AI Without Illusions

csbaby
  • 5,0 (1)
  • Технологии

Are you a software engineer transitioning into the AI world? AI Without Illusions is an AI-native channel that breaks down the foundational papers and architectures of modern ML. Tailored for seasoned engineers, we bypass the heavy math to deliver clear, intuitive explanations on how AI truly works.

Выпуски

  1. 11 июн.

    Episode 2: Why Size Matters & When It Doesn't

    The hosts will dive straight into the macro-economics of deep learning, covering empirical Scaling Laws, the Chinchilla correction, the "mirage" of emergent abilities, and how to optimally allocate a compute budget. Per your handoff note, they will keep it intriguing, fun, and conversational, using relatable budgeting and infrastructure analogies while completely skipping the basics of Transformers and Attention.

    20 мин.

  2. 11 июн.

    EP3: Making Training Fit on GPUs

    The podcast will dive straight into the hardcore systems engineering of "Making Training Fit on GPUs," breaking down Data Parallelism, Tensor Parallelism, Pipeline Parallelism, and ZeRO/FSDP Sharding. As requested in your handoff note, it will skip all the basic Transformer and Attention explanations, focusing entirely on practical scenarios and using fun, relatable factory assembly line analogies to keep things engaging.

    51 мин.

  3. 11 июн.

    EP2:

    In this episode, we tackle the hardcore systems engineering challenge of physically fitting massive Large Language Models onto GPU clusters. Stepping away from heavy math and using relatable analogies—like a factory assembly line—we break down the four key dimensions of distributed training: data parallelism, tensor parallelism, pipeline parallelism, and ZeRO/FSDP sharding. We explain exactly what each method shards across your hardware and the practical scenarios for when to reach for them, providing a clear, systems-level framing for engineers looking to train at scale.

    21 мин.

  4. 3 июн.

    EP1: Transformer & The Power of Scale

    A breakdown of modern LLM architecture tailored for software engineers. We explore how the Transformer revolutionized AI by processing text in parallel to replace older, sequential RNNs. We also demystify the "self-attention" mechanism, explaining how it uses Queries, Keys, and Values much like an information retrieval system to build deep contextual understanding. Finally, we dive into empirical Scaling Laws, revealing how the massive scale of models like the 175-billion parameter GPT-3 unlocked "in-context learning"—the emergent ability to perform completely new tasks on the fly just by reading a prompt, without requiring any underlying parameter updates or fine-tuning

    20 мин.
  • Выпусков: 4

Об этом подкасте

Are you a software engineer transitioning into the AI world? AI Without Illusions is an AI-native channel that breaks down the foundational papers and architectures of modern ML. Tailored for seasoned engineers, we bypass the heavy math to deliver clear, intuitive explanations on how AI truly works.

Информация

  • Автор
    csbaby
  • Годы выхода
    2 тыс.
  • Выпуски
    4
  • Ограничения
    Без ненормативной лексики
  • Авторские права
    © csbaby
  • Сайт подкаста
    AI Without Illusions