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Tesla patent reveals Autopilot’s efficient method to enhance object identification
Tesla has a new patent that aims to improve the accuracy and efficiency of identifying objects inside images, as captured through its vehicle’s Autopilot cameras.
The patent, titled “Enhanced Object Detection for Autonomous Vehicles Based on Field View,” outlines Tesla’s plan to focus high computational requirements on objects that are more critical for self-driving, while downsampling less critical image data.
The patent states, “There may be…image sensors positioned at different locations on the vehicle. Certain image sensors, such as forward-facing image sensors, may thus obtain images of a real-world location towards which the vehicle is heading. It may be appreciated that a portion of these images may tend to depict pedestrians, vehicles, obstacles, and so on that are important in applications such as autonomous vehicle navigation.”
After determining the type of object that’s before a vehicle, “the particular field of view may be cropped from an input image. A remaining portion of the input image may then be downsampled. The high resolution cropped portion of the input image and the lower resolution downsampled portion of the input image may then be analyzed by an object detector.”
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- Tesla Autopilot (Source: Elon Musk | Twitter)
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- Credit: YouTube | JuliansRandomProject
Tesla vehicles utilize a series of eight cameras, or sensors, to identify and recognize real-world objects. The cameras obtain these images, which are sometimes pedestrians, other vehicles, animals, or other obstacles that are important to not only the safety of the driver in the Tesla vehicle but others as well. It is crucial that the cameras recognize these objects accurately and in real-time without any delay.
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- Tesla’s “Enhanced Object Detection for Autonomous Vehicles Based on Field View.” (Credit: U.S. Patent Office)
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- Tesla’s “Enhanced Object Detection for Autonomous Vehicles Based on Field View.” (Credit: U.S. Patent Office)
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- Tesla’s “Enhanced Object Detection for Autonomous Vehicles Based on Field View.” (Credit: U.S. Patent Office)
Tesla CEO Elon Musk has mentioned in the past that Autopilot’s core code and 3D labeling is being finished. Once completed, the electric carmaker can efficiently roll out more functionalities of its Full Self-Driving suite.
3D labeling is an integral part of the FSD suite because it allows the Neural Network to process information more efficiently and can help Tesla’s vehicles learn about rare and unforeseen occurrences on the road. Anyone who has ever ridden in a car knows that expecting the unexpected is one of the best ways to avoid an accident. With over 3 billion miles of Autopilot driving under the company’s belt, Teslas have seen a lot more than any human being will ever see.
The importance of 3D labeling and accurate object identification is crucial to Tesla’s eventual rollout of a “feature complete” Full Self-Driving suite. Tesla has continued to improve driving visualizations in vehicles that operate with Hardware 3 by recognizing objects on the road that could be a barrier between the vehicle and safe travel. It seems the company’s primary focus with this patent is to dial in on the effectiveness of the car’s cameras and sensors, allowing for a more accurate depiction of what lies on the road ahead.
Read Tesla’s patent for Enhanced Object Detection for Autonomous Vehicles Based on Field View below.
ENHANCED OBJECT DETECTION FOR AUTONOMOUS VEHICLES BASED ON FIELD VIEW by Joey Klender on Scribd
Elon Musk
Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online
Elon Musk shared his update in a recent post on social media platform X.
xAI has brought its Colossus 2 supercomputer online, making it the first gigawatt-scale AI training cluster in the world, and it’s about to get even bigger in a few months.
Elon Musk shared his update in a recent post on social media platform X.
Colossus 2 goes live
The Colossus 2 supercomputer, together with its predecessor, Colossus 1, are used by xAI to primarily train and refine the company’s Grok large language model. In a post on X, Musk stated that Colossus 2 is already operational, making it the first gigawatt training cluster in the world.
But what’s even more remarkable is that it would be upgraded to 1.5 GW of power in April. Even in its current iteration, however, the Colossus 2 supercomputer already exceeds the peak demand of San Francisco.
Commentary from users of the social media platform highlighted the speed of execution behind the project. Colossus 1 went from site preparation to full operation in 122 days, while Colossus 2 went live by crossing the 1-GW barrier and is targeting a total capacity of roughly 2 GW. This far exceeds the speed of xAI’s primary rivals.
Funding fuels rapid expansion
xAI’s Colossus 2 launch follows xAI’s recently closed, upsized $20 billion Series E funding round, which exceeded its initial $15 billion target. The company said the capital will be used to accelerate infrastructure scaling and AI product development.
