Will Tesla Lead the AI Business?
Reflections on Tesla AI Day 2021
After Tesla AI Day on August 20, 2021, I found myself repeatedly revisiting the presentation, absorbing every nuance of its vision. What struck me most was how Tesla seamlessly connected AI—a concept still abstract to many—to real-life applications, presenting a roadmap of unparalleled efficiency and optimization. The event was nothing short of inspiring.
A Personal Perspective
As I have been working on research papers regarding autonomous driving policies and corporate strategies in South Korea and China, Tesla’s rapid advancements in Full Self-Driving (FSD) and its execution capability compared to competitors have been on my mind. Around the same time, I happened to watch the TV series Humans, which made me acutely aware of the lack of societal discourse on AI and morality. Then came Tesla AI Day, and it hit me like a thunderbolt.
Tesla: More Than Just an Automaker
Tesla is far from being merely an electric vehicle company. It is an energy company, an AI company, and a mobility giant—one of the most innovative entities of our time. The company sits at the heart of three crucial technological frontiers: autonomous driving, semiconductors, and battery technology. At AI Day, Tesla laid out a bold roadmap centered around three key pillars.
1. Full Self-Driving (FSD)
Tesla demonstrated how its eight-camera system, combined with neural networks and vast amounts of data, could mimic the way humans drive—integrating limited HD camera input into a coherent vector space, just as humans rely on vision and cognition to navigate. No other company appears as advanced in real-world autonomous driving deployment.
However, Tesla’s greatest obstacle is not technology but regulation and convention. Unlike Waymo, which is building a fully controlled infrastructure for autonomy, Tesla takes a real-world-first approach, integrating autonomy into everyday life. While the autonomous driving market is still up for grabs among multiple players across different sectors, Tesla’s strategy remains one of the most compelling to watch.
Tesla integrates data captured by eight cameras into a vector space for navigation, employing over a thousand in-house staff for meticulous data labeling.
2. Dojo D1 Chip
Tesla is an automaker, but it needed massive computational power to handle autonomous driving processing. To train its self-driving AI, the company required a “dojo” of unparalleled computational capacity. Instead of relying on existing hardware, Tesla took matters into its own hands—designing its own chip, structuring it into a tile-based system, and achieving industry-leading performance in processing power, cooling efficiency, and energy optimization.
Seeing this, I couldn’t help but reflect on the broader industry trend: the era of general-purpose GPUs, led by NVIDIA, is evolving into an age where companies design custom chips tailored to specific needs. Just as Google and Apple have moved toward in-house chip design, Tesla’s foray into semiconductors signals an even greater shift. In this landscape, foundries like TSMC are poised to gain significant advantages from the rise of custom chip manufacturing.
The D1 chip vastly outperforms existing GPUs, achieving superior processing speed while optimizing power consumption and cooling efficiency.
3. Tesla Bot
Elon Musk’s keen business acumen shone through with the announcement of Tesla Bot. Tesla is no stranger to automation, with its expertise spanning engineering innovation, mobility from rockets to cars, and AI-powered software. In essence, Tesla’s vehicles are already semi-robotic. The next logical step? A general-purpose humanoid robot.
By delegating physically demanding and mundane tasks to Tesla Bot, Musk envisions applications not only within Tesla’s factories but also in broader industrial and exploratory fields, such as space missions. Unlike Ford, GM, and Hyundai, which have dabbled in robotics at an experimental level, Tesla’s approach suggests that mass production may be on the horizon sooner than expected.
Tesla Bot embodies general AI principles, leveraging FSD’s vision system, data processing, and in-house engineering capabilities.
AI: The Dawn of a New Era
The surge in AI interest, fueled by the rise of smartphones and computational advancements in the 2010s, has largely remained within the realm of recommendation algorithms and optimization. For the general public, AI is still synonymous with AlphaGo or Jarvis from The Avengers. However, the past decade has witnessed an explosion of research, akin to the wave of inventions following the steam engine’s emergence in the 19th century.
Today, AI is perceived as a digital transformation tool, but will it become deeply embedded in our daily lives through Tesla’s business model? That remains uncertain. One thing is clear: among all the frontrunners shaping the future of AI, Tesla stands out as one of the most imaginative and intriguing pioneers.
Tesla has built a full-stack AI ecosystem, integrating both software and hardware seamlessly into mobility solutions.
P.S. If you haven’t yet watched the Tesla AI Day presentation, I highly recommend taking the time to do so. You can find the full video at the link below:
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