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  • All (21181) +146
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  • DevOps (940) +5
  • Software (11185) +102
  • IT (5838) +28
  • Education (48)
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  • All (21181) +146
    • AI (3169) +10
    • DevOps (940) +5
    • Software (11185) +102
    • IT (5838) +28
    • Education (48)
  • Notice
  • All (21181) +146
  • AI (3169) +10
  • DevOps (940) +5
  • Software (11185) +102
  • IT (5838) +28
  • Education (48)
  • Notice
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  • 1 month ago · ai

    Building AI Agents with Google Gemini 3 and Open Source Frameworks

    The world of AI agents is rapidly evolving from simple chatbots to sophisticated, semi-autonomous systems that can make complex decisions in the real world. Thi...

    #Google Gemini #AI agents #LangChain #open-source frameworks #machine learning
  • 1 month ago · ai

    Building production AI on Google Cloud TPUs with JAX

    JAX has become a key framework for developing state‑of‑the‑art foundation models across the AI landscape, and not just at Google. Leading LLM providers such as...

    #JAX #Google Cloud TPUs #AI infrastructure #Machine Learning #Flax
  • 1 month ago · ai

    [Paper] Sampling on Metric Graphs

    Metric graphs are structures obtained by associating edges in a standard graph with segments of the real line and gluing these segments at the vertices of the g...

    #research #paper #ai #machine-learning
  • 1 month ago · ai

    The Machine Learning Lessons I’ve Learned This Month

    Christmas connections, Copilot's costs, careful no-choices The post The Machine Learning Lessons I’ve Learned This Month appeared first on Towards Data Science....

    #machine learning #GitHub Copilot #ML best practices #cost management #monthly lessons
  • 1 month ago · ai

    The Machine Learning “Advent Calendar” Day 1: k-NN Regressor in Excel

    This first day of the Advent Calendar introduces the k-NN regressor, the simplest distance-based model. Using Excel, we explore how predictions rely entirely on...

    #k-NN #regression #Excel #feature scaling #distance-based models #machine learning #advent calendar #data science
  • 1 month ago · ai

    [Paper] Feature Selection Empowered BERT for Detection of Hate Speech with Vocabulary Augmentation

    Abusive speech on social media poses a persistent and evolving challenge, driven by the continuous emergence of novel slang and obfuscated terms designed to cir...

    #research #paper #ai #machine-learning #nlp
  • 1 month ago · ai

    [Paper] EfficientFlow: Efficient Equivariant Flow Policy Learning for Embodied AI

    Generative modeling has recently shown remarkable promise for visuomotor policy learning, enabling flexible and expressive control across diverse embodied AI ta...

    #research #paper #ai #machine-learning #computer-vision
  • 1 month ago · ai

    [Paper] A Diffusion Model Framework for Maximum Entropy Reinforcement Learning

    Diffusion models have achieved remarkable success in data-driven learning and in sampling from complex, unnormalized target distributions. Building on this prog...

    #research #paper #ai #machine-learning
  • 1 month ago · ai

    [Paper] Visual Sync: Multi-Camera Synchronization via Cross-View Object Motion

    Today, people can easily record memorable moments, ranging from concerts, sports events, lectures, family gatherings, and birthday parties with multiple consume...

    #research #paper #ai #machine-learning #computer-vision
  • 1 month ago · ai

    [Paper] Improved Mean Flows: On the Challenges of Fastforward Generative Models

    MeanFlow (MF) has recently been established as a framework for one-step generative modeling. However, its ``fastforward'' nature introduces key challenges in bo...

    #research #paper #ai #machine-learning #computer-vision
  • 1 month ago · ai

    [Paper] Four Over Six: More Accurate NVFP4 Quantization with Adaptive Block Scaling

    As large language models have grown larger, low-precision numerical formats such as NVFP4 have become increasingly popular due to the speed and memory benefits ...

    #research #paper #ai #machine-learning #nlp
  • 1 month ago · ai

    [Paper] AlignSAE: Concept-Aligned Sparse Autoencoders

    Large Language Models (LLMs) encode factual knowledge within hidden parametric spaces that are difficult to inspect or control. While Sparse Autoencoders (SAEs)...

    #research #paper #ai #machine-learning #nlp

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