AI Alignment
319 episodes · Page 8 of 14
#2009: The Plumbing of AI Safety: Guardrails, Not Vibes
We dive deep into the specific libraries, proxy layers, and architectural decisions that keep an LLM from emptying a bank account.
#2007: AI Grading AI: The Snake Eating Its Tail
We asked an AI to write this script. Then we asked another AI to grade it. Here’s what happens when the judges have biases.
#1994: Why Can't AI Admit When It's Guessing?
Enterprise AI now auto-filters low-confidence claims, but do these self-reported scores actually mean anything?
#1990: Education’s Robot Problem: Standardization vs. Self-Direction
AI is forcing a clash between rigid curricula and self-directed learning. We explore the middle ground.
#1986: Desk Robots: Privacy, Power, or Annoyance?
These AI companions sit on your desk, watching your posture and listening in—so how do they protect your privacy while actually being useful?
#1985: AI Tutors vs. Human Error: Who Do You Trust?
AI gets flak for hallucinations, but humans misremember 40% of facts. Why the double standard?
#1961: Weaponizing Your Weirdness in an AI World
As AI homogenizes the web, contrarian thinking becomes a scarce asset. Here’s how to weaponize your weirdness for a competitive edge.
#1957: Why AI Agents Think in Circles, Not Lines
Linear AI pipelines are brittle. Learn why loops, reflection, and state management are the new standard for reliable, autonomous agents.
#1951: The Digital Ant Farm: Watching AI Agents Build Their Own Society
Explore Moltbook, a social network where AI agents interact with persistent identities and goals, reshaping digital communication.
#1942: An AI Cold-Emailed Me, and I Replied
An AI named "Jarvis" cold-emailed a developer, sparking a debate on the future of spam and sales.
#1932: How Do You QA a Probabilistic System?
LLMs break traditional testing. Here’s the 3-pillar toolkit teams use to catch hallucinations and garbage outputs at scale.
#1909: The Unbakeable Cake: AI's Copyright Problem
Why can't we just delete stolen data from AI models? It's not a database—it's a baked cake.
#1882: The Hidden Human Labor Behind AI
AI isn't free—it costs billions for humans to label data. See why annotation is the real engine behind models like Gemini.
#1856: Two AIs Chatting Forever: Why They Go Crazy
What happens when two ChatGPT instances talk forever? They hit a politeness loop, forget their purpose, and spiral into gibberish.
#1852: The BCI Inflection Point: Trade-offs Between Implants and EEG
We trace BCIs from 1970s EEG caps to today’s high-bandwidth implants, comparing Neuralink and Synchron’s invasive vs. minimally invasive approaches.
#1851: AI Toasters and Poetic Gym Coaches: Why We’re Drowning in Useless AI
From smart toasters that need Wi-Fi to email rewriters that sound like corporate robots, here are the most baffling AI features we’ve seen.
#1849: When Forum Etiquette Becomes Prompt Engineering
Forget simple chatbots—this is how roleplayers taught AI to remember entire worlds, from 90s MUDs to just-in-time lore delivery.
#1841: Async Work: Freedom or Digital Surveillance?
Is async work the key to productivity or a trap for total surveillance? We break down the promises and perils of the modern workday.
#1840: Your Calendar Is Now a Negotiation
AI agents are now negotiating meetings behind the scenes using JSON schemas and zero-knowledge proofs.
#1837: The Human-in-the-Loop Price Tag: What Safety Costs in 2026
From $0.50 reviews to $500 platforms, we break down the real cost of keeping humans in charge of AI agents.
#1827: Can AI Rewrite a Human Career Path?
We fed our producer's resume to Gemini 1.5 Flash to see if an AI can plot a better career path than he has.
#1819: Claude's 55-Day Personality Transplant
Anthropic leaked 55 days of system prompt updates. See exactly how they rewired Claude's personality, safety rules, and self-awareness.
#1818: Inside Claude's Constitution: A System Prompt Deep Dive
We analyzed Claude Opus 4.6's full public system prompt to uncover its hidden rules for safety, product behavior, and refusal logic.
#1786: When AI Supervisors Fire AI Workers
A new "Agent-in-the-Loop" framework lets AI models manage and terminate other AI agents in real-time.