The Accelerationist

MUSK CONSIDERS MERGING SPACEX AND XAI SpaceX and xAI are reportedly in talks to merge, which would unite SpaceX, Starlink, X, and Grok AI under one company, according to Reuters. The discussions come ahead of SpaceX’s anticipated public debut.

BREAKING: Tesla Model Y Robotaxi with literally no one in the car spotted driving itself on public roads in Austin, Texas! A new age has begun 🤖

6 Billion FSD Miles - When and Why? Faster that you might think... When: If FSD remains only approved in the USA & Canada, as early as June to September 2025. Or perhaps as late as June to September 2026 if last quarter's acceleration in FSD miles is an aberration. If FSD is approved elsewhere - say in China or in Europe - these time lines could be pulled forward by a few months. Why is 6 Billion cumulative FSD miles important? Back in July 2016 in Master Plan, Part Deux, Elon - talking about autonomy - stated: "We expect that worldwide regulatory approval will require something on the order of 6 billion miles (10 billion km)." But why might that be the magic number? We don't know what was behind Elon's thinking, but here are some likely factors: 1) Data-Driven Validation: Tesla's FSD software development relies on vast amounts of data to train AI algorithms and to validate the safety of the systems. The more data collected from real-world driving, the more scenarios and edge cases (unusual or rare driving events) the system can learn to handle. Tesla's goal was to accumulate enough data - say 6 billion miles - to statistically prove that its self-driving cars are safer than human drivers in a wide variety of driving conditions. 2) Regulatory Confidence: Regulatory agencies, such as those governing transportation and vehicle safety, require extensive proof that autonomous systems can operate safely before they grant approval for widespread deployment. Elon's 6 billion mile goal may have been an estimate of the amount of data needed to satisfy these regulatory bodies that Tesla's autonomous system is not only reliable but also safer than human drivers. 3) Edge Cases and Anomalies: Autonomous systems need to learn from a wide range of driving situations, including rare and unexpected events, known as "edge cases." The larger the dataset (i.e., more miles driven), the more comprehensive the system's understanding of these edge cases will be, leading to better performance in real-world conditions. 4) Benchmark for Safety: Accumulating 6 billion miles worth of data can help build a benchmark to compare the performance of the self-driving system against human drivers. This benchmark could show how frequently the system avoids accidents, manages complex traffic situations, and responds to hazards. Either way, it will be exciting to see the cumulative FSD miles march towards 6 billion and beyond...