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What comes after large language models?
In this episode of The Deep View Conversations, we talked with Zuzanna Stamirowska, CEO of Pathway, to explore why her team believes today’s dominant AI architecture has fundamental limits, and what it could take to move beyond them.
Pathway is developing Dragon Hatchling, a new architecture designed to gi...
What happens when powerful AI no longer has to live in the cloud?
In this episode of The Deep View Conversations, we talked with Mark Papermaster, CTO of AMD, about why the next major shift in AI could happen on the device sitting on your desk.
Papermaster explains how computers could soon run sophisticated models and teams of private AI agents ...
AI systems almost always have an answer, even when they should say, “I don’t know.”
In this episode of The Deep View Conversations, senior reporter Sabrina Ortiz speaks with Ruchir Puri, chief scientist at IBM Research, about why uncertainty modeling may be AI’s most urgent technical challenge.
Puri explains why today’s models struggle to...
Is it possible for enterprises to build AI agents they can actually trust?
In this episode of The Deep View Conversations, Senior Reporter Sabrina Ortiz sat down with Priya Srinivasan of IBM to discuss Sovereign Core, IBM’s software designed to enable enterprises to deploy AI in a secure, compliant, and sovereign way.
As AI moves from cha...
In this episode of The Deep View Conversations, we sat down with Caroline Ingeborn, COO of Luma, an AI lab dedicated to omnimodal intelligence, to discuss where generalized physical AI could take us.
Rather than focusing only on video models, Luma takes an omnimodal, or multimodal, approach, creating models that understand text, video, images and audio. Th...