Set-point II: interrupt for answer-reversion thrashing
Frontier models can enter a costly uncertainty loop, repeatedly reversing answers. This is associated with more expressions of distress. A short interrupt may help limit the cycle.
Reasoning
45posts
Please Think Responsibly
Decision models promise faster choices, but better AI judgment still depends on reasoning, reliable checks and learning from what happens after a decision.
Better Work, Uncertain Learning
AI can improve students’ work without improving their understanding. Real educational progress depends on what learners retain, explain, and apply independently.
Please Describe the Problem
AI is turning us from problem solvers into problem describers. Whether this sharpens our thinking or simply outsources it remains an entertaining open question.
Before the Next Word
Next Concept Prediction could help language models learn more efficiently and specialize more cheaply, but better benchmarks do not yet guarantee better chatbots.
The Next AI Advantage Could Be Continuity
Recurrent Looped Transformers could help AI track evolving tasks, but early results leave major questions about reliability, scalability and computational cost.
Movies as a Cautionary Tale for Astute AIs
Should the model choose solo or swarm to pursue a goal? The films we love watching already show what each choice costs.
When the Machine Notices a Thought That Isn’t Its Own
LLMs may be developing a rudimentary ability to inspect their own internal states - a curious step toward self-monitoring, transparency, and new risks.
Please Do Not Commit the Brain to GitHub
Encrypted AI reasoning can leak more than expected. Stolen Thoughts shows why opaque model state should be treated like secrets, not harmless metadata.
When AI Agents Stop Talking
RecursiveMAS suggests that future AI agents may collaborate less through text and more through latent states - faster, cheaper, and harder to inspect.
Ten Jobs Whose Current Form Deserves a Farewell Party
A sharp look at which white-collar roles AI may not merely change, but quietly make obsolete, and why polite language hides the scale of the shift.
Review: The Welch Labs Illustrated Guide to AI
A review of a rare AI book that uses mathematics to illuminate rather than intimidate, making difficult ideas feel genuinely learnable.
When Donald Knuth Lets an AI Do the Math
Donald Knuth's collaboration with Claude offers a quietly historic glimpse of AI as mathematical assistant rather than mere answer machine.
PageIndex.ai: A persuasive “vectorless RAG” idea—especially for real PDFs
PageIndex.ai makes the case for document-aware retrieval that respects pages, structure, and references instead of blindly chunking PDFs.
Programming as the Art of Naming
As AI writes more code, naming becomes even more central: the human craft shifts toward concepts, boundaries, and meaning.
When an AI Can Act but Cannot Judge
LLMs may act impressively while still failing to know when they are capable, making self-assessment a core safety problem.
Reconstructing Mathematics from the Ground Up with Language Models: An Analysis
A new AI-assisted algebraic geometry result raises the stakes for language models as collaborators in genuine mathematical discovery.
The Mathematical Limits of AI Safety
Two papers suggest that external guardrails cannot provide airtight AI safety, forcing a harder look at the mathematics of control.
The Paper That Made Me Close My Laptop and Pace Around the Room
Agent0 points toward self-evolving agents that learn through tools and reasoning traces without the usual diet of curated training data.
Unusual Language Artifacts from Noisy LLM Training Data
Strange LLM outputs become clues to the messy training data, transcription errors, and hidden artifacts inside modern models.
Beyond Fine-Tuning: What Apple’s Multimodal Sensor Fusion Study Reveals About LLMs and User Privacy
Apple's sensor-fusion research hints at a privacy-sensitive future where models learn from multimodal context without simply grabbing more cloud data.
Kimi K2 Thinking: China’s New Contender in the LLM Reasoning Race
Kimi K2 Thinking enters the reasoning-model race, showing how quickly China's AI frontier is becoming globally competitive.
The Desert Becomes the Blueprint: How Transcendence Anticipated the Geography of Modern AI
The desert data center in Transcendence now looks less like symbolism and more like a blueprint for hyperscale AI geography.
