<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>The Artificial Engineer</title><description>Practical ML engineering notes. Deep dives for engineers and accessible explainers for everyone.</description><link>https://theartificialengineer.ai/</link><language>en-us</language><item><title>Notes from ICLR 2026: Five Orals on ML Architectures and Training</title><link>https://theartificialengineer.ai/posts/iclr-2026-ml-architectures-orals/</link><guid isPermaLink="true">https://theartificialengineer.ai/posts/iclr-2026-ml-architectures-orals/</guid><description>Notes from Day 2&apos;s first oral session at ICLR 2026. Five papers on learning rate schedules, MoE sparsity, curriculum data, softmax expressivity, and pre-training under infinite compute.</description><pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate><category>engineers</category><category>iclr</category><category>conference</category><category>pretraining</category><category>moe</category><category>scaling-laws</category><category>curriculum</category><category>transformers</category></item><item><title>Notes from ICLR 2026: Six Orals on LLMs and Evaluation</title><link>https://theartificialengineer.ai/posts/iclr-2026-llm-evaluation-orals/</link><guid isPermaLink="true">https://theartificialengineer.ai/posts/iclr-2026-llm-evaluation-orals/</guid><description>Notes from the second oral session at ICLR 2026. Six papers on reward hacking detection, multi-turn reliability (the Best Paper), micro-benchmarking, value-difference generation, preference interpretability, and mutual-judgment alignment.</description><pubDate>Thu, 23 Apr 2026 00:00:00 GMT</pubDate><category>engineers</category><category>iclr</category><category>conference</category><category>llms</category><category>evaluation</category><category>alignment</category><category>rlhf</category></item><item><title>Notes from ICLR 2026: Five Orals on LLMs and Reasoning</title><link>https://theartificialengineer.ai/posts/iclr-2026-llm-reasoning-orals/</link><guid isPermaLink="true">https://theartificialengineer.ai/posts/iclr-2026-llm-reasoning-orals/</guid><description>Notes from the first oral session at ICLR 2026. Five papers on active reasoning, long-context memory, CoT verification, retriever training, and model merging.</description><pubDate>Thu, 23 Apr 2026 00:00:00 GMT</pubDate><category>engineers</category><category>iclr</category><category>conference</category><category>llms</category><category>reasoning</category><category>rl</category><category>long-context</category><category>retrieval</category><category>interpretability</category></item><item><title>Notes from ICLR 2026: Maja Mataric on Why AI Needs a Body</title><link>https://theartificialengineer.ai/posts/iclr-2026-mataric-human-centered-ai/</link><guid isPermaLink="true">https://theartificialengineer.ai/posts/iclr-2026-mataric-human-centered-ai/</guid><description>Opening keynote at ICLR 2026 from USC and Google DeepMind&apos;s Maja Mataric — a case that intelligence without a body misses the point, and that the robots we actually need aren&apos;t the ones trying hardest to look human.</description><pubDate>Thu, 23 Apr 2026 00:00:00 GMT</pubDate><category>everyone</category><category>iclr</category><category>conference</category><category>human-centered-ai</category><category>robotics</category><category>embodiment</category></item><item><title>Why I Started The Artificial Engineer</title><link>https://theartificialengineer.ai/posts/why-this-blog/</link><guid isPermaLink="true">https://theartificialengineer.ai/posts/why-this-blog/</guid><description>A two-track ML blog: reproducible engineering deep dives for practitioners, and clear explainers for everyone.</description><pubDate>Tue, 02 Sep 2025 00:00:00 GMT</pubDate><category>everyone</category><category>ml-engineering</category><category>reproducibility</category><category>learning-in-public</category></item></channel></rss>