“I built an evidence-first pipeline where: Content is generated only from a curated KB; Retrieval is chunk-level with reranking; Every important sentence has a clickable citation → click opens the source”

“Running this at 5K RPS with sub-microsecond overhead now. The concurrency primitives in Go made this way easier than Python would've been.”

“起きていたのは、高度に整流された人間思考の再現 (What was happening was a reproduction of highly-refined human thought).”

“The benchmark demands a lot of model's visual reasoning: they must mentally rotate pieces, count coordinates properly, keep track of each piece's starred square, and determine the relationship between different pieces on the board.”

“The article quotes user comments from previous discussions on the topic, providing context for the design decisions. It also mentions the use of specific tools and libraries like PanPhon, Epitran, and Claude 3.7 Sonnet.”

“ShowUI-$π$ achieves 26.98 with only 450M parameters, underscoring both the difficulty of the task and the effectiveness of our approach.”

“ProDM significantly improves CAC scoring accuracy, spatial lesion fidelity, and risk stratification performance compared with several baselines.”

“Findings suggest automated feedback functions are most suited as a supplement to human instruction, with conservative surface-level corrections proving more reliable than aggressive structural interventions for IELTS preparation contexts.”

“SourceRank cannot be reliably used to discriminate between benign and malicious packages in real-world scenarios.”

“LAILA fills a critical need in Arabic AES research, supporting the development of robust scoring systems.”

“The strongest results arise when priors are combined with content embeddings (AUC~0.815), while content-only models remain above chance but substantially weaker (AUC~0.626).”

“LLM-PeerReview is conceptually simple and empirically powerful. The two variants of the proposed approach obtain strong results across four datasets, including outperforming the recent advanced model Smoothie-Global by 6.9% and 7.3% points, respectively.”

“The results demonstrate that SecureBank significantly improves automated attack handling and accelerates identity trust adaptation while preserving conservative and regulator aligned levels of transactional integrity.”

“Would you call this “machine learning,” or a physics data visualization that uses ML pieces?”

“DICE achieves 85.7% agreement with human experts, substantially outperforming existing LLM-based metrics such as RAGAS.”

“Nvidia has agreed to license technology from AI startup Groq for use in some of its artificial intelligence chips, marking the chipmaker’s largest deal and underscoring its push to strengthen competitiveness amid surging demand.”

“The framework achieves a macro F1-score of 88.78% on the UCI-HAR dataset under strict few-shot conditions, outperforming classical approaches.”

“The method achieved a classification accuracy of 0.94 and a specificity of 0.933 for HER2 status scoring.”

“Even leading models achieve only 60% of the expert-defined ideal score.”

“We find that all scoring functions, including using a learned inlier distribution, perform identically.”

“The article's context revolves around using CLIP based region-aware feature fusion.”

“The research is sourced from ArXiv, indicating it's a peer-reviewed research paper.”

“The article is sourced from ArXiv, indicating a peer-reviewed or pre-print research paper.”

“The paper focuses on multi-layer confidence scoring for identifying out-of-distribution samples, adversarial attacks, and in-distribution misclassifications.”

“Probing LLMs for Generalizable Essay Scoring Representations.”

“Focuses on localizing shortcut learning in pixel space.”

“VAAS is a Vision-Attention Anomaly Scoring method.”

“The paper focuses on cross-tokenizer likelihood scoring algorithms for language model distillation.”

“The study is published on ArXiv.”

“DISCODE is a 'Distribution-Aware Score Decoder' for robust automatic evaluation of image captioning.”

“The article likely discusses the methodology used for credit risk estimation, the features included in the non-financial data, and the performance of the models. It may also compare the results with traditional credit scoring methods.”

“The article discusses the application of AI to enhance assessment validity.”

“The paper introduces a framework, scoring mechanism, and real-time model card evaluation pipeline.”

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“The article's context indicates the application of AI within the Basque language learning domain.”

“The research focuses on the development of an Artificial Age Score (AAS) for Large Language Models (LLMs).”

“The paper presents a framework for evaluating LLM structured output reliability.”

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“Test AI agents in the real world with Collinear TraitMix and Together Evals: dynamic persona simulations, multi-turn dialogs, and LLM-as-judge scoring.”

“Simplifying the implementation of more complex LLM-based evaluation metrics, like Hallucination and Moderation.”

“Nvidia revenue up 262%”

“The router balances user preferences for quality, speed and cost. The end result is higher quality and faster LLM responses at lower cost.”

“Alan's expertise and research interests encompass value alignment and AI governance.”

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“N/A”

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“If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations.”

“Model training happened nightly on a Spark cluster... Separating the training technology from the execution technology was nice but the PMML format is limiting...”