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• #50224 S_x96x_S addikt

  Új Válasz 2025-12-02 00:50:10 #50224

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  S_x96x_S

  addikt

  1.) "Google, Nvidia, and OpenAI"
  Monday, December 1, 2025
  https://stratechery.com/2025/google-nvidia-and-openai/

  - Google visszavág
  - Gemini 3 veri OpenAI-t
  - TPU-k veszélyeztetik Nvidiát
  - Nvidia CUDA-előnye csökken
  - OpenAI moatja: 800M felhasználó
  - OpenAI marad a nyerő

  ----

  2.) "The chip made for the AI inference era – the Google TPU"
  https://www.uncoveralpha.com/p/the-chip-made-for-the-ai-inference
  - Google TPU inference-re optimalizált
  - Szisztolikus tömb hatékonysága kiemelkedő
  - GPU-kat veri költségben
  - GCP előny a piacon

  mi a különbség :

  "The difference between a TPU and a GPU?
  To understand the difference, it helps to look at what each chip was originally built to do.
  A GPU is a “general-purpose” parallel processor,
  while a TPU is a “domain-specific” architecture.
  The GPUs were designed for graphics.
  They excel at parallel processing (doing many things at once), which is great for AI.
  However, because they are designed to handle everything from video game textures to scientific simulations, they carry “architectural baggage.”
  They spend significant energy and chip area on complex tasks like caching, branch prediction, and managing independent threads.
  A TPU, on the other hand, strips away all that baggage. It has no hardware for rasterization or texture mapping. Instead, it uses a unique architecture called a Systolic Array.
  ....
  ""

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