<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI Safety &amp; Alignment — The Latent Daily</title><description>Making AI systems safe, honest and aligned.</description><link>https://thelatentdaily.com/</link><language>en-us</language><atom:link href="https://thelatentdaily.com/rss/ai-safety-alignment.xml" rel="self" type="application/rss+xml"/><item><title>InstructGPT explained: how human feedback turned language models into assistants</title><link>https://thelatentdaily.com/research/instructgpt-rlhf-paper-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/research/instructgpt-rlhf-paper-explained/</guid><description>The 2022 InstructGPT paper showed that reinforcement learning from human feedback makes models more helpful and less harmful. The method, the results and the trade-offs.</description><pubDate>Sun, 18 Oct 2026 05:20:00 GMT</pubDate><category>NLP &amp; LLMs</category><category>research</category><category>rlhf</category><category>alignment</category><category>llms</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Towards Monosemanticity explained: finding the concepts inside a neural network</title><link>https://thelatentdaily.com/research/towards-monosemanticity-sparse-autoencoders-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/research/towards-monosemanticity-sparse-autoencoders-explained/</guid><description>Anthropic used sparse autoencoders to decompose a model&apos;s neurons into thousands of interpretable features. What superposition is, what they found and why it matters.</description><pubDate>Sun, 18 Oct 2026 05:12:00 GMT</pubDate><category>Interpretability</category><category>research</category><category>interpretability</category><category>sparse-autoencoders</category><category>anthropic</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Levels of AGI explained: DeepMind&apos;s framework for measuring progress toward AGI</title><link>https://thelatentdaily.com/research/levels-of-agi-deepmind-framework-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/research/levels-of-agi-deepmind-framework-explained/</guid><description>Google DeepMind proposed rating AI systems by performance and generality, like levels of self-driving cars. The six levels, the principles behind them and the debate.</description><pubDate>Sun, 18 Oct 2026 05:10:00 GMT</pubDate><category>AGI &amp; Frontier</category><category>research</category><category>agi</category><category>deepmind</category><category>frameworks</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>What is AI alignment? The problem of making AI do what we intend</title><link>https://thelatentdaily.com/articles/what-is-ai-alignment-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/what-is-ai-alignment-explained/</guid><description>Why it is hard to make AI systems pursue the goals we actually want, the main techniques used today — from RLHF to constitutional AI — and the open research problems.</description><pubDate>Sun, 18 Oct 2026 04:28:00 GMT</pubDate><category>AI Safety &amp; Alignment</category><category>ai-safety</category><category>alignment</category><category>rlhf</category><category>research</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Frontier AI safety frameworks explained: how labs decide a model is safe to release</title><link>https://thelatentdaily.com/articles/frontier-ai-safety-frameworks-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/frontier-ai-safety-frameworks-explained/</guid><description>Responsible scaling policies, preparedness frameworks and dangerous-capability evaluations: how leading AI labs test models for catastrophic risks before release.</description><pubDate>Sun, 18 Oct 2026 04:27:00 GMT</pubDate><category>AI Safety &amp; Alignment</category><category>ai-safety</category><category>frontier-ai</category><category>evaluations</category><category>governance</category><author>dario_admin@resolvia-crm.tech</author></item></channel></rss>