🚗 1. Different Philosophies

• Tesla: Vision-First, Consumer-Scale
  • Uses cameras (and formerly radar), with neural nets trained on billions of miles of real-world driving data from customer vehicles.
  • Believes in an “end-to-end” AI approach: a single neural network processes video input and outputs driving decisions.
  • Goal: deploy Full Self-Driving (FSD) via software updates to consumer-owned vehicles.
• Waymo: Lidar-Heavy, Geofenced Robotaxi
  • Relies on high-definition maps, Lidar, radar, and a more rule-based AI architecture.
  • Operates robotaxis in restricted zones (Phoenix, San Francisco, etc.).
  • Goal: offer a driverless taxi service, not sell cars to consumers.

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⚙️ 2. Tesla’s Edge (in Theory)

• Scalability
  • If Tesla’s camera-based approach works, it can scale globally—because it doesn’t depend on detailed pre-mapping.
• Massive Data Advantage
  • Every Tesla with Autopilot contributes driving data, fueling model training at scale Waymo can’t match.
• Vertical Integration
  • Tesla controls hardware (cars), software (FSD), chips (Dojo), and fleet—allowing tight optimization and faster iteration.
• Cost Efficiency
  • No need for expensive sensors like Lidar, making autonomy potentially cheaper and more accessible.

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🚧 3. Challenges Tesla Faces

• Technical Doubts
  • Critics argue vision-only autonomy may never match the reliability of multi-sensor systems, especially in edge cases (fog, complex traffic).
• Regulatory & Safety Hurdles
  • Tesla FSD is still classified as Level 2 (driver-assist), not fully autonomous, and faces increasing scrutiny.
• Uncertain Timeline
  • Musk has repeatedly missed autonomy deadlines. FSD remains in beta and underwhelming in many scenarios.

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🧠 4. Waymo’s Strengths

• It Works (in Zones)
  • Waymo One is already operating true Level 4 driverless cars in select cities—no human in the front seat.
• Safety Record
  • Waymo boasts one of the safest track records in the AV space, which is critical for trust and regulation.
• Deliberate Expansion
  • Their slow but steady rollout (city-by-city) avoids overpromising, and sets realistic public expectations.

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💰 5. Lidar Economics: Why Waymo Can’t Scale Yet (But Might Not Need To)

Here’s the kicker: Waymo’s cars are expensive.

Waymo uses 5–7 Lidars per vehicle, including:

• A roof-mounted long-range Lidar (~$7K–$10K)
• Multiple mid- and short-range units (~$1K–$5K each)

Even building in-house, a Waymo vehicle’s sensor suite alone can cost $20,000–$30,000. Add compute, redundancy systems, insurance, regulatory overhead… and you’re flirting with $50K per robotaxi before you start the engine.

This isn’t consumer tech—it’s city infrastructure disguised as a car.

But while Tesla is selling autonomy as a $12,000 add-on, Waymo is building an actual working taxi business. If autonomy stays hard, Waymo’s cautious, heavily instrumented approach may prove right.

🥊 Tesla’s Strategy to Compete:

1. Bet on Generalization Over Maps
   • Tesla’s approach aims to create a system that can generalize across environments, not rely on curated routes.
2. Leverage Fleet for Real-World Testing
   • Continuous improvement from millions of user-miles versus Waymo’s limited test areas.
3. Position as a Consumer Product
   • If FSD improves, Tesla can monetize autonomy through direct sales, subscriptions, or even its own robotaxi fleet.

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Tesla is betting on scale, data, and a generalizable AI approach. If it works, it could dominate. Waymo is betting on safety, precision, and a services model. It’s further along technically but less scalable right now.

Whether Tesla can “catch up” or leapfrog Waymo hinges on whether end-to-end vision-based autonomy can reach Level 4 safely in the real world—and how fast.

🇨🇳 The Chinese AV Landscape: Key Players

1. Baidu (Apollo & Apollo Go)

• Equivalent of Google in China—huge tech muscle.
• Apollo Go robotaxi service is live in cities like Wuhan, Chongqing, and Beijing.
• Level 4 autonomy in restricted urban zones, with some fully driverless rides.

2. Pony.ai

• Operates in China and the U.S. (California).
• Backed by Toyota and others.
• Has been granted permits for driverless testing and commercialization in multiple Chinese cities.

3. AutoX

• Backed by Alibaba.
• Claims fully driverless operation in parts of Shenzhen with no safety drivers.
• Uses a combination of Lidar, radar, and vision.

4. XPeng / Huawei / Didi

• XPeng and Huawei are pursuing Tesla-like consumer vehicles with strong driver-assist systems.
• Didi has its own robotaxi arm and is also testing autonomy at scale.

