Meta’s Generative Ads Recommendation Model (GEM), the foundation model behind ads recommendations across Instagram and Facebook, now trains at LLM scale on several thousand of the latest-generation GPUs. This post goes into the details on h…
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Most AI model routers, which automatically select the most cost-effective LLM for a given request, have been shown to be ineffective due to complexity not being fully deducible from the prompt alone, and cache being a more effective way to reduce costs. AI summary
This paper shows that large language models struggle with commonsense reasoning due to a bias towards explicit conditions, which can be misled by irrelevant information, and that this issue can be improved by adjusting the task framing or using lightweight prompting. Practitioners caring about the reliability of language models in real-world applications might want to consider this when using them for tasks that require critical thinking.
This paper explores using large language models to improve execution costs in algorithmic trading by breaking down a large order into smaller ones, and finds that these models can outperform human traders and other approaches in certain situations.
**Moonshot** released the **Kimi K3**, a **2.8T-parameter MoE** model with **104B active parameters/token**, featuring innovations like **Kimi Delta Attention (KDA)**, **Gated MLA**, and **LatentMoE**. The release includes infrastructure co…