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ใครเป็นคนเรียง sequence ล่ะ 🤔 #NEXcheckinKorea #AyoKOREAwithTHAIBUS #THAINEXcheckinKOREA

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43,669 görüntüleme • 6 ay önce •via X (Twitter)

Komedi Seyahat Sanat #NEXcheckinKorea #AyoKOREAwithTHAIBUS #THAINEXcheckinKOREA

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พี่บอย 💥💥ออกมาพูดถึงปมสาเหตุจบรัก 15ปี ของ #อั้มอธิชาติ #นัทมีเรีย คนในวงการบันเทิงเอง พอรู้คร่าวๆ ล่ะ แต่รอเจ้าตัวออกมาพูดเอง พี่บอยเปิดประเด็นน่าสนใจไว้หลายประเด็น ทั้งประเด็นมือที่ 3 ยังไม่มี แต่อั้มคงซุกซนบ่อยจนขาดความไว้ใจของคนเป็นเมีย ถ้าไม่ถึงที่สุดนัทคงไม่ออกมาบอกเลิก 📌📌 ประเด็นเจ้าชู้ก็คงมีล่ะ คนเป็นเมียเวลามีอะไรเข้าหูเยอะๆ มันก็ร้อนหู ผัวเมียอยู่ด้วยกันผ่านสุข ผ่านทุกข์มาด้วยกัน แต่ถ้าวันนึงการอยู่ด้วยกันแล้วไม่มีความสุขอีกต่อไป พยายามที่จะมีลูกด้วยในหลายๆปีแต่ไม่สำเร็จ🥹 ประเด็นพวกนี้น่าสนใจ 🤔🤔

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‼️New AUTOPSY Details Just Dropped Showing HEMORRHAGING In Charlie’s Heart And BOTH Lungs — Consistent With BLUNT Force Trauma👀🤔 A prosecution memorandum in the Tyler Robinson case has highlighted additional findings from the medical examiner’s report that go beyond the previously publicized neck wound. In addition to the described path through the left side of the neck, carotid, jugular veins, and the destruction of cervical vertebrae with spinal cord transection, the report notes hemorrhaging around Charlie’s heart and in both lungs. Hemorrhaging of that nature is commonly associated with blunt force trauma. The timing questions are already circulating: if death was instantaneous and the heart stopped immediately, how did significant hemorrhaging occur in the heart and lungs? Competing accounts about whether a pulse was present in the critical minutes only deepen the issue. Candace is clear that these findings, combined with the rooftop footage showing no visible gun or recoil, further undermine the single-shot-from-Losee narrative. She continues to point toward the possibility of an exploding device near the chest — the wireless microphone transmitter that was under Charlie’s shirt — as a more coherent explanation for both the internal injuries and the overall sequence of events. The more details that surface, the less the official story holds together. FOLLOW Candace Owens , RT and watch her FULL episode linked below.

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The current Second Sphinx Hypothesis Location is a mirror placement to the First Sphinx...🧐🤔 The scan data has been processed through multiple AI systems including Google Gemini and Grok, which returned an 83 to 94 percent probability that the shape is a Sphinx-type monument and a 98 percent probability that the location is archaeologically significant. Proportional diagnostics found the Fibonacci sequence and the golden ratio in the facial geometry, matching the original Sphinx's canonical measurements. A 54 percent probability of a male face was returned alongside a 29 percent probability of female. The nemes headdress is visible in the scan data, and unlike the original Sphinx, which lost its serpent ornament at some point in history, the snake appears to still be attached on the second Sphinx. The proportional mismatch between head and body, one of the most discussed anomalies of the original Sphinx and a central argument in the theory that its head was recarved from something older, appears to be present in the second Sphinx as well, which either means the small-head design was intentional or that both monuments were reworked at the same time from the same original form. The Dream Stela, an inscription placed between the original Sphinx's paws during the New Kingdom, has always depicted two sphinxes facing away from each other, and archaeologists have long dismissed this as artistic rather than literal. The fact that the second Sphinx faces the opposite direction to the original gives that imagery a new weight. Excavation permission has been submitted to the Egyptian Ministry of Antiquities. The location is accessible, covered only by a sand mound deposited during 1920s excavations of nearby mastabas, and no significant dig infrastructure would be required. Everything now depends on whether the Egyptian government says yes.

UFO mania

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There’s been two papers released in the past couple months, one by Google and one by NVIDIA, that argue that ordering the documents retrieved by RAG systems can enhance performance. However, they both give two different strategies on HOW these documents should be ordered 🤔 Both papers agree on two main points: 1️⃣ There’s a fundamental issue in RAG - as more documents are retrieved, more irrelevant context (e.g., hard negatives) are introduced, which leads to confusion for the LLM and eventually degrades the quality of the generated output. This is called an inverted-U performance curve. 2️⃣ Ordering the retrieved documents is a key lever for optimizing RAG performance. Google Cloud researchers proposed ordering results based on relevance scores: The authors in this paper argue for relevance-based reordering, or ordering the retrieved chunks based on their similarity scores, so the most relevant documents are at the beginning and the end of the inputs to counter the “lost in the middle” effect. NVIDIA researchers proposed ordering results based on the original sequence of document chunks: The authors of this paper argue for Order-Preserving Reordering, or Order-Preserve RAG (OP-RAG), to maintain the logically coherent content flow of the document. So they preserved the original order of retrieved document chunks in the source text, instead of ranking them by relevance scores. So which one is right? It probably depends on the specific use case and dataset - relevance-based reordering could perform better in tasks where you need fast access to the most critical information (e.g., fact retrieval, QA systems), while order-preserving RAG might be better where you need to understand the sequential structure of information (e.g., narrative or legal documents). There are still so many uncertainties in AI - we don’t actually know what we’re doing, and it takes awhile to figure out the best strategies for most things! Excited to see more research about this.

There’s been two papers released in the past couple months, one by Google and one by NVIDIA, that argue that ordering the documents retrieved by RAG systems can enhance performance. However, they both give two different strategies on HOW these documents should be ordered 🤔 Both papers agree on two main points: 1️⃣ There’s a fundamental issue in RAG - as more documents are retrieved, more irrelevant context (e.g., hard negatives) are introduced, which leads to confusion for the LLM and eventually degrades the quality of the generated output. This is called an inverted-U performance curve. 2️⃣ Ordering the retrieved documents is a key lever for optimizing RAG performance. Google Cloud researchers proposed ordering results based on relevance scores: The authors in this paper argue for relevance-based reordering, or ordering the retrieved chunks based on their similarity scores, so the most relevant documents are at the beginning and the end of the inputs to counter the “lost in the middle” effect. NVIDIA researchers proposed ordering results based on the original sequence of document chunks: The authors of this paper argue for Order-Preserving Reordering, or Order-Preserve RAG (OP-RAG), to maintain the logically coherent content flow of the document. So they preserved the original order of retrieved document chunks in the source text, instead of ranking them by relevance scores. So which one is right? It probably depends on the specific use case and dataset - relevance-based reordering could perform better in tasks where you need fast access to the most critical information (e.g., fact retrieval, QA systems), while order-preserving RAG might be better where you need to understand the sequential structure of information (e.g., narrative or legal documents). There are still so many uncertainties in AI - we don’t actually know what we’re doing, and it takes awhile to figure out the best strategies for most things! Excited to see more research about this.

Victoria Slocum

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