Aug 14, 2026

IBM’s cloud collab, Meta’s Muse Glimmer & OpenAI’s upcoming Astra model

This episode explores IBM's massive AI infrastructure partnership with Together AI and NVIDIA, Meta's open-source Muse Glimmer model enabling powerful on-device AI, and OpenAI's delayed Astra model due to critical cybersecurity capabilities. Discussions cover the economics of industrial-scale AI, the implications of local vs. cloud AI, and the profound security challenges and opportunities presented by both open and closed frontier models.

Jul 12, 2026

Semantic Blindness: 500,000 Sensors Confused an LLM - Raahul Singh & Vanč Levstik, Phaidra

Modern LLMs struggle with combinatorial engineering problems in industrial settings due to "Semantic Blindness" – an inability to understand physical system topology, scale efficiently, or handle repetitive naming conventions. This talk introduces a hybrid AI architecture that combines LLMs for high-level planning with deterministic systems for execution, leveraging hierarchical structures and pattern-based search. This approach achieves 100% accuracy and flat operational costs at massive scales, demonstrating an "inversion" of the Software 1.0/3.0 paradigm where AI-native systems mature by integrating deterministic code for reliable, structured tasks.

Oct 30, 2025

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.