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<title>AI News: Lilian Weng</title>
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<description>Latest publications from Lilian Weng, aggregated by AI News from the official source.</description>
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<lastBuildDate>Fri, 23 Oct 2026 19:08:30 GMT</lastBuildDate>
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<item><title>Lilian Weng: Harness Engineering for Self-Improvement</title><link>https://lilianweng.github.io/posts/2026-07-04-harness/</link><guid isPermaLink="false">https://lilianweng.github.io/posts/2026-07-04-harness/</guid><pubDate>Sat, 04 Jul 2026 00:00:00 GMT</pubDate><category>voices</category><description>The concept of recursive self-improvement (RSI) dates back to I. J. Good (1965) , where he defined an “ultraintelligent machine” as a system that can surpass humans in all intellectual activities and design better machines to improve itself. Yudkowsky (2008) used the phrase “r…</description></item>
<item><title>Lilian Weng: Scaling Laws, Carefully</title><link>https://lilianweng.github.io/posts/2026-06-24-scaling-laws/</link><guid isPermaLink="false">https://lilianweng.github.io/posts/2026-06-24-scaling-laws/</guid><pubDate>Wed, 24 Jun 2026 00:00:00 GMT</pubDate><category>voices</category><description>Scaling laws are one of the most critical empirical findings in deep learning. The observation is simple in form: the training loss $L$ decreases predictably as we scale up model size $N$, dataset size $D$, and compute $C$, following a power-law curve, which appears as a strai…</description></item>
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