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Will Grannis

Founder and leader of Google Cloud’s CTO Office, a team of senior engineers fostering collaborative innovation between Google and its largest customers. He has a background as an entrepreneur, enterprise technology executive, and investor, building and scaling technical platforms.

Top 3 podcasts with Will Grannis

Ranked by the Snipd community
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32 snips
Apr 9, 2025 • 58min

#246 Will Granis: How Google Cloud is Powering the Future of Agentic AI

Will Grannis, CTO of Google Cloud, shares insights on the revolutionary landscape of agentic AI. He discusses how multi-agent systems can streamline tasks like expense automation and enhance operational workflows. Grannis highlights the importance of trust in AI, emphasizing secure agent management and the potential for scientific discovery. He also explains how large organizations can leverage their data for agility, comparing their pace to startups. This conversation redefines our understanding of AI's future, focusing on autonomy and innovation in technology.
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9 snips
May 1, 2025 • 38min

Google Cloud CTO on LLM Demand Surge, Use Cases

Will Grannis, Chief Technology Officer of Google Cloud, shares insights on the explosive demand for large language models like Gemini, boasting a 40x growth in usage. He highlights Google's Ironwood TPU, designed to enhance efficiency and performance significantly. The conversation dives into versatile use cases for AI across industries, emphasizing seamless integration and customer customization. Grannis also touches on the importance of authoritative data in AI applications and tackles future trends and market metrics in the ever-evolving tech landscape.
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Mar 30, 2021 • 31min

Games, Teams, and Moonshots: Google Cloud’s Will Grannis

Will Grannis, founder of Google Cloud’s CTO Office, shares how his early love for gaming shaped his tech career. He discusses the importance of defining problems for success in AI projects, emphasizing a user-first mindset and collaboration across diverse perspectives. Grannis highlights the intricate balance between human teamwork and machine integration, particularly in customer support contexts. He also underlines that focusing on business impact rather than just technology is crucial for effective machine learning solutions, drawing valuable parallels from gaming.

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