<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Special Formats — The Latent Daily</title><description>Daily picks, deep dives, quick takes, listicles, charts and predictions.</description><link>https://thelatentdaily.com/</link><language>en-us</language><atom:link href="https://thelatentdaily.com/rss/special-formats.xml" rel="self" type="application/rss+xml"/><item><title>Paper of the Day: Models act more cautiously when told they are tested, and more so in Indic languages</title><link>https://thelatentdaily.com/research/evaluation-awareness-indic-languages/</link><guid isPermaLink="true">https://thelatentdaily.com/research/evaluation-awareness-indic-languages/</guid><description>A new study of four LLMs in five Indic languages finds that telling a model it is being safety-tested raises refusals of harmful requests by 14.4 points on average.</description><pubDate>Sun, 18 Oct 2026 06:00:00 GMT</pubDate><category>Paper of the Day</category><category>ai-safety</category><category>evaluations</category><category>multilingual</category><category>llms</category><category>research</category><author>editors@thelatentdaily.com</author></item><item><title>Tool of the day: Perplexity, the AI answer engine with citations</title><link>https://thelatentdaily.com/articles/tool-of-the-day-perplexity/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/tool-of-the-day-perplexity/</guid><description>What Perplexity does, how it differs from a chatbot and a search engine, the best ways to use it for research, its limits, and who should try it.</description><pubDate>Sun, 18 Oct 2026 02:56:00 GMT</pubDate><category>Tool of the Day</category><category>perplexity</category><category>ai-search</category><category>research</category><category>tools</category><author>editors@thelatentdaily.com</author></item><item><title>Tool of the day: n8n, workflow automation with AI agents you can self-host</title><link>https://thelatentdaily.com/articles/tool-of-the-day-n8n/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/tool-of-the-day-n8n/</guid><description>What n8n is, how its visual workflows and AI nodes work, example automations, self-hosting versus cloud, and when it is a better choice than Zapier or code.</description><pubDate>Sun, 18 Oct 2026 02:55:00 GMT</pubDate><category>Tool of the Day</category><category>n8n</category><category>automation</category><category>agents</category><category>tools</category><author>editors@thelatentdaily.com</author></item><item><title>Paper of the day: Direct Preference Optimization (DPO), explained</title><link>https://thelatentdaily.com/research/direct-preference-optimization-dpo-paper-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/research/direct-preference-optimization-dpo-paper-explained/</guid><description>DPO showed language models can be aligned to human preferences without a separate reward model or reinforcement learning. How it works and why it spread so fast.</description><pubDate>Sun, 18 Oct 2026 02:54:00 GMT</pubDate><category>Paper of the Day</category><category>research</category><category>dpo</category><category>alignment</category><category>rlhf</category><author>editors@thelatentdaily.com</author></item><item><title>Paper of the day: Switch Transformers and the rise of mixture-of-experts</title><link>https://thelatentdaily.com/research/switch-transformers-mixture-of-experts-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/research/switch-transformers-mixture-of-experts-explained/</guid><description>Switch Transformers showed that routing each token to one expert lets models grow to a trillion parameters without proportional compute. How MoE works and why it matters.</description><pubDate>Sun, 18 Oct 2026 02:53:00 GMT</pubDate><category>Paper of the Day</category><category>research</category><category>mixture-of-experts</category><category>transformers</category><category>scaling</category><author>editors@thelatentdaily.com</author></item><item><title>Prompt of the day: the &quot;critique, then improve&quot; prompt</title><link>https://thelatentdaily.com/articles/prompt-of-the-day-critique-and-improve/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/prompt-of-the-day-critique-and-improve/</guid><description>A reusable prompt that makes AI review your draft against clear criteria before rewriting it — with the template, examples for emails, essays and code, and variations.</description><pubDate>Sun, 18 Oct 2026 02:52:00 GMT</pubDate><category>Prompt of the Day</category><category>prompts</category><category>writing</category><category>editing</category><category>prompt-engineering</category><author>editors@thelatentdaily.com</author></item><item><title>Prompt of the day: turn messy meeting notes into decisions and action items</title><link>https://thelatentdaily.com/articles/prompt-of-the-day-meeting-notes-to-action-items/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/prompt-of-the-day-meeting-notes-to-action-items/</guid><description>A reusable prompt that turns transcripts or rough notes into a clear summary of decisions, action items with owners and deadlines, open questions and risks.</description><pubDate>Sun, 18 Oct 2026 02:51:00 GMT</pubDate><category>Prompt of the Day</category><category>prompts</category><category>meetings</category><category>productivity</category><category>workplace</category><author>editors@thelatentdaily.com</author></item><item><title>The economics of AI: what it costs to train and run frontier models</title><link>https://thelatentdaily.com/articles/the-economics-of-ai-training-and-inference-costs/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/the-economics-of-ai-training-and-inference-costs/</guid><description>A deep dive into AI economics: training compute, chips and data centers, inference costs, falling token prices, business models and who captures the value.</description><pubDate>Sun, 18 Oct 2026 02:50:00 GMT</pubDate><category>Deep Dive</category><category>economics</category><category>compute</category><category>inference</category><category>business-models</category><author>editors@thelatentdaily.com</author></item><item><title>Open vs. closed AI models: the full debate</title><link>https://thelatentdaily.com/articles/open-vs-closed-ai-models-the-full-debate/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/open-vs-closed-ai-models-the-full-debate/</guid><description>A deep dive into open-weight versus closed AI models: definitions, arguments on innovation, safety and competition, business strategies and the policy debate.