Tesla has filed a recently-published patent application titled “High-Speed Wiring System Architecture” that addresses an important aspect of its Full Self-Driving (FSD) suite: redundancy.
Traditional computer wiring systems often have no redundancy in their communications. Individual devices are connected to a central point (such as a processor), and each device receives communications separately from that point via some sort of cable. If one of the connections fails, communications to the device fails, and in a self-driving situation, that could mean complete system failure.
Simply adding more backup cables isn’t really a great solution, either. More wires mean more connection points, and if you’ve ever worked with microcontrollers or circuit boards professionally or as a hobby, you can already see the downside to this. More connection points mean bigger boards, and bigger boards mean higher manufacturing costs.
This is where Tesla’s new wiring system comes in, which was published on August 15, 2019 as US Patent Publication No. 2019/0248310.

The wiring architecture, as described, comprises a bi-directional backbone cable that forms a loop to and from a processor; along that backbone are connected devices (i.e., segments) with hubs inside associated with one or more cameras and/or radars. The backbone can function as two separate loops, meaning if one portion of the backbone fails, data from all the devices and hubs can still be sent to and from the processor thanks to the dual-loop capacity.
Perhaps a good way to visualize this is to imagine bumper cars or a marble traveling in a loop unimpeded. If a barrier were to suddenly be erected, the car and marble would bump the barrier and travel in the opposite direction. Or, instead of a barrier to bump, imagine a sharp U-turn came up, forcing the travel back in the other direction. The U-turn would happen on either side of the barrier, meaning motion (communication) would still continue back and forth to the processor despite a break in the larger loop (backbone).
The specific advantage of this new architecture over traditional systems, other than less cables connected to the processor, is that each hub within the devices is also connected in serial or in parallel to the other hubs via the backbone. If one hub within a device fails, the other hubs can still transmit to the backbone and thus to the processor. In a traditional system, if one cable to/from a device fails, all communications to/from radars and cameras inside the device fails.

Essentially, what Tesla’s done here is mitigate the damage of one thing failing in an FSD system to just that one thing. Here’s how the application sums up that concept: “In embodiments, when backbone is formed using a bi-directional cable…then the wiring system architecture can tolerate one fault in the backbone while still maintaining communication pathways for all hubs and devices.”
Notably, Tesla’s patent application also specifies that its technology could be used in a variety of vehicles, including semi-trucks, indicating the company may intend to use the architecture as a standard setup for all its FSD programs in the future. Additionally, language is included to broaden the architecture’s application to farming, nautical, and other industrial applications.
A few of Tesla’s recent patent applications have demonstrated numerous efforts being made to improve the safety of FSD systems wherever opportunities for improvement are found. For example, an application published in May titled “System and Method for Handling Errors in a Vehicle Neural Network Processor” describes a way to safely handle errors encountered in self-driving software. Another application titled “Autonomous Driving System Emergency Signaling” describes a method of quickly communicating emergency information from vehicle sensors feeding into autonomous driving software. While Full Self-Driving may take a significant amount of time to be fully implemented for a variety of reasons, there’s no question that Tesla is working hard to make it a reality.
Energy
Tesla VP hints at Solar Roof comeback with Giga New York push
The comments hint at possible renewed life for the Solar Roof program, which has seen years of slow growth since its 2016 unveiling.
Tesla’s long-awaited and way underrated Solar Roof may finally be getting its moment. During the company’s Q3 2025 earnings call, Vice President of Energy Engineering Michael Snyder revealed that production of a new residential solar panel has started at Tesla’s Buffalo, New York facility, with shipments to customers beginning in the first quarter of 2026.
The comments hint at possible renewed life for the Solar Roof program, which has seen years of slow growth since its 2016 unveiling.
Tesla Energy’s strong demand
Responding to an investor question about Tesla’s energy backlog, Snyder said demand for Megapack and Powerwall continues to be “really strong” into next year. He also noted positive customer feedback for the company’s new Megablock product, which is expected to start shipping from Houston in 2026.
“We’re seeing remarkable growth in the demand for AI and data center applications as hyperscalers and utilities have seen the versatility of the Megapack product. It increases reliability and relieves grid constraints,” he said.
Snyder also highlighted a “surge in residential solar demand in the US,” attributing the spike to recent policy changes that incentivize home installations. Tesla expects this trend to continue into 2026, helped by the rollout of a new solar lease product that makes adoption more affordable for homeowners.
Possible Solar Roof revival?
Perhaps the most intriguing part of Snyder’s remarks, however, was Tesla’s move to begin production of its “residential solar panel” in Buffalo, New York. He described the new panels as having “industry-leading aesthetics” and shape performance, language Tesla has used to market its Solar Roof tiles in the past.
“We also began production of our Tesla residential solar panel in our Buffalo factory, and we will be shipping that to customers starting Q1. The panel has industry-leading aesthetics and shape performance and demonstrates our continued commitment to US manufacturing,” Snyder said during the Q3 2025 earnings call.