The round attracted a broad group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group. Strategic partners NVIDIA and Cisco also continued their support, helping xAI build what it describes as the world’s largest GPU clusters.
xAI said the funding will accelerate its infrastructure buildout, enable rapid deployment of AI products to billions of users, and support research tied to its mission of understanding the universe. The company noted that its Colossus 1 and 2 systems now represent more than one million H100 GPU equivalents, alongside recent releases including the Grok 4 series, Grok Voice, and Grok Imagine. Training is also already underway for its next flagship model, Grok 5.
Elon Musk
Tesla AI5 chip nears completion, Elon Musk teases 9-month development cadence
The Tesla CEO shared his recent insights in a post on social media platform X.
Tesla’s next-generation AI5 chip is nearly complete, and work on its successor is already underway, as per a recent update from Elon Musk.
The Tesla CEO shared his recent insights in a post on social media platform X.
Musk details AI chip roadmap
In his post, Elon Musk stated that Tesla’s AI5 chip design is “almost done,” while AI6 has already entered early development. Musk added that Tesla plans to continue iterating rapidly, with AI7, AI8, AI9, and future generations targeting a nine-month design cycle.
He also noted that Tesla’s in-house chips could become the highest-volume AI processors in the world. Musk framed his update as a recruiting message, encouraging engineers to join Tesla’s AI and chip development teams.
Tesla community member Herbert Ong highlighted the strategic importance of the timeline, noting that faster chip cycles enable quicker learning, faster iteration, and a compounding advantage in AI and autonomy that becomes increasingly difficult for competitors to close.
AI5 manufacturing takes shape
Musk’s comments align with earlier reporting on AI5’s production plans. In December, it was reported that Samsung is preparing to manufacture Tesla’s AI5 chip, accelerating hiring for experienced engineers to support U.S. production and address complex foundry challenges.
Samsung is one of two suppliers selected for AI5, alongside TSMC. The companies are expected to produce different versions of the AI5 chip, with TSMC reportedly using a 3nm process and Samsung using a 2nm process.
Musk has previously stated that while different foundries translate chip designs into physical silicon in different ways, the goal is for both versions of the Tesla AI5 chip to operate identically. AI5 will succeed Tesla’s current AI4 hardware, formerly known as Hardware 4, and is expected to support the company’s Full Self-Driving system as well as other AI-driven efforts, including Optimus.
News
Tesla Model Y and Model 3 named safest vehicles tested by ANCAP in 2025
According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025.
The Tesla Model Y recorded the highest overall safety score of any vehicle tested by ANCAP in 2025. The Tesla Model 3 also delivered strong results, reinforcing the automaker’s safety leadership in Australia and New Zealand.
According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025. ANCAP’s 2025 tests evaluated vehicles across four key pillars: Adult Occupant Protection, Child Occupant Protection, Vulnerable Road User Protection, and Safety Assist technologies.
The Model Y posted consistently strong results in all four categories, distinguishing itself through a system-based safety approach that combines structural crash protection with advanced driver-assistance features such as autonomous emergency braking, lane support, and driver monitoring.
This marked the second time the Model Y has topped ANCAP’s annual safety rankings. The Model Y’s previous version was also ANCAP’s top performer in 2022.
The Tesla Model 3 also delivered a strong performance in ANCAP’s 2025 tests, contributing to Tesla’s broader safety presence across segments. Similar to the Model Y, the Model 3 also earned impressive scores across the ANCAP’s four pillars. This made the vehicle the top performer in the Medium Car category.
ANCAP Chief Executive Officer Carla Hoorweg stated that the results highlight a growing industry shift toward integrated safety design, with improvements in technologies such as autonomous emergency braking and lane support translating into meaningful real-world protection.
“ANCAP’s testing continues to reinforce a clear message: the safest vehicles are those designed with safety as a system, not a checklist. The top performers this year delivered consistent results across physical crash protection, crash avoidance and vulnerable road user safety, rather than relying on strength in a single area.
“We are also seeing increasing alignment between ANCAP’s test requirements and the safety technologies that genuinely matter on Australian and New Zealand roads. Improvements in autonomous emergency braking, lane support, and driver monitoring systems are translating into more robust protection,” Hoorweg said.
Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online
Tesla AI5 chip nears completion, Elon Musk teases 9-month development cadence
