AIAW Podcast

Season 12 of the AIAW Podcast kicks off with a high-stakes question: Can we reach Artificial General Intelligence (AGI) by 2026? In Episode 174, we’re joined by Karim Nouira, founder of sics.ai (Superintelligence Computing Systems), for a deep and provocative conversation on the technical frontiers of AGI. From LLM limitations and JEPA’s alternative path to robotics brains and latent space reasoning, we unpack what it would take to build truly autonomous systems. We also explore Sweden’s role in the global AGI race, the future of labor in an agentic world, and the societal implications of superintelligent machines. A powerful start to a season focused on what’s next in AI. Tune in. 
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In Episode 173 of the AIAW Podcast, we close out Season 11 with a festive and future-focused Christmas & Year-End Special—and you're invited. Together with surprise guests Patrick Couch, Jesper Fredriksson, and Fredrik Olsson, we look back at the AI rollercoaster that was 2025: from breakthroughs in model development and enterprise AI maturity to the biggest twists in tech and regulation. We also look ahead to 2026, sharing bold predictions, strategic challenges, and the trends that could define the next wave of AI transformation. Equal parts serious and celebratory, this episode is the perfect way to reflect, recharge, and reset for what’s next. Grab something festive and tune in to the grand finale of Season 11. 
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We explore how to scale in the age of AI without drowning in complexity, moving from one-off pilots to reusable platforms, and from efficiency-only thinking to adaptability, trust, and aligned autonomy. Helena Hörnerbrandt shares enterprise-tested principles that travel across 65+ markets, plus a real ABS rollout that shows product over project in action.

• deepfake demo as a visceral risk signal
• value-led scaling and decoupling growth from OPEX
• escaping point-solution spaghetti with use case families
• bimodal model for value creation and capitalization
• governance that speeds decisions, not stalls them
• continuous design over static process change
• trust, discipline, aligned autonomy, and mastery
• product vs project and market enablement roles
• ERP standardization vs data pattern standardization
• the intelligence plane and shared, synthetic, real-time data
• buy to build, ecosystem scaling, and partnerships
• Europe’s need for sandboxes and co-created guidance
• AGI outlook across both risk and opportunity

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Follow us on youtube: https://www.youtube.com/@aiawpodcast

In Episode 170 of the AIAW Podcast, we’re joined by Jim Dowling, CEO of Hopsworks, co-creator of featurestore.org, and author of the upcoming O’Reilly book Building Machine Learning Systems with a Feature Store. Known as "Mr. Feature Store," Jim walks us through the evolution of AI infrastructure. From traditional batch learning to real-time, agentic workflows powered by vector databases, RAG, and LLMs. We discuss how feature stores serve as the memory layer of AI agents, enabling contextual awareness and low-latency decision-making, and why they’re central to the future of scalable, ethical, and sovereign AI systems. Tune in for a deep dive into the systems powering tomorrow’s most advanced AI applications. 
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