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Granite 4.0: Small AI Models, Big Efficiency

Granite 4.0: Small AI Models, Big Efficiency

IBM's Granite 4.0 models introduce a groundbreaking hybrid architecture combining Mamba-2 and Transformer blocks with a Mixture of Experts (MoE) design. This approach enables smaller models to achieve superior performance, speed, and memory efficiency, even outperforming much larger models on key enterprise tasks while running on consumer-grade hardware.

Build Hour: AgentKit

Build Hour: AgentKit

A deep dive into OpenAI's AgentKit, demonstrating how to visually build, deploy, and optimize multi-step, tool-calling agents using Agent Builder, ChatKit, and the integrated Evals platform.

Sam, Jakub, and Wojciech on the future of OpenAI with audience Q&A

Sam, Jakub, and Wojciech on the future of OpenAI with audience Q&A

Sam Altman and Yakob present OpenAI's updated strategy, detailing a concrete research roadmap towards an automated AI researcher by 2028, a vision for an open AI platform, and massive infrastructure plans totaling $1.4 trillion. They also introduce a new corporate structure with a non-profit foundation focused on using AI to cure diseases and build AI resilience.

Commure: The AI Operating System for Healthcare

Commure: The AI Operating System for Healthcare

Tanay Tandon, co-founder and CEO of Commure, discusses his journey from building a medical device in college to creating an AI operating system for healthcare. He covers the pivot from hardware to software, the power of LLMs in automating revenue cycle and clinical documentation, and his vision for a future where AI liberates physicians from administrative burdens and fundamentally reshapes patient care.

Building the Real-World Infrastructure for AI, with Google, Cisco & a16z

Building the Real-World Infrastructure for AI, with Google, Cisco & a16z

AI is driving an unprecedented buildout of physical infrastructure. Experts from Google and Cisco discuss the "AI industrial revolution," where power, compute, and networking are the new scarce resources, demanding a complete reinvention of the technology stack from silicon to software.

Build and monitor multi-agent contact centers using Weights & Biases

Build and monitor multi-agent contact centers using Weights & Biases

This post explores the shift from costly legacy contact center software to multi-agent AI systems. It demonstrates how to build, monitor, and evaluate these complex agentic systems using the Weights & Biases AI Developer Platform, with a focus on tracing, quality assessment, and ensuring consistent customer support.