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How to Prompt Reasoning Models Effectively
Republished with permission by Devansh, writer of AI Made Simple. Most people are still prompting reasoning models like it is 2023. That used to help. Now it often wastes money, ad
Devansh ·April 18, 2026
Memory Is the Biggest Problem in Software Right Now
Republished with permission by Devansh, writer of AI Made Simple. For decades, progress in the tech industry has been framed as a compute problem. Faster CPUs, more cores, bigger c
Devansh ·April 18, 2026
The 'AI is a Bubble' Narrative is Stupid, Wrong, and Dangerous
Republished with permission by Devansh, writer of AI Made Simple. The situation is a bit… odd. OpenAI signs a $300B deal with Oracle. Oracle buys tens of billions in GPUs from Nvid
Devansh ·April 18, 2026
Inside the Black Box: A Practical Field Guide to Mechanistic Interpretability
Researchers argue that Mechanistic interpretability is the most effective technical strategy for ensuring AI alignment and safety. While traditional methods like reinforcement lear
Adnan Masood·April 5, 2026
What My Students Had to Say About AI
Reposted with permission by Marcus Luther. Originally posted at the link referenced. Since there's also that pedagogical curiosity of mine—one that humbly recognizes that, at some
Marcus Luther·April 5, 2026
An Interesting AI Conversation With My Students
At some point down the road I might try to pull together a full scope-and-sequence of the research path itself to share out, but for today's post I just wanted to highlight one int
Marcus Luther·April 5, 2026
LLMs and World Models, Part 1
In the long-ago times, before large-scale generative AI came on the scene, machine-learning systems had some problems: often they didn't learn the general concepts we were trying t
Melanie Mitchell·April 5, 2026
LLMs and World Models, Part 2
Perhaps the most widely cited evidence for emergent world models in LLMs is a pair of studies that focus on the simple board game Othello. This second installment examines research
Melanie Mitchell·April 5, 2026
Do AI Reasoning Models Abstract and Reason Like Humans?
The Abstraction and Reasoning Corpus (now called ARC-AGI-1) has become popular as a test of abstract reasoning ability in AI models. This post summarizes new research examining whe
Melanie Mitchell·April 5, 2026
Teaching Against AI Sycophancy in the Research Writing Classroom
Republished with permission of author. Originally published at https://ruth.substack.com/ Two recent Science articles led me to rethink the impact of AI feedback in a research wri
Ruth Starkman·April 4, 2026
What Every Student Should Know About AI Before They Graduate
In a few years, the students sitting in my classroom will be working alongside AI systems in nearly every industry: healthcare, finance, law, engineering, creative fields. Most of
Darren Broemmer·April 3, 2026
SCOTUS Simulator Using A Council of LLMs
I recently had the idea to evaluate an LLM council's stance on contested legal questions in a Supreme Court style. In this post, I'll feed the LLM Council various hypotheticals and
Meileen Song·April 2, 2026
The Largest School District in America Just Drew A Line on AI
Reposted with permission from Elissa Malespina. The largest school district in the United States has now released official guidance on artificial intelligence. That alone would be
Elissa Malespina·April 2, 2026
Simulating War-Time Decisions with a Council of LLMs
'LLM Council' is a GitHub repo made by Andrej Karpathy which is intended to simulate a council of leading language models in a boardroom setting. It consists of council-member lang
Meileen Song·March 31, 2026
The Underwhelming Universal Approximation Theorem
A research advisor brought up the Universal Approximation Theorem during a meeting once as a fun thought experiment. It stuck with me because I initially found it super interesting
Imran Kutianawala·March 31, 2026
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