

Qwen released Qwen2.5-VL-32B-Instruct, the second largest vision 32B model.

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Qwen released Qwen2.5-VL-32B-Instruct, the second largest vision 32B model.
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🚀 GraphRAG: The Practical Guide for Cost-Effective Document Analysis with Knowledge Graphs
— Satya Mallick (@LearnOpenCV) 24 mars 2025
GraphRAG integrates structured Knowledge Graphs (KGs) with semantic chunks (vectors), enabling LLMs to reason over multi-hop connections for complex queries and connect the dots between… pic.twitter.com/KMMrSLbM2v
GraphRAG: The Practical Guide for Cost-Effective Document Analysis with Knowledge Graphs GraphRAG integrates structured Knowledge Graphs (KGs) with semantic chunks (vectors), enabling LLMs to reason over multi-hop connections for complex queries and connect the dots between

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Deepseek-v3-0324 is now also available on @lmarena_ai for you to try!

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AI is quietly transforming cities—smarter traffic lights, safer streets, better parking. It’s not about flashy tech, it’s about real-time, edge intelligence. What’s the most interesting urban AI use case you’ve seen? https://
eu1.hubs.ly/H0hLd3F0 #AI #EdgeAI #selfdriving #smartcities

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DeepSeek-V3-0324 dropped on @huggingface
, an upgraded version of a previously released V3 version.

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Guest Lecture 6 CS329A by Prof. Jeff Clune:Open-ended Agent Learning in the Era of Foundation Models https://
buff.ly/ILupGfY
#AI #MachineLearning #DeepLearning #LLMs #DataScience

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Finally our Complete Computer Vision Bootcamp With Pytorch and Tensorflow is Live in Udemy.
You can get this course in 399rs INR. It has more than 50+ hours of content and it includes everything 🙂 Happy Learning!! https://
udemy.com/course/complet
e-computer-vision-bootcamp-with-pytoch-tensorflow/?couponCode=MARCH01
…

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Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't Quy-Anh Dang, Chris Ngo: https://
arxiv.org/abs/2503.16219 #DeepLearning #ChatGPT #ReinforcementLearning
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Paper: https://arxiv.org/pdf/2503.05383
Code:

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AI agents can play StarCraft II now? AVA, proposed in this paper from @CamelAIOrg , can execute complex tactical maneuvers without explicit training, achieving comparable performance to traditional MARL methods that require substantial training iterations. A win for VLM and RL!