From PDE Guarantees to LLM Inference: What BEACONS Gets Right About Reliability
BEACONS offers a model for reliability that AI systems badly need: explicit bounds, checkable guarantees, and less benchmark theater.
Science
18 posts
The Assistant Axis: when “helpful” is a place, not a promise
New interpretability work suggests assistant behavior may be a geometric direction in model space, making persona control more concrete than branding.
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.
Bridging Context Engineering in AI with Requirements Engineering
Context engineering and requirements engineering converge, suggesting better ways to specify AI-assisted software before code is written.
AI Magnifies Your Team’s Strengths and Weaknesses – Insights from Google’s 2025 DORA Report
Google's DORA findings suggest AI amplifies team quality: strong practices get stronger, broken processes get louder.
Less Is More: When Overthinking Leads to Worse Outcomes
More thinking can make both humans and models worse, revealing when deliberation becomes noise rather than wisdom.
Anticipations of Artificial Intelligence in Literature
A tour of artificial intelligence in literature, from ancient automata to modern science fiction's uneasy machine minds.
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.
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.
Unleashing AI: The Wild World of Uncensored Models
Uncensored models promise creative freedom and research access, but also expose the tradeoffs that safety layers usually conceal.
The Great Saturation: When Markets, Minds, and Machines Hit Their Limits
Saturation appears across markets, research, and models, revealing what happens when growth hits limits and novelty thins out.
How AI Cracked One of Biology's Greatest Mysteries: The Story of Protein Folding
The Nobel recognition for protein-folding AI becomes a story about how machine learning cracked a central biological mystery.
The AI Cargo Cult: Mimicry vs. True Intelligence in the Pursuit of AGI
The post warns against an AI cargo cult that confuses impressive mimicry with the harder problem of genuine intelligence.
Navigating the AI Seas: The Art and Science of LLM Steerability
LLM steerability is treated as both craft and control problem: how to guide powerful models without losing the plot.
A Short Trip Through Data Science Workflows With KNIME
A practical introduction to KNIME and the shift from fragile spreadsheet work toward reproducible data workflows.
No Boss, All Brains: The New Paradigm of Decentralized AI Agents
Decentralized multi-agent systems promise problem-solving without a central boss, but coordination becomes the real challenge.
Multi-Agent LLMs: Exploring the Future of AI Collaboration
Multi-agent LLM systems are explored as a path toward distributed reasoning, specialization, and collaborative AI workflows.
Exploring the Retro Sci-Fi Linguist: Use Cases and Capabilities
The Retro Sci-Fi Linguist GPT is introduced as a tool for exploring early utopian fiction and translation between English and German.