Snyder did not explicitly name the product, though his reference to aesthetics has fueled speculation that Tesla may finally be preparing a large-scale and serious rollout of its Solar Roof line.
Originally unveiled in 2016, the Solar Roof was intended to transform rooftops into clean energy generators without compromising on design. However, despite early enthusiasm, production and installation volumes have remained limited for years. In 2023, a report from Wood Mackenzie claimed that there were only 3,000 operational Solar Roof installations across the United States at the time, far below forecasts. In response, the official Tesla Energy account on X stated that the report was “incorrect by a large margin.”
News
Tesla VP explains why end-to-end AI is the future of self-driving
Using examples from real-world driving, he said Tesla’s AI can learn subtle value judgments, the VP noted.
Tesla’s VP of AI/Autopilot software, Ashok Elluswamy, has offered a rare inside look at how the company’s AI system learns to drive. After speaking at the International Conference on Computer Vision, Elluswamy shared details of Tesla’s “end-to-end” neural network in a post on social media platform X.
How Tesla’s end-to-end system differs from competitors
As per Elluswamy’s post, most other autonomous driving companies rely on modular, sensor-heavy systems that separate perception, planning, and control. In contrast, Tesla’s approach, the VP stated, links all of these together into one continuously trained neural network. “The gradients flow all the way from controls to sensor inputs, thus optimizing the entire network holistically,” he explained.
He noted that the benefit of this architecture is scalability and alignment with human-like reasoning. Using examples from real-world driving, he said Tesla’s AI can learn subtle value judgments, such as deciding whether to drive around a puddle or briefly enter an empty oncoming lane. “Self-driving cars are constantly subject to mini-trolley problems,” Elluswamy wrote. “By training on human data, the robots learn values that are aligned with what humans value.”
This system, Elluswamy stressed, allows the AI to interpret nuanced intent, such as whether animals on the road intend to cross or stay put. These nuances are quite difficult to code manually.
Tackling scale, interpretability, and simulation
Elluswamy acknowledged that the challenges are immense. Tesla’s AI processes billions of “input tokens” from multiple cameras, navigation maps, and kinematic data. To handle that scale, the company’s global fleet provides what he called a “Niagara Falls of data,” generating the equivalent of 500 years of driving every day. Sophisticated data pipelines then curate the most valuable training samples.
Tesla built tools to make its network interpretable and testable. The company’s Generative Gaussian Splatting method can reconstruct 3D scenes in milliseconds and model dynamic objects without complex setup. Apart from this, Tesla’s neural world simulator allows engineers to safely test new driving models in realistic virtual environments, generating high-resolution, causal responses in real time.
Elluswamy concluded that this same architecture will eventually extend to Optimus, Tesla’s humanoid robot. “The work done here will tremendously benefit all of humanity,” he said, calling Tesla “the best place to work on AI on the planet currently.”
News
Tesla is releasing a modified version of FSD v14 for Hardware 3 owners: here’s when
Tesla is releasing a modified version of the Full Self-Driving (Supervised) version 14 suite for Hardware 3 owners, the company announced during the Q3 Earnings Call earlier this week.
Perhaps one of the most pertinent issues for Tesla owners right now is that those owners who have purchased vehicles before 2024 have been stuck with an older version of the company’s self-driving chip, known as Hardware 3 or AI3.
Owners with Hardware 3 vehicles have been stuck in a strange limbo for some time, wondering whether they should wait for the company’s official plans to upgrade them to the newer AI4 or even the to-be-released AI5 chip, or if they should purchase a new vehicle altogether. The upgrade would give them access to the latest Full Self-Driving suite releases, but it would likely cost a good bit of money.
For a while, these owners have been waiting for Tesla to give some sort of update on its plans, as the company has, in a way, danced around the issue by stating it would “take care” of those owners. The problem is, the definition of “take care” is subjective, and nobody knows if that means an upgrade or a free Tesla t-shirt.
Nevertheless, many owners finally got a tad bit more color earlier this week during the Earnings Call, when company executives finally outlined the beginning of a concrete plan to “take care” of HW3 vehicles.
Chief Financial Officer Vaibhav Taneja gave the first bit of the answer, as it is a personal issue to him. He also said that the vehicle he drives is a HW3 car, so it is impacted by the lack of upgrades.
He said:
“We have not completely given up on HW3. These customers are very important. They are early adopters. We will definitely take care of you guys.”
However, Tesla’s Head of AI, Ashok Elluswamy, gave some additional color, revealing that Tesla plans to launch v14 Lite for HW3 cars, and it will be released in Q2 of next year, tentatively:
“Once the v14 release series is fully done, we are planning on working on a v14 Lite version for hardware three. Probably expected in Q2 next year.”
This is somewhat of an answer, but some owners have already voiced discontent with this solution because HW3 will more than likely not be capable of what will be the “feature complete” version of FSD.
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