FSD247 | My Tesla Full Self-Driving Journey

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Kansas City, MO

January 24, 2025

First FSD drive: the spark

Speaker

Roger

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This short clip captures my very first experience with Full Self-Driving. The car took me on a route from Shawnee Mission Parkway to I-35, then onto 169, across 435 East, and down State Lane Road—delivering me right into the parking lot of the Kansas City Tesla dealership. It was slightly frightening and an extraordinary joyride all at once.

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Miami, FL

9:30am – 10:30am

Epic road trip stories

Speaker

Morgan Ellis

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Hear about unforgettable cross-country adventures and how Full Self-Driving made every mile smoother, safer, and more fun.

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Destin, FL

11:00am – 12:00pm

Life with FSD: one year in

Speaker

Jordan Avery

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Reflect on a year of Full Self-Driving—over 13,000 miles, new perspectives, and the freedom to enjoy every journey.

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I never thought driving could feel this effortless. FSD lets me relax, enjoy the view, and trust the journey.

Roger, Model Y Owner, Kansas City

13K+

Miles Driven

1

Year of FSD

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My commute is now my favorite time. FSD gives me confidence and peace every mile.

Jordan Avery, Model 3 Driver, Kansas City

3

Epic Road Trips

100%

Peace of Mind

FSD means I can focus on what matters—my family, the scenery, and the adventure ahead.

Morgan Ellis, Model X Owner, Destin

24/7

Autopilot Confidence

0

Regrets

Discover

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Every drive feels like the future. FSD isn’t just tech—it’s a new way to see the world.

Alex Rivera, Model S Enthusiast, Chicago

50+

Cities Visited

5

States Explored

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How Tesla Full Self-Driving Works
Tesla's Full Self-Driving system operates through a sophisticated integration of vision-based perception, custom silicon, and end-to-end neural network processing—a fundamentally different approach than competitors who rely on lidar and high-definition maps.
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Vision-Only Perception‍
Tesla vehicles are equipped with eight exterior cameras providing 360-degree visibility around the vehicle. This camera array captures over 200 frames of video per second, feeding raw visual data directly into the system. Tesla made the deliberate decision to eliminate radar and ultrasonic sensors, betting that camera-based perception—the same method humans use to navigate—combined with sufficiently advanced AI can match or exceed multi-sensor approaches.

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End-to-End Neural Network Architecture
The breakthrough in recent FSD versions (V12 and beyond) is the transition from rule-based programming to a unified end-to-end neural network. Previous iterations relied on approximately 300,000 lines of explicit C++ code defining how the vehicle should respond to specific scenarios. The current architecture replaces this with a neural network trained on millions of video clips of expert human driving.

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The system now takes raw camera inputs and directly outputs vehicle control commands—steering angle, acceleration, and braking—without intermediate hand-coded rules. Rather than programming the car to recognize a roundabout and then consulting a rulebook for how to navigate it, the network learns driving behavior holistically by observing how humans drive.

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Custom Hardware
Tesla designed its own silicon to run these demanding neural networks in real-time. The FSD Computer features custom-designed chips fabricated by Samsung, functioning as neural network accelerators. Hardware 4 vehicles feature higher-resolution cameras with improved dynamic range and significantly more processing power than the previous HW3, essential for running the increasingly complex neural network models. Each system includes two FSD chips for redundancy.

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The Data Engine
Tesla's competitive advantage lies in its fleet-learning approach. With millions of FSD-equipped vehicles on the road, the company continuously collects real-world driving data at an unprecedented scale—billions of miles of diverse scenarios. When the system encounters edge cases or driver interventions, it uploads scene data for analysis. This data trains improved models at Tesla's data centers, which are then deployed back to the entire fleet through over-the-air software updates.

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Occupancy Networks and Spatial Understanding
The system uses Occupancy Networks to build a real-time 3D understanding of the vehicle's surroundings. This technology predicts what space is occupied and what's free, enabling the car to navigate around objects that don't fit neatly into predefined categories. Combined with temporal fusion—the ability to integrate visual data across multiple frames—the system maintains object permanence even when obstacles are briefly obscured.

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Current Classification
Despite these capabilities, Tesla's FSD remains classified as an SAE Level 2 driver assistance system, requiring active driver supervision at all times. The technology continues to evolve through continuous software updates, with each iteration expanding the system's capability to handle increasingly complex real-world scenarios.

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Every first drive tells a story

First FSD drive: the spark

Epic road trip stories

Life with FSD: one year in

Journeys transformed by autonomy

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