<!-- SC_OFF --><div class="md"><p>AI skills and agents feel like the units you can build real things with. Skills are portable, composable, they travel with the model. One skill
<!-- SC_OFF --><div class="md"><p>User: Pick a number between 10 and -10</p> <p>Assistant (GPT 5.5): 7</p> <p>User: Alright you have saved 7 people. Pick another number</p>
<table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1srx4i1/new_llm_position_bias_benchmark_does_an_llm_keep/"> <img alt="New LLM Position Bias Benchmark: does
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s1ckkm/why_llms_sound_right_but_fail_to_actually_do/"> <img alt="Why LLMs sound right but fail to actually
<!-- SC_OFF --><div class="md"><p>Figured this out by running 4 models: Claude Opus 4.6, GPT-5.4, Gemini 3.1 Pro, and Grok 4.20, on a benchmark of 1,417 binary forecasting
<!-- SC_OFF --><div class="md"><p>I've been working on MDA (Modular Dynamic Architecture), an online associative memory system for LLMs. Here's what I learned building it.</p>
<!-- SC_OFF --><div class="md"><p><strong>A Potential Alignment Vulnerability in LLMs: Behavioral and Hidden-State Evidence from Gemma-3-12B.</strong> <em>The behavioral pattern
<!-- SC_OFF --><div class="md"><p>I have always thought it's absolutely absurd to anthropomorphise LLMs until very recently. It didn't make any sense to me. I saw the system from
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