Andrej Karpathy, former Tesla Autopilot Director, offers a fascinating perspective on Artificial General Intelligence (AGI) by drawing parallels with the evolution of self-driving technology. As the world grapples with the implications of AGI, Karpathy suggests that the trajectory of autonomous vehicles provides valuable insights into what AGI might entail and its impact on society.

The blog post has since been deleted, but you can still check it out here; Karpathy defines AGI as an autonomous system exceeding human capabilities in most economically valuable tasks. This definition hinges on two criteria: complete autonomy and broad economic applicability. According to Karpathy, the journey of self-driving technology exemplifies the societal dynamics of increasing automation and, by extension, AGI’s potential evolution.

The Gradual Rise of Automation

Self-driving technology stands out due to its high visibility, significant economic footprint, large human workforce, and the complex challenge of automating driving. Unlike other sectors that have seen automation, the path to self-driving is a prime example of AGI’s characteristics: accessibility, economic importance, workforce impact, and technical challenge.

Karpathy outlines the gradual development of driving automation. Initially, vehicles featured Level 2 driver assistance, where AI collaborates with humans in navigation, handling many low-level driving aspects while allowing human intervention. This partial automation is analogous to AI tools in various industries, like GitHub Copilot in programming, highlighting the incremental nature of AI advancement.

The leap to full automation, as seen in Waymo’s driverless cars, marks a significant milestone. In cities like San Francisco, Waymo offers autonomous rides in a small, geo-fenced area, however, it helps showcase a future where AI will surpass human driving abilities. The transition to full autonomy will depend on public awareness, trust, preferences, and supply constraints in creating a large automated fleet.

Global Expansion: Challenges and Opportunities

The globalization of full automation, Karpathy notes, is a gradual, resource-intensive process. Waymo’s current limitations to specific cities illustrate the challenges of expanding automated services, including adapting to local conditions and regulations. This expansion mirrors the broader trajectory of AGI deployment across various sectors, where scalability is both achievable and gradual.

Society’s reaction to self-driving technology parallels AGI’s potential impact. Despite significant advancements, public awareness and acceptance vary. Some view autonomous vehicles with curiosity and skepticism, while others adapt quickly. This range of responses suggests how society might adapt to AGI in various industries.

Economically, self-driving technology has both eliminated and created jobs. While driver roles are phased out, new positions in data labeling, remote support, fleet maintenance, and sensor technology emerge. This transformation reflects the broader economic implications of AGI, where work is not merely eliminated but refactored and reshaped.

The competitive landscape in self-driving technology, with companies like Waymo, Tesla, and others, mirrors the expected consolidation in AGI-related industries. As with self-driving, only a few companies may dominate the AGI space after an initial burst of growth and competition.

Karpathy envisions AGI as a gradual, society-involved evolution rather than a sudden, uncontrollable leap. Just as self-driving technology is transforming transportation, making it safer and more efficient, AGI promises to reshape various sectors.

Tesla has always responded quickly to changes required by the National Highway Traffic Safety Administration, but what occurred during the latest recall has set a new standard. NHTSA published a recall notice about the rearview camera display in 2023 Model S, Model X, and Model Y vehicles equipped with Hardware 4.0. By the time the government body issued it, Tesla had already fixed it thanks to an over-the-air update weeks prior.

Rapid Identification and Response

The problem, identified as a bug that occasionally prevented the rearview camera image from displaying, could have decreased the driver’s rear visibility. Tesla first became aware of the issue on December 26, 2023, and promptly initiated an investigation. The root cause was found to be insufficient inter-integrated circuit protocol stability, which occasionally failed to activate the rearview camera view.

Tesla developed a fix within just two days of identifying the issue. The fix was initially deployed to a small number of vehicles on December 28, 2023, as a test. Following the successful trial, the update, labeled 2023.44.30.7, was rolled out to all affected vehicles on January 3, 2024. The recall notice from the NHTSA went to Tesla on January 23, 2024 – a full 20 days after the issue had already been addressed.

Debate Over the Term ‘Recall’

However, despite Tesla’s response, which fixed nearly 200,000 cars overnight, being used to showcase the unique advantages of its software-centric approach to vehicle design and maintenance, the legacy media used the recall to run the usual negative stories on the company.

