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SUMMARY:Silicon\, Systems\, and Supercomputers: The Past\, Present\, and Future of Compute Infrastructure
DESCRIPTION:This event will be held in person only. Free admission – registration required. (www. austinforum.org/events) \nEvery breakthrough in artificial intelligence\, climate modeling\, molecular simulation\, energy production\, pharmaceutical design\, and more is powered by massive computational infrastructure. From the micro-architectures carved into silicon chips to the sprawling supercomputers and interconnected cloud clusters that span entire data centers\, compute capacity is the foundational engine of modern scientific discovery\, engineering innovation\, and business operations. \nOn September 1\, join the Austin Forum for a fast-paced\, comprehensive exploration of the past\, present\, and possible futures of compute infrastructure. Our speakers will trace the trajectory of hardware evolution—from legacy chip paradigms to today’s exascale hyperscale clusters—and share a comprehensive overview of the current\, state of the art computing infrastructure. The presentation will conclude with thoughts on the future of computing—from architectures to new applications\, drivers\, and impacts. Spanning technology\, real-world applications\, power/energy constraints\, and global economics; this presentation will give you a complete picture of the physical systems driving our digital world. \nKey Discussion Highlights\n*The Evolution of Silicon: How Moore’s Law drove decades of microprocessor innovation\, where chip scaling stands today\, and why specialized accelerators (GPUs\, TPUs\, and domain-specific ASICs) have taken center stage.\n*Systems\, Clusters\, and Clouds: How individual chips are integrated into boards\, servers\, racks\, and massive clusters that power modern high-performance computing (HPC) supercomputers and public cloud platforms.\n*Future Architectures on the Horizon: What comes next when traditional silicon hits physical limits? An exploration of alternative paradigms\, including 3D stacked chiplets\, optical/photonic computing\, neuromorphic processing\, and quantum integration.\n*Workloads Shaping the Hardware: How applications—from frontier AI training and drug discovery to real-time defense and financial modeling—are dictating future hardware design requirements.\n*Power\, Cooling\, and Economics: Confronting the physical reality of building gigawatt-scale infrastructure—including thermal management\, energy grid demands\, capital expenditure dynamics\, and global supply chain considerations. \nEvent Agenda & Post-Event Networking\n*Presentation: A high-octane\, multi-perspective overview of silicon\, systems\, and supercomputer architectures.\n*Audience Q&A: Bring your technical and economic questions for an interactive session with our expert presenters.\n*Continued Conversation at Remedy: When the Q&A wraps\, the evening is far from over! Head down the street with us to Remedy\, located at 3rd & Nueces\, for post-event networking. \nConnect with fellow attendees\, swap insights on the future of compute\, and enjoy a complimentary drink courtesy of our generous Austin Forum Annual Partners\, Champions\, and Friends.
URL:https://austin-ai.org/event/silicon-systems-and-supercomputers-the-past-present-and-future-of-compute-infrastructure/
LOCATION:The Center for Government and Civic Service\, ACC Rio Grande: Building 3000\, 1218 West Avenue\, Austin\, TX\, 78701\, United States
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SUMMARY:Human Orchestration of Tools and Agents - Beyond the Prototype II — Self-Recursive Agents
DESCRIPTION:Many organizations are stuck in “AI purgatory”; building impressive prototypes that fail to scale\, break quietly in production\, or degrade in quality over time. To achieve true ROI\, AI systems must move beyond simple task execution and become self-aware\, self-healing\, and self-improving. \nEveryone has a demo. AI demos work\, but production breaks. The gap between “works in a demo” and “runs reliably at scale” is where organizations get stuck. This session teaches you a framework for closing this gap.  \nThis session is for builders who have hit the wall with prototype agents that degrade or stagnate. We are going beyond the prototype to tear down a self-evolving agent architecture. Mario will show you the four capabilities every production AI systems needs. \nWhat You’ll Be Able to Learn\n\nShared Memory – How agents learn from each other\nTrust Scoring – How to know which outputs to trust\nPrompt Evolution – How systems improve themselves weekly\nSafe Governance – How to deploy changes without breaking production\n\n What Makes This Session Different\n\nVery few have a system that improves itself in production\nBased on real architecture\, real data\, and real lessons\nWe are addressing the hard gaps: FadeMem decay\, pruning governance\, and the MinionS protocol (achieving 97.9% performance at 18% cost).\nThis is a live\, production-grade system teardown. Mario will show you the exact infrastructure (n8n\, Supabase\, Qdrant\, OpenRouter) that runs MEF Solutions.\n\nWho Is It For\n\nAI engineers and builders who are tired of brittle prototypes and want to deploy resilient\, self-improving systems.\nTechnical founders trying to bridge the gap between AI experimentation and AI operations.\nRevOps and GTM leaders who need autonomous architectures to drive actual revenue\, not just engagement.\nAnyone who is done watching demos that don’t survive contact with real users\, and wants their AI still working next quarter\, not just this one.\nBefore You Arrive \n\nReview your current agent architecture and identify where the feedback loops are broken.\nCalculate the token cost and failure rate of your most complex autonomous workflow.\nBring your skepticism. We’re going to look at what actually works in 2026.\nInstructor Bio\nMario Facussé is the Managing Director of MEF Solutions\, where he builds AI-powered revenue systems for growth-stage companies. He designs and operates autonomous agent architectures that self-improve in production; not prototypes\, not demos\, but systems that run his own company. His work draws from peer-reviewed research in self-evolving agents\, collaborative reinforcement learning\, and autonomous optimization\, implemented on practical infrastructure. He’s spoken at leading AI conferences and events and advises companies on strategy\, GTM\, operations\, revenue\, and bridging the gap between AI experimentation and AIoperations. \n 
URL:https://austin-ai.org/event/hota-beyond-the-prototype-2/
LOCATION:The Center for Government and Civic Service\, ACC Rio Grande: Building 3000\, 1218 West Avenue\, Austin\, TX\, 78701\, United States
CATEGORIES:AAIA,HOTA
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ORGANIZER;CN="Austin AI Alliance":MAILTO:info@austin-ai.org
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