AI Tesla ile savaşıyor! Huang Renxun, Toyota ile işbirliği yaparak "AV endüstrisini oluşturuyor": Otomatik sürüş endüstrisinin değeri trilyonlarca doları bulacak
Nvidia CEO Huang Renxun announced today at the Consumer Electronics Show (CES) in the United States that they will collaborate with Toyota to develop autonomous driving technology based on Nvidia's technology, competing directly with TSL, and it is expected to impact the global automotive industry with visual computing AI. (Background: Huang Renxun announced the RTX5090 graphics card with 'twice the performance of the 4090', equipped with AI technology DLSS 4; Nvidia büyük yükseliş pushed Apple back to the top of the market value) (Background: Nvidia will launch the humanoid robot computing platform 'Jetson Thor' next year, will the physical AI ChatGPT era arrive?) Nvidia CEO Huang Renxun announced today at the Consumer Electronics Show (CES) in the United States that they will collaborate with Toyota, a company with annual sales of 100 million units, to jointly develop autonomous driving. Huang Renxun stated that the success of TSL and Waymo in the United States confirms the possibility of visual AI in the field of autonomous driving, and further indicates that the AV (Autonomous vehicles) industry will reach the potential of trillions of dollars. Huang Renxun stated that the operation of autonomous driving depends on three types of computers built into the vehicles, including the AI computing power-providing AI computing power computer, the simulation computer capable of detecting and judging the environment, and the data generation system. In different business cases, they may be one to two devices: I am really very happy that today we can announce that Toyota will develop next-generation autonomous driving vehicles together with Nvidia. There are one billion cars on the road each year, driving over a trillion miles, and in the future, all of these will be autonomous driving vehicles. This will be a very huge industry with a value of trillions of dollars, possibly growing at a rate of 50 billion dollars per year. Next-generation vehicle platform According to the contents of the slides, the autonomous driving platform developed by Nvidia is called 'AGX', and the autonomous driving computer is equipped with Nvidia Drive OS, designed for fully functional safety autonomous driving vehicles. In addition to the core AI computing power chip 'Sol', it also has a large number of cameras, radars, and ultrasonic sensors, and all the driving information detected by these sensors will be automatically transformed into appropriate driving judgments and output commands on the platform. Huang Renxun stated that the prototype vehicle of this platform computer also meets the highest ASIL safety automobile standards, with 70,000 lines of program code, 15,000 engineer hours of investment, and 2 million actual tests, which can be said to have undergone very rigorous testing before being made public. Omnimap real-time scene generation Huang Renxun also demonstrated the new system 'Omnimap' combining Omniverse and Nvidia Cosmos, showing the visual effects actually demonstrated on the AGX platform, accumulated through a large amount of remote calculations by the DGX computer. Each AGX is like having a supercomputer inside to depict the virtual Omniverse world. In various environments, the data accumulated by AGX can be used to compute neural networks and images through DGX, achieving more realistic and precise Omnimap depiction. In the background, DGX can simulate the possible changes in different scenes at different times, allowing scenes to appear in infinite variations, thus making the autonomous driving of AGX more mature. Under computer calculations, some driving data that only has a few hundred occurrences will be able to obtain several billion effective miles in Omniverse, adding higher standards for safety and autonomous driving. Based on physical capabilities, we can produce countless data to train AI in the background. This artificial intelligence is based on physical principles and is very accurate and reasonable. We are very excited about this because just like the development of the computer industry in the past, we will see similar progress in the field of autonomous driving in the coming years, and it will accelerate significantly in the next few years. Competing with TSL Although TSL was only mentioned at the beginning, in fact, Nvidia's collaboration with traditional car manufacturers such as Toyota is already a direct competition with TSL. The biggest difference between the current TSL's autonomous driving and Nvidia's collaboration with Toyota and other traditional car manufacturers is that the vehicle platform announced by Nvidia is a universal public version. From the appearance, test vehicles do not seem to be completely newly built autonomous driving vehicles, but rather traditional cars with computers and sensors added to achieve autonomous driving. This means that it may have a high threshold for traditional cars to upgrade to Nvidia's autonomous driving. In the future, these car manufacturers may not have the qualifications for every vehicle to obtain the autonomous driving system, depending on the compatibility of Nvidia's AGX with various car manufacturers. The highest probability is that car manufacturers will introduce completely new models for autonomous driving. Compared to TSL, which was originally designed for vehicles produced for autonomous driving, even if the current vehicles do not have complete autonomous driving capabilities, compared to Nvidia AGX and the solutions of traditional car manufacturers, there is a higher probability of painless upgrades. On the other hand, in terms of the logical solution of the autonomous driving solution, TSL has completely switched to a pure visual mode, without relying on any radar sensors for completely autonomous driving, while Nvidia AGX uses a mixed solution of visual image AI and laser radar to achieve it. This means that the two will have inherent differences in the development speed and system characteristics of autonomous driving. Although TSL has the advantage of being a pioneer, under the competition of Nvidia's large AI computing power investment, there may be situations where each has its own victory. Related reports BTC breaks through $102,000! Trump is rumored to relax tariff policies, Nvidia, TSMC ADR hits a new high Musk's xAI completes a $6 billion Series C financing, with participation from Nvidia, BlackRock, a16z... a group of industry big shots Nvidia intends to establish its overseas headquarters in Taiwan! Jiang Wan'an: Strive for landing in Taipei 〈AI confronts TSL! Huang Renxun collaborates with Toyota to 'build the AV industry': the value of autonomous driving will reach trillions of dollars〉This article was first published on BlockTempo, the most influential Blok chain news media in the dynamic trend.
