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Google AI: Release Notes

Google AI: Release Notes

著者: Google AI
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Ever wondered what it's really like to build the future of AI? Join host Logan Kilpatrick for a deep dive into the world of Google AI, straight from the minds of the builders. We're pulling back the curtain on the latest breakthroughs, sharing the unfiltered stories behind the tech, and answering the questions you've been dying to ask. Whether you're a seasoned developer or an AI enthusiast, this podcast is your backstage pass to the cutting-edge of AI technology. Tune in for: - Exclusive interviews with AI pioneers and industry leaders. - In-depth discussions on the latest AI trends and developments. - Behind-the-scenes stories and anecdotes from the world of AI. - Unfiltered insights and opinions from the people shaping the future. So, if you're ready to go beyond the headlines and get the real scoop on AI, join Logan Kilpatrick on Google AI: Release Notes.2024 Google 科学
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  • Deep Dive into Long Context
    2025/05/02

    Explore the synergy between long context models and Retrieval Augmented Generation (RAG) in this episode of Release Notes. Join Google DeepMind's Nikolay Savinov as he discusses the importance of large context windows, how they enable Al agents, and what's next in the field.

    Chapters:
    0:52 Introduction & defining tokens
    5:27 Context window importance
    9:53 RAG vs. Long Context
    14:19 Scaling beyond 2 million tokens
    18:41 Long context improvements since 1.5 Pro release
    23:26 Difficulty of attending to the whole context
    28:37 Evaluating long context: beyond needle-in-a-haystack
    33:41 Integrating long context research
    34:57 Reasoning and long outputs
    40:54 Tips for using long context
    48:51 The future of long context: near-perfect recall and cost reduction
    54:42 The role of infrastructure
    56:15 Long-context and agents

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    1 時間
  • Launching Gemini 2.5
    2025/03/28

    Tulsee Doshi, Head of Product for Gemini Models joins host Logan Kilpatrick for an in-depth discussion on the latest Gemini 2.5 Pro experimental launch. Gemini 2.5 is a well-rounded, multimodal thinking model, designed to tackle increasingly complex problems. From enhanced reasoning to advanced coding, Gemini 2.5 can create impressive web applications and agentic code applications. Learn about the process of building Gemini 2.5 Pro experimental, the improvements made across the stack, and what’s next for Gemini 2.5.

    Chapters:

    0:00 - Introduction
    1:05 - Gemini 2.5 launch overview
    3:19 - Academic evals vs. vibe checks
    6:19 - The jump to 2.5
    7:51 - Coordinating cross-stack improvements
    11:48 - Role of pre/post-training vs. test-time compute
    13:21 - Shipping Gemini 2.5
    15:29 - Embedded safety process
    17:28 - Multimodal reasoning with Gemini 2.5
    18:55 - Benchmark deep dive
    22:07 - What’s next for Gemini
    24:49 - Dynamic thinking in Gemini 2.5
    25:37 - The team effort behind the launch

    Resources:

    • Gemini → https://goo.gle/41Yf72b
    • Gemini 2.5 blog post → https://goo.gle/441SHiV
    • Example of Gemini’s 2.5 Pro’s game design skills → https://goo.gle/43vxkq1
    • Demo: Gemini 2.5 Pro Experimental in Google AI Studio → https://goo.gle/4c5RbhE
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    28 分
  • Gemini app: Canvas, Deep Research and Personalization
    2025/03/20

    Dave Citron, Senior Director Product Management, joins host Logan Kilpatrick for an in-depth discussion on the latest Gemini updates and demos. Learn more about Canvas for collaborative content creation, enhanced Deep Research with Thinking Models and Audio Overview and a new personalization feature.

    0:00 - Introduction
    0:59 - Recent Gemini app launches
    2:00 - Introducing Canvas
    5:12 - Canvas in action
    8:46 - More Canvas examples
    12:02 - Enhanced capabilities with Thinking Models
    15:12 - Deep Research in action
    20:27 - The future of agentic experiences
    22:12 Deep Research and Audio Overviews
    24:11 - Personalization in Gemini app
    27:50 - Personalization in action
    29:58 - How personalization works: user data and privacy
    32:30 -The future of personalization

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    37 分

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