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Tesla's new data pipeline and deep learning patent paves way for quicker autonomous driving improvements
Tesla’s Neural Net continues to improve and become more advanced on a daily basis, but it appears that the electric car maker is making sure that it will evolve at an even faster rate in the future. A recent patent, for example, would allow Tesla’s autonomous driving systems to work more efficiently, thanks to a new data pipeline focused on optimized image processing.
Tesla’s patent for “Data Pipeline and Deep Learning System for Autonomous Driving” was published on December 26. The idea behind the patent is to revolutionize and improve upon past deep learning systems that have been used for autonomous driving vehicles. In the past, these systems have used “captured sensor data” to retrieve information.
Tesla recognizes the need for new sensors when data becomes more complex. According to the electric car maker’s patent, there is “a need for a customized data pipeline that can maximize the signal information from the captured sensor data and provide a higher level of signal information to the deep learning network for deep learning analysis.”
The system described in this patent would capture an image using any of the sensors or cameras on the vehicle. In this case, this would describe a high dynamic range camera, camera sensor, radar sensor, or ultrasonic sensor. The image would then be broken down through a “high-pass” or ‘lo-pass” filter and a series of processors would then decipher what the image means.
The flowchart below describes what the process of the vehicle learning the information would look like. “Receive Sensor Data” is the first portion of this process. Then, data will be broken down and pre-processed for the system to then begin its “Deep Learning Analysis.” The results will then be passed along to the vehicle’s Artificial Intelligence Processor to be utilized during vehicle control.
In another process, the series of information that is retrieved from these images will be compared to data compiled from other Tesla users on a global scale. This will alleviate concerns that drivers may have that the system could perform the wrong process when driving autonomously. The aim of the patent is to create a safe driving experience and improve upon the already solid performance of Tesla’s autonomous driving software, and do so in a process that is more efficient than before.
By using this process, Tesla is able to maintain as much resolution as possible from the images captured by its vehicles’ cameras and sensors. This then allows the Neural Network to more efficiently learn from the data packets that it is receiving. This allows the Neural Network to work with better images in a more efficient manner as well, which opens the doors to faster autonomous driving improvements. These efficiencies would work very well with the additional horsepower offered by Tesla’s Hardware 3 computer, which is specifically designed for full self-driving with built-in redundancies.
Building upon the foundation that Tesla has already laid down in terms of its Full Self Driving suite, the recent patent suggests that the company is now attempting to narrow down on the finer points of its software’s performance. The addition of this patent will not only create a safer driving experience for owners of Tesla vehicles but will bring the quickly approaching future of fully-autonomous vehicles even closer to completion.
The full text of Tesla’s new data pipeline and deep learning patent could be viewed here.
News
Tesla seeks approval to test FSD Supervised in new Swedish city
Tesla has applied to conduct local Full Self-Driving (Supervised) testing in the city of Jönköping, Sweden.
Tesla has applied to conduct local Full Self-Driving (Supervised) testing in the city of Jönköping, Sweden.
As per local outlet Jönköpings-Posten, Tesla has contacted the municipality with a request to begin FSD (Supervised) tests in the city. The company has already received approval to test its Full Self-Driving (Supervised) software in several Swedish municipalities, as well as on the national road network.
Sofia Bennerstål, Tesla’s Head of Public Policy for Northern Europe, confirmed that an application has been submitted for FSD’s potential tests in Jönköping.
“I can confirm that we have submitted an application, but I cannot say much more about it,” Bennerstål told the news outlet. She also stated that Tesla is “satisfied with the tests” in the region so far.
The planned tests in Jönköping would involve a limited number of Tesla-owned vehicles. Trained Tesla safety drivers would remain behind the wheel and be prepared to intervene if necessary.
Tesla previously began testing in Nacka municipality after receiving local approval. At the time, the company stated that cooperation between authorities, municipalities, and industry enables technological progress and helps integrate future transport systems into real-world traffic conditions, as noted in an Allt Om Elbil report.
If approved, Jönköping would become the latest Swedish municipality to allow local Full Self-Driving (Supervised) testing.
