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California Energy Commission pushes efforts to hold unreliable EV charging networks accountable
The California Energy Commission is taking steps to increase EV charging networks’ accountability and responsiveness to complaints. The efforts are timely as the number of electric vehicle owners in the state is growing at a quick pace.
Among electric vehicle makers, only Tesla has really solved the problem of long-distance travel in an all-electric car. This is largely due to the Tesla Supercharger Network, which provides a simple, quick, and reliable system for the company’s lineup of vehicles. Tesla’s Supercharger Network in the United States is still exclusive to Tesla as of writing, so non-Tesla EV owners are required to use other DC charging solutions for their vehicles.
This is where problems ensue since DC fast charging systems even in electric vehicle hubs like California are still far from very reliable. As noted in a Car and Driver report, EV charging networks may list a charger as “working” as long as the stations respond to a ping request from a remote center. The system is better than nothing, but it is prone to errors since charging stations can maintain cellular connectivity despite having issues such as jammed credit card readers, or software errors, to name a few.
The issue has been so notable that electric vehicle owners have come up with crowdsourced solutions to accurately rate DC chargers. Among these is the @rateyourcharge account on Twitter, which was created by EV group Out of Spec Studios to provide accurate reports of EV charger capabilities in the wild.
Amidst this environment, the California Energy Commission has shared plans to establish regulations for evaluating the reliability and availability of public electric vehicle charging stations. The commission is set to begin a public feedback process with the aim of defining “uptime” standards for EV chargers. These are expected to block excessive exemptions that would enable EV charging networks to avoid being held accountable for the reliability of their service.
The Commission also noted that it would no longer rely on self-reported claims from EV charging network providers regarding the availability and uptime of public charging stations. Instead, the commission plans to gather data from various sources to gain feedback from the public about the reliability and availability of EV charging stations. This feedback could include reports of non-functioning stations that are posted on apps and other platforms.
Apart from this, efforts are underway for California to evaluate the availability of EV charging stations at the individual station level instead of the overall site. This is quite different from the draft standards being developed by the National Electric Vehicle Infrastructure (NEVI) program, which could result in some charging sites getting a 100% score just because one stall is functioning. EV charging networks generally prefer this system, but electric vehicle owners are the ones that end up with the shorter end of the stick.
Providing fast and reliable charging solutions to electric vehicles is no small task. Non-Tesla Supercharger networks like Electrify America have to cater to numerous brands of cars with equally numerous types of software, and details such as payment options are abounding. Managing membership plans for electric car owners is also a pretty complicated task. But as electric vehicles become more mainstream, the time is right to demand more accountability among EV charging network providers. There will only be more EVs on the road in the coming years, after all, so it only makes sense to ensure that they are well-supported.
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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
