Elon Muskknown for its ability to generate great expectations, has once again turned on the spotlight with a bold proposal: the creation of a robotaxi completely autonomous for 2026.
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This initiative, an essential part of his vision for Tesla, promises to transform mobility as we know it.
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However, this ambitious prediction has not convinced everyone, including NVIDIAa key player in the technological development of vehicle autonomy systems.
In a recent interview, Ali Kanivice president of automotive at NVIDIA, approached Musk’s statements with a tone of well-founded skepticism.
“We are not close to achieving it. It is very difficult”he stated forcefully. These words highlight the numerous challenges facing the industry in its race towards full autonomy, casting doubt on the possibility of meeting the schedule proposed by Tesla.
A dream that bumps into reality
NVIDIA, which has built its reputation as a leader in automotive hardware and software, works with giants such as Mercedes-Benz, Volvo and Jaguar Land Rover.
The company has been instrumental in significant advancements in driver assistance systems (ADAS), but Kani maintains that achieving full autonomy is a monumental task.
The vice president highlighted the technological requirements necessary to make an operational and safe robotaxi a reality.
Among them, he mentioned the need for much higher processing powers, amplified memory bandwidths, next-generation LiDAR sensors and radars, and redundant algorithms capable of working simultaneously. “The complexity of these systems is staggering and we have not yet reached a point where it is possible to implement them on a large scale”he explained.
Tesla persists in his vision
For his part, Elon Musk does not seem fazed by the criticism. Tesla continues to bet on its Full Self-Driving (FSD) system, a technology based on computer vision and machine learning that, according to Musk, could completely eliminate the need for human intervention in the near future.

However, this approach has been described as risky. Many experts believe that relying solely on cameras and data processingleaving aside additional sensors such as LiDAR, could limit the effectiveness of the system in unforeseen situations.
Still, Tesla maintains its strategy, trusting that the accumulation of data and the continuous improvement of its software will give it a competitive advantage.
Security: the decisive obstacle
One of the most critical points in the debate about total autonomy is security. Ali Kani noted that current systems often have unpredictable failures, such as phantom braking or unnecessary acceleration, which could endanger users.
“The industry cannot afford a mistake. “If one company makes a significant mistake, it will set everyone back for years.”Kani warned.
This comment reflects growing concern about the impact that failures in autonomous driving systems could have, both on public trust and regulation of the sector.
Although the progress has been impressive, the massive accumulation of data and the development of algorithms More sophisticated technologies are essential to ensure these vehicles are completely safe before commercial deployment.
Despite the differences between Tesla and NVIDIAit is undeniable that both companies are driving technology towards a future of autonomous mobility.
However, while Musk projects a near horizon for robotaxisNVIDIA and other industry experts believe that full autonomy requires more time and significant advances.
Kani emphasized that although automotive software development has evolved rapidly, the industry is far from reaching the level needed for a fully functional robotaxi in the next three years.
This position highlights the importance of approaching technological progress with a realistic perspective, prioritizing safety and efficiency over speed.
The debate between Tesla and NVIDIA highlights the balance between vision and pragmatism in the race towards vehicle autonomy. As Elon Musk envisions a future revolutionized by autonomous robotaxis in the near future, NVIDIA calls for caution, highlighting the many challenges that still need to be overcome.
What is clear is that the path to total autonomy will be long and complex. Although timelines may vary, collaboration and constant advancement will remain essential to making this transformative technology a reality.
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