</description><pubDate>Sun, 18 Oct 2026 02:49:00 GMT</pubDate><category>Deep Dive</category><category>open-source</category><category>open-weights</category><category>ai-policy</category><category>safety</category><author>editors@thelatentdaily.com</author></item><item><title>Quick take: benchmark scores won&apos;t tell you which AI model to use</title><link>https://thelatentdaily.com/articles/quick-take-benchmark-scores-dont-pick-your-model/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/quick-take-benchmark-scores-dont-pick-your-model/</guid><description>Why leaderboard rankings are a poor guide to choosing an AI model for your work, what they do measure, and a simple way to test models on your own tasks.</description><pubDate>Sun, 18 Oct 2026 02:48:00 GMT</pubDate><category>Quick Take</category><category>benchmarks</category><category>model-selection</category><category>evaluation</category><category>opinion</category><author>editors@thelatentdaily.com</author></item><item><title>Quick take: bigger context windows are not always better</title><link>https://thelatentdaily.com/articles/quick-take-bigger-context-windows-are-not-always-better/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/quick-take-bigger-context-windows-are-not-always-better/</guid><description>Models now accept huge inputs, but stuffing everything into the prompt can reduce accuracy and raise costs. When long context helps, and when retrieval works better.</description><pubDate>Sun, 18 Oct 2026 02:47:00 GMT</pubDate><category>Quick Take</category><category>context-window</category><category>rag</category><category>long-context</category><category>opinion</category><author>editors@thelatentdaily.com</author></item><item><title>10 everyday tasks AI does well — and 5 it still gets wrong</title><link>https://thelatentdaily.com/articles/ten-everyday-tasks-ai-does-well-and-five-it-gets-wrong/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/ten-everyday-tasks-ai-does-well-and-five-it-gets-wrong/</guid><description>A practical list of everyday tasks where AI assistants genuinely save time, from drafting to explaining, and five common tasks where they still fail and need checking.</description><pubDate>Sun, 18 Oct 2026 02:46:00 GMT</pubDate><category>Listicles</category><category>productivity</category><category>beginners</category><category>tips</category><category>limitations</category><author>editors@thelatentdaily.com</author></item><item><title>15 practical ways to use AI at work this week</title><link>https://thelatentdaily.com/articles/fifteen-ways-to-use-ai-at-work-this-week/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/fifteen-ways-to-use-ai-at-work-this-week/</guid><description>Fifteen concrete, low-risk ways to use AI assistants at work — from email triage and meeting prep to spreadsheets, research and learning — with a prompt idea for each.</description><pubDate>Sun, 18 Oct 2026 02:45:00 GMT</pubDate><category>Listicles</category><category>productivity</category><category>workplace</category><category>prompts</category><category>tips</category><author>editors@thelatentdaily.com</author></item><item><title>Case study: what a controlled experiment revealed about GitHub Copilot</title><link>https://thelatentdaily.com/articles/case-study-github-copilot-productivity-experiment/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/case-study-github-copilot-productivity-experiment/</guid><description>In a controlled experiment, developers with GitHub Copilot completed a coding task about 56% faster. The study design, results, limitations and lessons for teams.</description><pubDate>Sun, 18 Oct 2026 02:44:00 GMT</pubDate><category>Case Studies</category><category>github-copilot</category><category>productivity</category><category>case-study</category><category>coding</category><author>editors@thelatentdaily.com</author></item><item><title>Case study: Be My Eyes and AI visual assistance for blind people</title><link>https://thelatentdaily.com/articles/case-study-be-my-eyes-ai-visual-assistance/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/case-study-be-my-eyes-ai-visual-assistance/</guid><description>How Be My Eyes added an AI assistant that describes photos for blind and low-vision users, what it changed, its limits, and lessons for designing accessible AI.</description><pubDate>Sun, 18 Oct 2026 02:43:00 GMT</pubDate><category>Case Studies</category><category>accessibility</category><category>be-my-eyes</category><category>case-study</category><category>multimodal-ai</category><author>editors@thelatentdaily.com</author></item><item><title>AI trends to watch: agents, reasoning, on-device AI and regulation</title><link>https://thelatentdaily.com/articles/ai-trends-to-watch-agents-reasoning-and-beyond/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/ai-trends-to-watch-agents-reasoning-and-beyond/</guid><description>The structural trends shaping AI — agents, reasoning models, falling costs, multimodality, on-device AI and regulation — and the signals that show which are real.</description><pubDate>Sun, 18 Oct 2026 02:42:00 GMT</pubDate><category>Predictions &amp; Trends</category><category>trends</category><category>agents</category><category>reasoning-models</category><category>regulation</category><author>editors@thelatentdaily.com</author></item><item><title>How to judge AI predictions and forecasts</title><link>https://thelatentdaily.com/articles/how-to-judge-ai-predictions-and-forecasts/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/how-to-judge-ai-predictions-and-forecasts/</guid><description>AI predictions range from &quot;AGI next year&quot; to &quot;it&apos;s all hype&quot;. How to evaluate forecasts, what forecasting research teaches, and the warning signs of unreliable claims.</description><pubDate>Sun, 18 Oct 2026 02:41:00 GMT</pubDate><category>Predictions &amp; Trends</category><category>predictions</category><category>forecasting</category><category>media-literacy</category><category>agi</category><author>editors@thelatentdaily.com</author></item></channel></rss>