"Nine failures are the tuition; the tenth swing is the future"
— Aditya Mohan, Founder, CEO & Philosopher-Scientist, Robometrics® Machines
In the crucible of innovation, conventional wisdom stands as both sentinel and barrier—a gatekeeper that, more often than not, is right. Yet the most transformative leaps require more than deference; they demand audacity. As Jeff Bezos observed in his 2015 shareholder letter, a ten‑percent chance of a hundred‑times return justifies the leap—even if nine ventures falter. Failure, in this light, is not the sting of defeat but a vital heartbeat, a necessary tremor in the anatomy of invention.
Bezos’s metaphor draws from baseball, where a player’s maximum outcome is capped: no matter how sweetly one connects, the ceiling is four runs. Business, however, is governed by long‑tailed distributions. Every once in a while, stepping to the plate yields not four runs, but a thousand. That recognition—that asymmetry—is what gives experimentation its power. The winners, rare and staggering, pay for the entire catalogue of misses. In such a system, risk is not merely tolerated but required.
When viewed through the lens of artificial intelligence and robotics, this philosophy takes on an even sharper edge. Imagine a stage where machines are not passive tools but actors in a vast human‑machine performance. Each experiment—whether an algorithm’s failed reasoning chain or a robot’s misaligned gesture—appears as a strikeout. Yet every attempt refines the choreography, and within the rhythm of repeated failure lies the possibility of a crescendo: an AI that can perceive, adapt, and feel. These moments, improbable and rare, become the home runs that shift civilization.
Human creativity, too, thrives on this calculus. History’s great designers, scientists, and playwrights did not advance by avoiding error but by embracing the improbable. Alan Turing’s bold hypotheses, Isaac Asimov’s sweeping universes, Iain M. Banks’s radical civilizational visions, Jony Ive’s reductionist elegance, and George Bernard Shaw’s biting clarity—all were swings for the fences. Each took the risk of rejection and misfire, yet the few triumphs remade worlds of thought and design. The long‑tail of innovation is written in their stories.
For leaders, creators, and engineers alike, the lesson is plain: the willingness to be wrong repeatedly is the price of being right in ways that matter. In business, as in science and art, the thousand‑run possibility is rare but real. To confine oneself to safe swings is to accept mediocrity. To step forward boldly, with experiments destined to fail more often than succeed, is to court the possibility of transformation. In Bezos’s words, the big winners pay for so many experiments.
Thus, the mathematics of boldness is not about avoiding failure but about orchestrating it. Each misstep is a note in a greater composition, each strikeout a rehearsal for the day the improbable connects. And when it does, when the ball arcs impossibly into the unseen, we glimpse the truth: the future belongs to those who dare to swing.
Nine tries teach the wings; the tenth lets them remember.
“Learning to rise begins inches above the grass.”
— Aditya Mohan, Founder, CEO & Philosopher-Scientist, Robometrics® Machines
From Infinite Improbability to Generative AI: Navigating Imagination in Fiction and Technology
Human vs. AI in Reinforcement Learning through Human Feedback
Generative AI for Law: The Agile Legal Business Model for Law Firms
Generative AI for Law: From Harvard Law School to the Modern JD
Unjust Law is Itself a Species of Violence: Oversight vs. Regulating AI
Generative AI for Law: Technological Competence of a Judge & Prosecutor
Law is Not Logic: The Exponential Dilemma in Generative AI Governance
Generative AI & Law: I Am an American Day in Central Park, 1944
Generative AI & Law: Title 35 in 2024++ with Non-human Inventors
Generative AI & Law: Similarity Between AI and Mice as a Means to Invent
Generative AI & Law: The Evolving Role of Judges in the Federal Judiciary in the Age of AI
Embedding Cultural Value of a Society into Large Language Models (LLMs)
Lessons in Leadership: The Fall of the Roman Republic and the Rise of Julius Caesar
Justice Sotomayor on Consequence of a Procedure or Substance
From France to the EU: A Test-and-Expand Approach to EU AI Regulation
Beyond Human: Envisioning Unique Forms of Consciousness in AI
Protoconsciousness in AGI: Pathways to Artificial Consciousness
Artificial Consciousness as a Way to Mitigate AI Existential Risk
Human Memory & LLM Efficiency: Optimized Learning through Temporal Memory
Adaptive Minds and Efficient Machines: Brain vs. Transformer Attention Systems
Self-aware LLMs Inspired by Metacognition as a Step Towards AGI
The Balance of Laws with Considerations of Fairness, Equity, and Ethics
AI Recommender Systems and First-Party vs. Third-Party Speech
Building Products that Survive the Times at Robometrics® Machines
Autoregressive LLMs and the Limits of the Law of Accelerated Returns
The Power of Branding and Perception: McDonald’s as a Case Study
Monopoly of Minds: Ensnared in the AI Company's Dystopian Web
Generative Native World: Digital Data as the New Ankle Monitor
The Secret Norden Bombsight in a B-17 and Product Design Lessons
Kodak's Missed Opportunity and the Power of Long-Term Vision
The Role of Regulatory Enforcement in the Growth of Social Media Companies
Embodied Constraints, Synthetic Minds & Artificial Consciousness
Tuning Hyperparameters for Thoughtfulness and Reasoning in an AI model
TikTok as a National Security Case - Data Wars in the Generative Native World
23andMe and the National Security Stakes of Population‑Scale Genomic Data
The Data Deficit Threat to National Security in a Generative Native World