New research maps the step‑by‑step reasoning of large language models, revealing where their chain‑of‑thought breaks down—especially on benchmark puzzles and moral dilemmas. An open‑source annotation framework shows how to spot failures and improve autopilot AI. Dive into the findings and see the traces yourself. #ChainOfThought #ReasoningTraces #MoralDilemmas #LLMBenchmarks

🔗 https://aidailypost.com/news/study-maps-ai-reasoning-steps-pinpointed-where-they-fail

**Bài Đính Chính:**
Benchmark so sánh NVIDIA RTX Pro 6000 và DGX Spark cho inference LLM (8B/70B). RTX Pro 6000 nhanh **6-7 lần** dù batch size từ 1-32. Ví dụ: Llama 3.1 8B batch 1: DGX Spark 100.1s vs RTX 14.3s. Sự khác biệt do băng thông RAM: RTX 1.792 GB/s (DGX chỉ 273 GB/s). #RTXPro6000 #DGXSpark #LLMBenchmarks #MởRộngAI
(495/500 ký tự)

https://www.reddit.com/r/LocalLLaMA/comments/1o9it7v/benchmark_visualization_rtx_pro_6000_vs_dgx_spark/

Tencent Releases its Hunyuan T1 AI Reasoning Model, Beating DeepSeek R1, GPT-4.5, o1 Across Multiple Benchmarks

#AI #GenAI #TencentAI #HunyuanT1 #AIReasoning #EnterpriseAI #LLMbenchmarks #ChinaAI #MMLU #MathAI #AIModels #AIInference

https://winbuzzer.com/2025/03/23/tencents-releases-its-hunyuan-t1-reasoning-model-beating-deepseek-r1-gpt-4-5-o1-across-benchmarks-xcxwbn/