self-driving AI News & Updates
Tesla Expands Driverless Robotaxi Operations to Dallas and Houston
Tesla has launched its robotaxi service in Dallas and Houston, expanding beyond its initial Austin deployment where driverless operations began in January 2026. The company now operates fully autonomous vehicles without safety drivers in three Texas cities, though early tracking data suggests limited initial fleet sizes in the new markets. Tesla's Austin fleet has reported 14 crashes since launch according to a February filing.
Skynet Chance (+0.01%): Deployment of autonomous systems in real-world environments without human oversight increases the surface area for potential loss of control scenarios, though the limited scope and reported crash rate suggest current systems remain constrained. The expansion demonstrates growing confidence in removing human safety monitors.
Skynet Date (+0 days): Commercial deployment of autonomous systems without safety drivers represents incremental progress toward more autonomous AI systems in critical applications, slightly accelerating the timeline. However, the limited fleet size and regional scope suggest modest rather than dramatic acceleration.
AGI Progress (+0.01%): Successful deployment of fully autonomous vehicles in multiple cities demonstrates meaningful progress in real-world perception, decision-making, and navigation capabilities that are components of general intelligence. The removal of safety drivers indicates confidence in the system's reliability across diverse scenarios.
AGI Date (+0 days): Expansion of driverless robotaxi operations to new cities shows acceleration in deploying autonomous AI systems at scale, suggesting faster progress toward more capable and generalizable AI systems. The willingness to operate without safety monitors indicates advancing maturity of the underlying AI technology.
Tesla Discontinues Dojo AI Supercomputer Project, Shifts to External Partners
Tesla is shutting down its Dojo AI training supercomputer project and disbanding the team, with lead engineer Peter Bannon leaving the company. The company is pivoting to rely more heavily on external partners like Nvidia and AMD for compute power, while signing a $16.5 billion deal with Samsung for AI6 inference chips. This represents a major strategic shift away from in-house chip development that CEO Elon Musk had previously touted as crucial for achieving full self-driving capabilities.
Skynet Chance (-0.03%): Tesla's shift away from developing proprietary AI hardware reduces potential concentration of advanced AI capabilities under a single company's control. Increased reliance on established vendors like Nvidia creates more distributed oversight and standardization in AI development infrastructure.
Skynet Date (+1 days): The abandonment of Dojo represents a setback in Tesla's AI ambitions and suggests slower progress toward autonomous systems that could pose control risks. This strategic retreat likely delays aggressive AI capability development in the automotive sector.
AGI Progress (-0.04%): Tesla's retreat from custom AI hardware development represents a step back from vertical integration in AI systems. The failure of Dojo, which was designed to process vast amounts of video data for autonomous driving, suggests challenges in scaling specialized AI compute infrastructure.
AGI Date (+0 days): While Tesla's pivot to external partners may provide access to more mature hardware, the abandonment of Dojo likely delays Tesla's specific contributions to AGI through autonomous vehicle AI. However, increased reliance on Nvidia may accelerate overall progress through established infrastructure.