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GenAI Learner

GenAI Learner

By: hogarthian.art
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Dive deep into the exciting realm of Generative AI without the jargon! 🚀 Here, we transform the latest GenAI technologies – sourced from pioneering research papers and top blogs – into easy-to-follow podcast discussions. Join our community of AI enthusiasts, learn something new every week, and become a GenAI expert with us!

Copyright 2025 All rights reserved.
Episodes
  • Scaling AI: Think Operators, Not Models
    Nov 15 2025

    Scaling large AI models to meet dynamic traffic is slow and leads to significant resource waste. Researchers at Microsoft Azure Research and Rice University are rethinking this process, finding that scaling the entire model as a monolith is inefficient. Their breakthrough, "operator-level autoscaling," scales just the specific bottleneck parts (operators) of the model instead of the whole thing. This new approach is far more efficient, preserving performance while using up to 40% fewer GPUs and 35% less energy.

    Arxiv: https://arxiv.org/abs/2511.02248

    The GenAI Learner podcast explains this new, efficient approach in simple terms.

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    12 mins
  • Can AI Learn Like Humans? The Novel Games Benchmark
    Nov 13 2025

    Researchers at MIT and Harvard argue that true intelligence requires constructing internal world models, proposing a generative game benchmark to prove if AI can adapt to unseen environments without millions of training steps—tune into GenAI Learner for the details. https://arxiv.org/pdf/2507.12821

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    12 mins
  • The Surprising Limits of RL in LLMs: Why Optimization Kills Deep Reasoning Capacity
    Nov 12 2025

    The Surprising Limits of RL in LLM Reasoning

    Arxiv: https://arxiv.org/pdf/2504.13837The promise of RL for LLM growth hits a wall: Tsinghua University's study shows RLVR only improves efficiency but is bounded by and does not elicit novel reasoning in base models—get the non-technical scoop on the "GenAI learner" podcast.

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    14 mins
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