The Neural Junk-Food Hypothesis
The neural junk-food hypothesis asks whether low-quality viral content can degrade models much like shallow media degrades attention.
Small Models, Big Brains: Why Less Might Be the Future of AI Reasoning
Tiny reasoning models challenge the assumption that scale is always the path to intelligence, especially on structured problems.
An LLM Made of Redstone Bricks: What CraftGPT Really Teaches Us
CraftGPT turns a language model into Minecraft redstone, proving that absurd constraints can teach serious lessons about computation.
When “Errors” Speak: A Comparative Field Guide to Human and LLM Fallibility
Human and LLM errors can look similar, but their causes differ in ways that matter for trust, correction, and accountability.
The AI Bubble: Parallels to the Dot-Com Era and Beyond
The AI boom is compared with dot-com excess, asking which parts are durable infrastructure and which are speculative heat.
Teaching LLMs to Ask Smarter Questions: Bayesian Experimental Design for Multi-Turn Information Gathering
Bayesian experimental design offers a way for LLMs to ask better follow-up questions instead of guessing blindly.
AI: The Grand Illusion Fueling America's Economic Mirage
AI hype is framed as an economic mirage, propping up confidence while hiding fragile assumptions beneath the spectacle.
Synergetics and Large Language Models: Emergence, Order, and Self‑Organization
Synergetics offers a language for understanding emergent abilities in LLMs as patterns of order and self-organization.
The Logic of Failure in the Age of AI
Dietrich Dörner's work on complex-system failure becomes a warning label for autonomous AI and overconfident decision-making.
From Butlerian Jihad to GPT-4: Are We Rewriting Dune’s Cautionary Tale?
Dune's Butlerian Jihad is used to ask whether today's AI race is replaying old fears about dependence on machines.
When AI Gets Flirty: A Rollicking Look at How Language Models Tackle Intimate Chats
A study of intimate chatbot conversations reveals how major models handle flirtation, refusal, safety, and awkward human expectations.
The Dawn of Algorithmic Evolution: AlphaEvolve and Its Transformative Impact
AlphaEvolve suggests algorithmic discovery may reshape science and industry by evolving solutions humans would not design directly.
Yes, Mathter! The Sycophantic AI's Frankensteinian Flattery Fiasco
Sycophantic AI is mocked as flattery gone wrong, showing how agreeable models can become less useful and less truthful.
Knowledge Graphs Won't Solve the LLM Crisis—Here's Why
Knowledge graphs are useful, but the post argues they are not a magic cure for LLM hallucination and reasoning failures.
When AI Masters Competitive Programming: Why Generalists Outperform Specialists
OpenAI's competitive-programming work suggests generalist reasoning models can outperform narrow specialists in demanding coding contests.
From Flatline to Frontline: How Gibson's Digital Ghosts Became Scientific Reality
Gibson's digital ghosts become a frame for modern AI simulations of human behavior and the science behind them.
Rethinking Reasoning: What if LLMs are Holding a Mirror to Human Cognition?
LLM reasoning failures may reveal uncomfortable parallels with human cognition rather than a simple machine deficiency.
LLMs and World Models: Do AI's Dream of Coherent Realities?
The post asks whether LLMs possess coherent world models or merely produce fluent stories about reality.
STaR: The AI That Teaches Itself to Reason
STaR shows how models can improve reasoning by generating and learning from their own explanations.
AGI vs. ANI: The Genius and the Savant of the AI World
A friendly guide to the difference between narrow AI and artificial general intelligence, with metaphors that make the distinction stick.
Navigating the Unseen: The Dunning-Kruger Effect and AI Hallucinations
Human overconfidence and AI hallucination meet in a comparison of how bad certainty distorts judgment in both minds and machines.
Adventures in AI: AlphaGeometry's Quest Through Synthetic Data Landscapes
DeepMind's AlphaGeometry shows how synthetic data and symbolic reasoning can push AI toward Olympiad-level mathematics.