Latest Interviews
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How Open Source Became AI's Backbone | Inferact with a16z
Elena Burger, Matt Bornstein, Simon Mo
VLLM serves as a critical inference engine for over half a million GPUs, bridging the gap between research and production by collaborating with hardware vendors and model labs to ensure day-zero compatibility for over 1,000 architectures. The platform addresses the industry's shift toward open-weight models by providing granular control over performance tiers, data retention, and guardrails that proprietary APIs often restrict. Looking forward, VLLM advocates for an ecosystem where open and frontier models become indistinguishable in capability, with infrastructure innovation focusing on optimization speed and algorithmic efficiency rather than mere data sourcing.
- a16z47 min
Why AI Characters & Virtual Influencers Are the Next Frontier in Video ft Hedra’s Michael Lingelbach
Michael Lingelbach, Justine Moore, Matt Bornstein
Hedra distinguishes itself in the AI video sector by prioritizing character-centric primitives over generic frames, enabling enterprises and creators to productionize viral signals into autonomous, bi-directional workflows. Founder Michael leads the company's rapid growth in automated newscasting and educational tutoring by leveraging a modular architecture that integrates best-in-class partners for granular control over performance and timing. This approach facilitates medium-scale personalization and interactive storytelling while navigating the industry's shift from text-to-video prompting toward true co-creation with programmable digital personas.
- a16z46 min
Building AI Systems You Can Trust
Following a fifteen-year career optimizing traditional machine learning and leading AI divisions at Intel, the speaker identified that enterprise adoption of generative AI is hindered by a critical trust gap rather than a lack of raw performance. This insight drove the founding of Distributional, a platform that replaces marginal optimization with distributional testing and holistic monitoring to detect behavioral shifts in non-deterministic, agentic systems. By shifting focus from atomic metrics to continuous validation of complex workflows, the company enables organizations to centralize operations, mitigate operational risks like hallucination, and scale reliable AI applications.