<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>AI Breakthroughs — TKDB</title><description>Carefully verified reporting on major AI results: what was shown, what was only claimed, and what is still open.</description><link>https://tkdb.pages.dev/</link><item><title>Looking back at 2017&apos;s Transformer: the translation model that dropped recurrence for attention</title><link>https://tkdb.pages.dev/blogs/ai-breakthroughs/transformer-2017/</link><guid isPermaLink="true">https://tkdb.pages.dev/blogs/ai-breakthroughs/transformer-2017/</guid><description>A retrospective on &quot;Attention Is All You Need&quot;: what the 2017 paper actually showed, how an independent lab reproduced it, how it spread to GPT and BERT, and the limits that remain.</description><pubDate>Sun, 25 Oct 2026 00:00:00 GMT</pubDate><category>transformers</category><category>attention</category><category>machine-translation</category><category>retrospective</category><category>peer-reviewed</category></item></channel></rss>