On Self-driving, Waymo is playing chess while Tesla plays checkers

Tesla’s Business Identity & Valuation

• Debate over whether Tesla is primarily an automaker, energy company, or “stock company” whose main product is its equity.
• Some argue its high valuation is justified by energy, charging, and battery businesses and the “future growth” story.
• Others say valuation is detached from current fundamentals and sustained by hype; long-term, market may demand performance tied to realized results.
• Concern that robotaxis move Tesla further into speculative territory: success requires not just solving self-driving, but enjoying a temporary monopoly.

Regulation, Politics, and Market Strategy

• Waymo is seen as ahead on regulatory/political work: slow rollouts, cooperation with regulators, building public trust, and helping shape rules competitors must later follow.
• Tesla is criticized for a “just turn it on” mentality, underestimating regulatory hurdles and public acceptance of “2‑tonne death traps.”
• Some note second movers can benefit from the first mover’s regulatory groundwork and mistakes, but that may erode pricing power and margins.

Technical Approaches: Vision vs. Sensors

• Pro‑Tesla voices praise the “vision-only” strategy as elegant, scalable, and broadly applicable to other automation tasks; claim big improvements in FSD with few interventions.
• Critics counter that:
  • Vision hasn’t “won” because actual Level 4 services (Waymo, Mercedes) use multiple sensors including lidar.
  • Tesla still requires constant human supervision; by definition that is not self-driving.
• Some argue relying only on vision needlessly copies human limitations (poor visibility, optical illusions), ignoring that machines can add richer sensing.

Safety, Evidence, and Responsibility

• One camp: self-driving only needs to be statistically better than human drivers to be a net social benefit.
• Others respond that:
  • Baseline human safety is already poor; comparisons should be to good professional drivers, not average ones.
  • Political and liability structures will demand automation be much safer than humans since each automated death has a clear corporate owner.
• Personal anecdotes of excellent FSD performance are challenged as insufficient; accidents are long‑tail events and require large-scale data.
• NHTSA findings tying Autopilot to hundreds of crashes and multiple deaths are cited as cause for skepticism.
• Dispute over falsifiability: skeptics point to Tesla’s refusal to take liability or deploy driverless cars; supporters emphasize huge supervised mileage without apparent catastrophe.

Waymo’s Remote Operators & Actual Autonomy

• Article’s focus on Waymo’s remote operators is attacked as implying “remote-controlled taxis.”
• Others clarify operators provide guidance/assistance rather than direct driving; exact intervention rates are undisclosed and thus unclear.
• Comparison drawn: Tesla uses a “local operator” (the human driver) for the same class of edge cases; both systems still rely on humans in the loop.

Economics of Robotaxis

• Tesla’s FSD is seen as high-margin software pre-sold years before full capability exists; critics call this monetizing a future that may never arrive.
• Promised timelines (e.g., a million robotaxis by 2020, owners earning $10k/year) are widely viewed as unrealistic in hindsight.
• Even if owners could earn that much, heavy utilization would rapidly depreciate vehicles; profitability is unclear.

Data, Scale, and Competitive Outcomes

• Supporters of Tesla’s “drive everywhere, human-supervised” approach argue it yields unparalleled data on rare edge cases, a key AI resource.
• View that Waymo’s remote-operator “joker” is replicable by Tesla once it reaches similar capability.
• Speculation that if Tesla’s vision-centric path is ultimately “correct,” many traditional automakers could fail, pivot via licensing, or be overtaken by lower-cost EV makers.

Alternative Visions: Infrastructure & Transit

• Some argue the entire self-driving paradigm is misguided, advocating standardized roadway infrastructure and expansion of trains/subways instead.
• Counterargument: even standardized infrastructure can’t remove all unusual situations; autonomy must handle messy reality.
• Disagreement over cost and feasibility: one side claims such infrastructure would have been cheaper and more effective; the other insists it would cost “trillions” and still fall short of general autonomy benefits.

Perceptions of Media and Hype

• Several comments criticize the linked article as shallow, click‑bait, or biased toward Waymo.
• Underlying tension: enthusiasm about rapid progress and elegant AI strategies versus skepticism rooted in missed deadlines, safety investigations, and opaque deployment details.