Elon Musk has made several predictions about when Tesla’s Full Self-Driving (FSD) software will achieve Level 4 or Level 5 autonomy, but none of them have come true. In his most recent prediction, Musk said that FSD would reach Level 4 or Level 5 before the end of this year. However, it is unclear what evidence he has to support this claim.

FSD Beta

Tesla’s FSD Beta software can currently drive in a limited number of situations, but it still requires a human driver to be ready to take over at all times. For example, FSD Beta can navigate on highways and change lanes, but it cannot handle complex intersections or driving in cities.


The Dojo supercomputer, scheduled to launch next month, could help Tesla improve the performance of its FSD software. Dojo is a massive supercomputer that will be able to process the massive amount of data that Tesla collects from its fleet of vehicles. This data could be used to train FSD software to handle more complex situations.


However, it is still too early to say whether Dojo will be enough to enable Level 4 or Level 5 autonomy. Tesla has a long way to go before its FSD software can drive safely in all conditions.

It is also worth noting that other companies are also working on developing self-driving cars. Waymo, Cruise, and Argo AI are all developing Level 4 or Level 5 autonomous vehicles. One of these companies may achieve Level 4 or Level 5 autonomy before Tesla does.

Overall, it is too early to say whether Tesla’s FSD software will achieve Level 4 or Level 5 autonomy before the end of this year. Musk’s prediction is certainly ambitious, but it is possible that Dojo could help Tesla make significant progress in the coming months.

Here are some pros and cons associated with the development of fully autonomous driving systems:


  • Safety: Autonomous driving systems have the potential to significantly reduce human error, which is a leading cause of accidents on the roads. By removing human drivers from the equation, autonomous vehicles can potentially improve road safety and save lives.
  • Efficiency and Traffic Flow: Autonomous vehicles can be programmed to optimize traffic flow, reduce congestion, and minimize fuel consumption. They can communicate with each other and the surrounding infrastructure, leading to smoother traffic patterns and more efficient use of road space.
  • Accessibility: Autonomous vehicles can increase mobility for people who cannot drive, such as the elderly or individuals with disabilities. They can provide greater independence and access to transportation options.
  • Productivity and Convenience: With autonomous driving, passengers can use their travel time more productively. Instead of focusing on driving, they can work, relax, or engage in other activities during their journeys.


  • Technological Challenges: Achieving fully autonomous driving is a complex task that requires overcoming significant technological challenges. Perception, decision-making, and reacting to unpredictable situations on the road remain ongoing areas of research and development.
  • 2. Legal and Regulatory Issues: Implementing autonomous driving systems involves navigating legal and regulatory frameworks. Determining liability in accidents involving autonomous vehicles, establishing safety standards, and ensuring compliance with existing laws are complex issues that must be addressed.
  • Ethical Considerations: Autonomous vehicles may need to make split-second decisions when harm is unavoidable. Programming these vehicles to make ethical choices, such as prioritizing the safety of passengers or pedestrians, poses ethical dilemmas that require careful consideration.
  • Job Displacement: The widespread adoption of autonomous vehicles could potentially lead to job displacement for professional drivers, such as truck and taxi drivers. Transitioning to a driverless future would require strategies to mitigate the impact on affected workers.
  • Cybersecurity and Privacy: Autonomous vehicles rely heavily on complex computer systems and connectivity, making them susceptible to cybersecurity threats. Ensuring the security and privacy of autonomous driving technology is crucial to protect against hacking, unauthorized access, and data breaches.


The development of fully autonomous driving systems has good advantages and significant challenges. On the positive side, autonomous vehicles have the potential to enhance road safety, improve traffic flow, increase accessibility, and provide convenience to passengers. However, technological, legal, ethical, and societal considerations also need to be carefully addressed.

While autonomous driving technology continues to progress, it’s important to approach timelines and predictions with caution, as the complexity of achieving full autonomy is still being navigated. It requires advancements in perception, decision-making, and adapting to unpredictable situations on the road.

Additionally, legal and regulatory frameworks need to be established, ethical dilemmas must be addressed, and concerns related to job displacement, cybersecurity, and privacy need careful consideration.

As the development of autonomous driving technology moves forward, ongoing research, collaboration between stakeholders, and continuous improvement of safety and security measures are necessary to unlock the potential benefits while ensuring the responsible and sustainable integration of autonomous vehicles into our transportation systems.

AFP via Drive Tesla Canada

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