This incident has once again sparked a debate within the Tesla community and beyond regarding using the term “recall” for issues addressed through OTA software updates. Tesla’s approach differs significantly from traditional automotive recall processes, as it eliminates the need for physical vehicle servicing. The term “recall” often implies a more laborious and inconvenient process for vehicle owners, whereas Tesla’s software updates are quick and seamless and do not disrupt the owner’s use of the vehicle.

Mercedes-Benz’s introduction of turquoise Automated Driving Marker Lights for its DRIVE PILOT system, following the SAE J3134 Recommended Practice, marks another step in the evolution of automated driving technology. This move raises the question: Should Tesla and all automakers developing autonomous driving features follow Mercedes’ lead? Considering the US’s lack of a national regulatory framework and the implications for the future of autonomous driving, this topic will get more significant as technology evolves.

Establishing a Common Language for Automated Vehicles

Mercedes-Benz’s initiative underscores the importance of a standardized visual communication method for automated vehicles. Such standardization would help inform all drivers and pedestrians when vehicles operate autonomously, improving road safety and predictability. If Tesla adopted this system, it could contribute significantly to establishing a universal language for automated cars, fostering a safer and more efficient integration into the existing traffic ecosystem.

There is still a long road ahead to fully autonomous driving, mainly because the technology is dealing with human behavior, which, at times, can be unpredictable. But this kind of signal could alert other FSD vehicles to travel together, lessening the risk of human error during those long road trips.

Risk of Misinterpretation

However, a significant concern for Tesla in adopting such a strategy is the potential for increased negative attention from EV critics. The move, known as ‘rolling coal,’ where diesel truck drivers intentionally emit large amounts of exhaust fumes near EVs, highlights tensions between traditional vehicle enthusiasts and the EV community. Introducing conspicuous turquoise lights might exacerbate this issue, making Tesla vehicles more of a target for such antagonistic behavior.

While using ADS marker lights offers clear benefits, concerns have been raised about their potential to attract intentional interference from other road users. There is also the risk of misinterpretation of these signals, which could lead to safety hazards. Tesla would need to consider these aspects carefully, ensuring that any implementation of such technology is accompanied by widespread public education and awareness campaigns to mitigate these risks.

There could also be an added risk of being a target on the road. If a pedestrian or vehicle knows that a vehicle is autonomous, they may take additional risks in passing or crossing in front of the vehicle, thinking that the vehicle will yield or stop for them.

Navigating the Regulatory Maze and Costs

Implementing turquoise lights as an indicator for full self-driving mode involves navigating complex legal and regulatory landscapes. Currently, there is no nationwide framework in the US for such technology. Mercedes only has approval for the new light in California and Nevada. Standardization requires extensive discussions and adaptations to the national road traffic and regulatory frameworks. Tesla would need to engage in these conversations actively and adapt to evolving standards, which could be resource-intensive.

However, Tesla is a leader in this sector and has experience changing opinions and getting support from competitors. Most automakers have announced plans to adopt Tesla’s NACS charging system, making the company’s charging technology the winner in North America. Others will notice and likely follow if Tesla considers a new light for its FSD.

Additionally, integrating these lights into Tesla’s existing vehicle designs might require significant engineering adjustments, adding to the cost and complexity of their vehicles. Who would pay for the retrofit of the current fleet or would it only apply to new vehicles?

Enhancing Accessibility and Safety for Persons with Disabilities

One of the critical considerations for automated driving systems is their potential to provide mobility solutions for individuals who cannot obtain a driver’s license due to various impairments. Clear visual signals like turquoise lights could make these technologies more accessible and understandable to all road users, including those with disabilities. By adopting such features, Tesla would be taking a step forward in creating inclusive and universally accessible transportation solutions.

The decision for Tesla to adopt turquoise lights similar to Mercedes-Benz for indicating full self-driving mode is multifaceted, involving considerations of safety, inclusivity, regulatory compliance, and public perception. As the landscape of automated driving continues to evolve, industry leaders like Tesla must navigate these challenges thoughtfully, contributing to a future where autonomous vehicles are seamlessly integrated into our daily lives, enhancing accessibility and safety for all road users.