Tesla’s Swedish testing program is part of the company’s efforts to validate its supervised autonomous driving software in everyday traffic environments. Municipal approvals allow Tesla to gather data in urban settings that include roundabouts, complex intersections, and mixed traffic conditions.
Sweden has become an increasingly active testing ground for Tesla’s driver-assistance software in Europe, with regulatory coordination between local authorities and national agencies enabling structured pilot programs.
Elon Musk
Microsoft partners with Starlink to expand rural internet access worldwide
The update was shared ahead of Mobile World Congress.
Microsoft has announced a new collaboration with Starlink as part of its expanding digital access strategy, following the company’s claim that it has extended internet connectivity coverage to more than 299 million people worldwide.
The update was shared ahead of Mobile World Congress, where Microsoft detailed how it surpassed its original goal of bringing internet access to 250 million people by the end of 2025.
In a blog post, Microsoft confirmed that it is now working with Starlink to expand connectivity in rural and hard-to-reach regions.
“Through our collaboration with Starlink, Microsoft is combining low-Earth orbit satellite connectivity with community-based deployment models and local ecosystem partnerships,” the company wrote.
The partnership is designed to complement Microsoft’s existing work with local internet providers and infrastructure companies across Africa, Latin America, and India, among other areas. Microsoft noted that traditional infrastructure alone cannot meet demand in some regions, making low-Earth orbit satellite connectivity an important addition.
Kenya was cited as an early example. Working with Starlink and local provider Mawingu Networks, Microsoft is supporting connectivity for 450 community hubs in rural and underserved areas. These hubs include farmer cooperatives, aggregation centers, and digital access facilities intended to support agricultural productivity and AI-enabled services.
Microsoft stated that 2.2 billion people globally remain offline, and that connectivity gaps risk widening as AI adoption accelerates.
Starlink’s expanding constellation, now numbering more than 9,700 satellites in orbit, provides near-global coverage, making it one of the few systems capable of delivering broadband to remote regions without relying on terrestrial infrastructure.
Starlink is expected to grow even more in the coming years as well, especially as SpaceX transitions its fleet to Starship, which is capable of carrying significantly larger payloads compared to its current workhorse, the Falcon 9.
Elon Musk
Tesla expands US LFP battery supply with LG Energy Solution deal: report
The report was initially published by TheElec, citing industry sources.
LG Energy Solution (LGES) will manufacture lithium iron phosphate (LFP) energy storage system (ESS) batteries for Tesla at its Lansing, Michigan facility.
The report was initially published by TheElec, citing industry sources.
LG Energy Solution’s Lansing plant, formerly known as Ultium Cells 3, was previously operated as a joint venture with General Motors. LGES acquired GM’s stake in May 2025 and now fully owns the site. With a production capacity of 50 GWh per year, it is one of the company’s largest facilities in North America.
LG Energy Solution is converting part of the Lansing factory to produce LFP batteries for energy storage systems. Equipment orders for the new lines have already been placed, and mass production is reportedly expected to begin in the second half of next year.
Last July, LG Energy Solution disclosed a 5.94 trillion won battery supply agreement running from August 2027 to July 2030. While the company did not name the customer, industry sources pointed to Tesla as the buyer.
Tesla has primarily used CATL’s prismatic batteries for its Megapack systems. The move to source prismatic LFP cells from LG Energy Solution’s U.S. plant could then be seen as part of Tesla’s efforts to bolster its North American supply base for its energy storage business.
For the Lansing conversion, LG Energy Solution reportedly plans to use electrode equipment originally ordered under its Ultium Cells venture with General Motors. Suppliers reportedly include CIS and Hirano Tecseed for electrode systems, TSI for mixing equipment, CK Solution for heat exhaust systems, A-Pro for formation equipment, and Shinjin Mtech for assembly kits.
Tesla currently manufactures energy storage products at facilities in California and Shanghai, though another Megafactory that produces the Megapack is also expected to be built in Texas. As per recent reports, the Texas Megafactory recently advanced with a major property sale.
Tesla seeks approval to test FSD Supervised in new Swedish city
Microsoft partners with Starlink to expand rural internet access worldwide