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🧩 How They Compete with Tesla and Waymo

🚀 Like Tesla: Scalable Hardware + AI

• XPeng, Huawei, and others aim to sell semi-autonomous vehicles to consumers.
• Heavy use of vision + Lidar; not vision-only like Tesla.
• Fast iteration due to high domestic demand and supportive regulation.

🧠 Like Waymo: Robotaxis in Geofenced Cities

• Baidu, AutoX, and Pony.ai are deploying robotaxis in large cities with full Level 4 autonomy.
• Government support for AV test zones and smart infrastructure (e.g., V2X sensors at intersections).

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🏁 China’s Competitive Advantages

• Regulatory Alignment
  • Central and municipal governments actively promote AVs via policy, infrastructure, and fast-track permits.
• Urban Digital Infrastructure
  • “Smart cities” with real-time traffic data, sensors, and 5G help AVs operate more reliably.
• Talent & Funding
  • China has world-class AI talent, plus deep funding pools from both private and state sources.
• Fast Iteration Cycle
  • Less friction around privacy, litigation, and bureaucracy allows more aggressive real-world testing.

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⚠️ Challenges Facing Chinese Players

• Export Barriers
  • U.S. and EU skepticism about Chinese tech, especially in sensitive areas like autonomous vehicles.
• Standardization
  • Fragmentation of platforms and inconsistent standards across provinces can slow national rollout.
• Data Governance
  • Tight Chinese controls on data localization and AI models could hinder global scalability.

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🧮 Summary Table: Tesla vs Waymo vs China

Feature	Tesla	Waymo	Chinese Players (e.g. Baidu, XPeng)
Approach	Vision-only AI	Lidar + HD maps	Hybrid: Lidar + Vision + V2X
Deployment Mode	Consumer Vehicles	Robotaxis	Both robotaxis & consumer EVs
Deployment Geography	Global (beta)	Few U.S. cities	Dozens of Chinese cities
Technical Readiness	Level 2 (FSD Beta)	Level 4 (limited)	Level 4 (some fully driverless)
Regulatory Support	Mixed	Careful scrutiny	Strong government backing

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💭 China Thought

The Chinese AV industry could outpace both Tesla and Waymo in the near term within China, thanks to regulatory alignment, smart infrastructure, and scale. However, global competition will depend on geopolitical barriers, trust, and brand perception.

In short: Tesla wants to win the world; Waymo wants to own U.S. cities; China may quietly win the future—at home and possibly abroad.

🧾 So, About That Put: What I Bought, and Why

Here’s the actual trade I placed:

Bought to Open 1 TSLA 08/15/2025 200.000 Put
Executed on June 25, 2025

✅ What this means:

• I paid a premium (the market price of the option) for the right—but not the obligation—to sell 100 shares of Tesla stock at $200 per share on or before August 15, 2025.
• I do not need to own any Tesla shares to make this bet. This is a speculative downside position, often called a “naked put” if you don’t own the underlying shares.
• It becomes profitable if TSLA drops below the strike price ($200) plus the premium paid before expiration.

Say I paid $6.00 per share in premium (total cost: $600).

• My break-even price is $194.00
• Below that, the put gains value.
• Above $200, the option expires worthless, and I’m out $600—my maximum loss.

🤔 Why this strike? Why this date?

• $200 is a psychologically significant support level—it’s a clean round number and not far below recent prices.
• August 15 gives me about 50 days for Tesla to disappoint: earnings, FSD rollout delays, macro wobbles, or just a general repricing of hype.
• It’s a small, defined-risk play—what you’d call a tactical trade, not a conviction short.

I’m not betting on a collapse. I’m betting on a gap between promise and price, and that some of the FSD froth may leak out of the stock as competitors like Waymo and Baidu keep delivering real-world autonomy, while Tesla keeps selling a “Beta” button.

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🪞But Also, Let’s Be Honest

I’m not a professional trader. I’m not running a fund. I’m just a guy watching the world’s biggest car company talk like a tech startup, and wondering how long the market will let that go on.

Tesla has vision (literally), but:

• Waymo has working Level 4 robotaxis.
• China has cities full of AVs that don’t need a babysitter.
• And Tesla still has to convince regulators that “Full Self-Driving” is not a punchline.

So maybe this put is just my way of saying: “Show me.”

If I’m wrong, I lose $600 and write a post titled “Why My Tesla Put Got Run Over by Dojo.”
If I’m right, I buy a used Rivian with the profits and never admit how lucky I was.

Either way, I’m watching closely.