Distributed Dissent

Does the release of Gemini 3 prove that intelligence is a commodity and that OpenAI’s moat is gone?In this month's episode of Distributed Dissent, En Hong and Mathias Bock break down the immediate impact of Google’s Gemini 3 and its dedicated TPU infrastructure on the AI landscape. They debate the dangerous trend of companies firing junior staff to replace them with AI, arguing instead for the "Cyborg approach"where human agency is multiplied by technology. Finally, they tackle the existential crisis of copyright, explaining why neural networks aren't actually "copying" anything and what that means for the future of creative industries.Topics Covered:The Hardware Wars: With Gemini 3 trained on TPUs, is Nvidia’s dominance threatened? The hosts discuss how specialized chips (like Bitcoin miners before them) might upend the GPU market.The "Cyborg" Lawyer: Why the "Matthew Effect" applies to legal tech: AI isn't a magic bullet, but a multiplier of agency. Those who know how to wield it will exponentially outpace those who don't.Don't Fire the Juniors: Analyzing the fallout from companies like Klarna (CLA) replacing staff with AI. Why the "last 10%" of work still requires human judgment and why firing the training class is a long-term disaster for firms.Waymo & The Safety Delta: A look at the staggering safety statistics of autonomous vehicles (10x-40x safer than humans) and the economic cost of letting humans continue to drive.The Copyright "Vibe": A deep dive into how neural networks actually learn (vectors vs. databases), why current copyright law is failing to catch up, and why the "Swiss Watch" of human connection is the only remaining moat for creators.Mentioned in this episode:TV Series: Alien: EarthArticle: Boredom by Nicholas Lynch (Skeptic.com)Article: Vatican City: City, State, Nation, or Bank?Tech: Google Gemini 3 & Anti-Gravity IDEReport: Harvey Legal Tech Adoption StudyConcept: The Matthew Effect (Matthew 25:29)

Episode Description: Is spending millions to fine-tune an AI model a waste of resources when frontier models like Gemini and GPT-5 are evolving so fast?In the debut episode of Distributed Dissent, En Hong (CEO, Generis AI) and Mathias Bock (CEO, Tokuma Labs) discuss the reality of being lawyers-turned-founders in Hong Kong and Tokyo. They debate the diminishing returns of training custom models, the psychological traps peoplefall into when using AI, and the stark differences between building startups in different Asian markets.Topics Covered:Frontier Models vs. Fine-Tuning: Why even well-funded startups are giving up on fine-tuning their own models in favor of riding the wave of big tech scaling.The "Gell-Mann Amnesia" Effect: Why experts immediately spot hallucinations in their own field but blindly trust AI in areas they don’t understand—and the risks this poses for legal professionals.Hong Kong vs. Tokyo: A comparative look at the startup ecosystems, including the surprising arbitrage in engineering talent and the cultural differences in venture capital.Involution hits the Legal Field: How extreme price competition in the region is driving fees down, and what this signals for the future of "median" legal work versus true expertise.Manufactured Intelligence: The economic implications of intelligence becoming a cheap utility, and why "plumbers might be safer than partners."Mentioned in this episode:Book: Permutation City by Greg EganBook: Blindsight & Echopraxia by Peter WattsArticle: Why Birds Don't Drive Bentleys and Why Humans Will Never FlyCase Law: Getty Images vs. Stability AI (UK Ruling)