are the norm, depending on load, tractor type, and area of operation. Most analysts calculate efficiency using fuel use in tons per mile with a relatively long distance (100-500 miles) being the average. Using this method, for example, in my time driving a tractor pulling a refrigerated trailer across all 48 states, my fuel economy average was about average for that sector of the industry at roughly 60 ton-miles per gallon. Today, these numbers are slightly higher, according to the latest U.S. Transportation Energy book. Using this method of calculation, a 2015 Toyota Prius is about a third as efficient at moving freight as was my truck.
This doesn’t mean there isn’t room for improvement, of course. There are more companies than Tesla working towards deleting the smoke stacks from big trucks.
In Europe, Volvo trucks is working hard towards a zero-emissions (at the tailpipe anyway) trucking solution with several approaches being tested. An overhead tram-like charging system has been deployed for a short stretch of highway in Sweden, aiming to improve plug-in trucks’ range in EV mode. Short-haul battery electrics and two different versions of autonomous (or semi-autonomous) systems are also being tested.
Here in the States, Volvo’s Mack Trucks is working on a handful of electrification options for heavy-duty drivetrains. So is Daimler (Freightliner, Western Star in the U.S.). Startups like Nikola also have eyes on this electric trucking future. Other startups have hoped to get into the mix as well, but the failure rate is high with companies like Smith Electric, Vision Industries, and Boulder Electric having designed and marketed innovative commercial truck options that ultimately never caught on.
Meanwhile, the largest maker of electric heavy vehicles is Chinese maker BYD, who branched out from making gadget batteries into building electric buses, trucks, and more. They are currently filling contracts internationally for buses and trucks in places as disparate at California, Malaysia, and Europe. BYD builds battery-electric, hydrogen fuel cell electric, plug-in hybrid, and hybrid drivetrains and machines for several commercial market sectors.
So we can guarantee that changes to the trucking industry are coming, but no one can say how fast or how much change that will be. Current federal regulations will drive the industry forward until 2018 and it’s likely that new standards will be in place to keep carrying change forward after that. California’s ambitious plans for adopting electric trucks will be largely regulation and incentive driven, but that has down sides as well. Many of the startups we’ve seen who’ve created electrified big rigs or delivery trucks ultimately failed when the incentives began to dry up.
For Tesla, this could mean that the financial case for the Tesla Semi will need to be more economics-based and less dependent on single market, incentives-based plans. This means that Elon and Co should be looking beyond California and it’s 100,000 vehicle plans into a broader market. We’ll discuss the potential economic case for a Tesla Semi in a future editorial.
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
