Waymo, Tesla Robotaxi, Cost Per Mile, And Public Transit

 Let’s break it down with real numbers.

🟢 PART 1: Robotaxi vs Human-Driven Taxi (Cost Per Mile)

Let’s take an average human-driven taxi and compare it to a Waymo or Tesla robotaxi:

Assumptions:

Item	Human Taxi	Robotaxi (Electric)
Driver Salary (inc. benefits)	$0.75/mile	$0
Fuel Cost	$0.20/mile	$0.04/mile (electricity)
Maintenance	$0.10/mile	$0.06/mile
Insurance & Licensing	$0.15/mile	$0.15/mile
Vehicle Depreciation	$0.25/mile	$0.25/mile
Total Cost per Mile	$1.45	$0.50

✅ Savings per mile: $0.95 (65%)

So, a robotaxi is 65% cheaper per mile than a human-driven taxi — driven largely by removing the driver and lowering energy costs.

---

🟢 PART 2: Autonomous Bus vs Human-Driven Bus

Now let’s scale up to a self-driving electric bus.

Assumptions for 40-seater bus:

Item	Human Bus	Self-Driving Electric Bus
Driver Salary (loaded)	$0.40/passenger-mile	$0
Fuel (Diesel vs Electric)	$0.15/passenger-mile	$0.03
Maintenance	$0.05	$0.03
Insurance & Misc.	$0.07	$0.07
Vehicle Cost (amortized)	$0.13	$0.13
Total Cost per Passenger-Mile	$0.80	$0.26

✅ Savings per passenger-mile: $0.54 (67.5%)

That’s massive. Cities could reduce costs dramatically — from $0.80 to $0.26 per passenger-mile.

---

🟢 PART 3: What This Means for Free Public Transit

Let’s do a city-wide calculation:

• Say a city runs 10 million passenger-miles per day.

• Current Cost (Human Bus): 10M x $0.80 = $8M/day

• Autonomous Electric Bus: 10M x $0.26 = $2.6M/day

💸 Daily savings = $5.4M → That’s almost $2 billion/year in savings.

So with enough scale, it may actually be cheaper for cities to run free autonomous electric bus systems than to operate or subsidize current systems. Free, frequent, clean — and automated.

---

🟢 Bottom Line

• 🚖 Robotaxis slash 65%+ of costs vs regular taxis.

• 🚌 Self-driving buses cut public transit costs by two-thirds.

• 📉 Removing drivers + switching to electric = huge compounding savings.

• 💡 At scale, free transit isn’t just utopian — it’s fiscally smart.

Velocity Money: Crypto, Karma, and the End of Traditional Economics
The Next Decade of Biotech: Convergence, Innovation, and Transformation
Beyond Motion: How Robots Will Redefine The Art Of Movement
ChatGPT For Business: A Workbook
Becoming an AI-First Organization
Quantum Computing: Applications And Implications
Challenges In AI Safety
AI-Era Social Network: Reimagined for Truth, Trust & Transformation

Why DeepSeek Took the U.S. by Surprise — A Tale of Blind Spots and Firewalls

How BYD Is Beating Tesla at Its Own Game

Why DeepSeek Took the U.S. by Surprise — A Tale of Blind Spots and Firewalls

When DeepSeek, the Chinese open-source LLM, burst onto the scene with capabilities rivaling GPT-4, it caught the U.S. AI world completely off guard. There was no drumroll. No press leaks. No whispers in tech forums. One day, it simply was. For a nation obsessed with innovation and competitiveness, especially in the AI arms race, this kind of blindside is remarkable. But it’s not unprecedented — and it points to a deeper issue.

So why did this happen? Two answers stand out: the American blind spot toward China, and China’s tight grip on its own flow of information.

1. The U.S. Tech Scene Underestimates China’s AI Depth

Despite the Pentagon, think tanks, and AI insiders occasionally sounding the alarm about China’s AI ambitions, the broader U.S. tech discourse tends to be myopic. American developers, VCs, and media have largely been focused on Silicon Valley, OpenAI, Anthropic, and Meta’s moves — and with good reason. These players dominate global headlines and benchmarks. But that insularity has a cost. It fosters the illusion that AI progress is Western by default.

There’s also a lingering assumption — rooted in outdated stereotypes — that Chinese innovation is derivative, not original. The success of TikTok, DJI, BYD, and now DeepSeek tells a very different story. Chinese AI companies aren’t just catching up. They are leapfrogging.

2. The Great Firewall Works Both Ways

China’s tight control of its internet — from censorship of Western media to closed developer communities — means that progress in the Chinese AI world often happens in a kind of parallel digital universe. DeepSeek was likely known to Chinese insiders and developers long before Western audiences had a clue. But that information never flowed out — either by design or by apathy.

The Chinese government also limits public access to its own advanced LLMs and AI tools, fearing misuse or political subversion. As a result, while AI breakthroughs occur in China, they don’t spread virally across Reddit, Hacker News, or Substack like they do in the West. That gives the illusion of silence — until the curtain is lifted.

3. It’s Not Just Politics — It’s a Clash of Media Cultures

U.S. tech news runs on leaks, hype cycles, and pre-release speculation. Chinese tech media, by contrast, operates in a more controlled, restrained environment. That means projects like DeepSeek can be developed quietly over many months — without a single Tweet, thread, or podcast mention in the West.

What feels like a “surprise launch” to Americans is often a deliberate choice by Chinese firms — a show-don’t-tell strategy shaped by political sensitivities and cultural norms.

---

Final Thought: Get Ready for More DeepSeeks

DeepSeek will not be the last AI surprise to emerge from behind the Great Firewall. As China doubles down on foundational AI, biotech, and quantum computing, the U.S. must expand its gaze and respect its competition — not just in capabilities, but in the game of attention itself.

Because when the next Chinese breakthrough arrives, it won’t ask for permission or make a noise. It will simply appear — fully formed, shockingly advanced, and ready to compete.