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AI Tesla ile savaşıyor! Huang Renxun, Toyota ile işbirliği yaparak "AV endüstrisini oluşturuyor": Otomatik sürüş endüstrisinin değeri trilyonlarca doları bulacak
Nvidia CEO Huang Renxun announced today at the Consumer Electronics Show (CES) in the United States that they will collaborate with Toyota to develop autonomous driving technology based on Nvidia's technology, competing directly with TSL, and it is expected to impact the global automotive industry with visual computing AI. (Background: Huang Renxun announced the RTX5090 graphics card with 'twice the performance of the 4090', equipped with AI technology DLSS 4; Nvidia büyük yükseliş pushed Apple back to the top of the market value) (Background: Nvidia will launch the humanoid robot computing platform 'Jetson Thor' next year, will the physical AI ChatGPT era arrive?) Nvidia CEO Huang Renxun announced today at the Consumer Electronics Show (CES) in the United States that they will collaborate with Toyota, a company with annual sales of 100 million units, to jointly develop autonomous driving. Huang Renxun stated that the success of TSL and Waymo in the United States confirms the possibility of visual AI in the field of autonomous driving, and further indicates that the AV (Autonomous vehicles) industry will reach the potential of trillions of dollars. Huang Renxun stated that the operation of autonomous driving depends on three types of computers built into the vehicles, including the AI computing power-providing AI computing power computer, the simulation computer capable of detecting and judging the environment, and the data generation system. In different business cases, they may be one to two devices: I am really very happy that today we can announce that Toyota will develop next-generation autonomous driving vehicles together with Nvidia. There are one billion cars on the road each year, driving over a trillion miles, and in the future, all of these will be autonomous driving vehicles. This will be a very huge industry with a value of trillions of dollars, possibly growing at a rate of 50 billion dollars per year. Next-generation vehicle platform According to the contents of the slides, the autonomous driving platform developed by Nvidia is called 'AGX', and the autonomous driving computer is equipped with Nvidia Drive OS, designed for fully functional safety autonomous driving vehicles. In addition to the core AI computing power chip 'Sol', it also has a large number of cameras, radars, and ultrasonic sensors, and all the driving information detected by these sensors will be automatically transformed into appropriate driving judgments and output commands on the platform. Huang Renxun stated that the prototype vehicle of this platform computer also meets the highest ASIL safety automobile standards, with 70,000 lines of program code, 15,000 engineer hours of investment, and 2 million actual tests, which can be said to have undergone very rigorous testing before being made public. Omnimap real-time scene generation Huang Renxun also demonstrated the new system 'Omnimap' combining Omniverse and Nvidia Cosmos, showing the visual effects actually demonstrated on the AGX platform, accumulated through a large amount of remote calculations by the DGX computer. Each AGX is like having a supercomputer inside to depict the virtual Omniverse world. In various environments, the data accumulated by AGX can be used to compute neural networks and images through DGX, achieving more realistic and precise Omnimap depiction. In the background, DGX can simulate the possible changes in different scenes at different times, allowing scenes to appear in infinite variations, thus making the autonomous driving of AGX more mature. Under computer calculations, some driving data that only has a few hundred occurrences will be able to obtain several billion effective miles in Omniverse, adding higher standards for safety and autonomous driving. Based on physical capabilities, we can produce countless data to train AI in the background. This artificial intelligence is based on physical principles and is very accurate and reasonable. We are very excited about this because just like the development of the computer industry in the past, we will see similar progress in the field of autonomous driving in the coming years, and it will accelerate significantly in the next few years. Competing with TSL Although TSL was only mentioned at the beginning, in fact, Nvidia's collaboration with traditional car manufacturers such as Toyota is already a direct competition with TSL. The biggest difference between the current TSL's autonomous driving and Nvidia's collaboration with Toyota and other traditional car manufacturers is that the vehicle platform announced by Nvidia is a universal public version. From the appearance, test vehicles do not seem to be completely newly built autonomous driving vehicles, but rather traditional cars with computers and sensors added to achieve autonomous driving. This means that it may have a high threshold for traditional cars to upgrade to Nvidia's autonomous driving. In the future, these car manufacturers may not have the qualifications for every vehicle to obtain the autonomous driving system, depending on the compatibility of Nvidia's AGX with various car manufacturers. The highest probability is that car manufacturers will introduce completely new models for autonomous driving. Compared to TSL, which was originally designed for vehicles produced for autonomous driving, even if the current vehicles do not have complete autonomous driving capabilities, compared to Nvidia AGX and the solutions of traditional car manufacturers, there is a higher probability of painless upgrades. On the other hand, in terms of the logical solution of the autonomous driving solution, TSL has completely switched to a pure visual mode, without relying on any radar sensors for completely autonomous driving, while Nvidia AGX uses a mixed solution of visual image AI and laser radar to achieve it. This means that the two will have inherent differences in the development speed and system characteristics of autonomous driving. Although TSL has the advantage of being a pioneer, under the competition of Nvidia's large AI computing power investment, there may be situations where each has its own victory. Related reports BTC breaks through $102,000! Trump is rumored to relax tariff policies, Nvidia, TSMC ADR hits a new high Musk's xAI completes a $6 billion Series C financing, with participation from Nvidia, BlackRock, a16z... a group of industry big shots Nvidia intends to establish its overseas headquarters in Taiwan! Jiang Wan'an: Strive for landing in Taipei 〈AI confronts TSL! Huang Renxun collaborates with Toyota to 'build the AV industry': the value of autonomous driving will reach trillions of dollars〉This article was first published on BlockTempo, the most influential Blok chain news media in the dynamic trend.