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Why AI Needs Fresh Data with Marc Freed-Finnegan
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תוכן מסופק על ידי Eric Tarczynski. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Eric Tarczynski או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
Marc Freed-Finnegan, co-founder and CEO of Chalk, joins us to talk about why AI infrastructure needs to shift from training to inference—and how Chalk is powering sub-5ms pipelines for customers like Whatnot, MoneyLion, and Sunrun. He explains why Chalk is taking on Databricks, why fresh data is more valuable than ever, and what it means to run Python at real-time scale.
We also dive into Marc’s fintech roots, Chalk’s origins, and the company’s approach to supporting complex ML use cases across fraud detection, content moderation, and clean energy. Plus, Marc shares his take on why infrastructure—not models—is often the biggest bottleneck in getting AI into production.
Finally, we covered Amazon’s first AI licensing deal with The New York Times, Meta’s XR partnership with Anduril, Anthropic CEO Dario Amodei’s warning about AI job losses, and a $38M raise for grid tech startup Heron Power.
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