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Join Ian Buck, VP of HPC and Hyperscale at NVIDIA to hear about the latest innovations in AI infrastructure. AI is being adopted by every industry and new state-of-the-art techniques are accelerating …
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AI is only as good as the foundation upon which it is built. Unstable infrastructure can turn even the most brilliant algorithms into expensive experiments that fail when you need them most. With prov …
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The semiconductor industry is experiencing unprecedented growth, and this growth comes with significant challenges—more design starts, rising design complexities, shorter time-to-market, and a shrinki …
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Unlock massive AI workloads with Google's TPU innovations. We’ll discuss how TPUs enable efficient large-scale training and optimal inference workloads including exclusive details of the latest gen TP …
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As AI workloads continue to grow in complexity and scale, improving energy efficiency has become acritical design objective from Silicon to Systems. This tutorial explores a holistic approach to optim …
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Discover how to overcome barriers at the edge, enabling the deployment of advanced AI models with lower costs and reduced power consumption across a range of devices and professional use cases.
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The generative AI revolution presents a dilemma: the best models are in the cloud, but your data is on-prem due to sovereignty, security, or latency needs. This makes on-prem AI complex and costly. Th …
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Building AI solutions involves critical strategic choices impacting cost, performance, and time-to-market. GenAI use cases and associated compute need has grown exponentially in the last 2-3 years. AI …
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The hypergrowth of the AI market has brought innovation and acceleration to the entire IT technology stack in just a few years time. Advancements in the network fabric, protocols, optics, and operatio …
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The future of AI demands a revolution in infrastructure. As frontier AI models strain the limits of traditional silicon scaling and copper connectivity, a fundamental shift is needed. AI data centers …
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Data Privacy & Governance: Infrastructure That Governs: Building Responsible AI from the Platform UpResponsible AI is often framed in terms of ethical models and fair data—but the foundation for responsibility lies in infrastructure. In this talk, we’ll explore how platform-level capabilities like e …
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The combination of extreme-density, co-packaged interconnects and next-gen AI accelerators form the backbone of bleeding-edge AI hardware system topologies. Co-Packaged Copper (CPC) optimizes 224 Gbps …
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Many AI agent projects stall after promising pilots because they can’t deliver the accuracy businesses need to trust them. A key reason is that enterprise data isn’t just numbers and tables- it comes …
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Running workloads on the edge means operating with a finite amount of compute resources, which means that running workloads as lightweight as possible is generally preferable. In contrast, securely op …
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As AI adoption accelerates, securing sensitive data during inference has become a critical challenge, particularly in regulated and privacy-sensitive environments. Fully Homomorphic Encryption (FHE) e …
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When it comes to AI, inference is how today’s gen AI models can solve real-world business problems. Google Kubernetes Engine (GKE) is seeing an increasing adoption of gen AI inference. In this session …
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As frontier LLMs grow ever larger, the challenge is no longer just raw compute—it’s deploying them efficiently, reliably, and at scale. In this session, Rebellions presents its full-stack approach to …
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As AI evolves into agentic systems where dozens to hundreds of LLMs and specialized models work in concert, running them efficiently in data centers poses immense software challenges. From disaggregat …
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Behind every AI product at WBD lies a shared foundation — a unified AI/ML architecture designed to handle everything from data ingestion to large-scale model deployment. In this session, we’ll take yo …
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As the adoption of generative and agentic AI accelerates, the challenges for memory as a key enabler of AI/ML processing architectures continue to grow. Balancing the demands for ever greater bandwidt …
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California faces over 7,000 wildfires each year, with enormous costs to lives, communities, and ecosystems. Responding faster requires distributed sensing and intelligence that can act in the field wh …
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What does it take to run one of the world's largest AI supercomputers? As artificial intelligence workloads grow exponentially, operating a hyperscale AI cloud fleet demands new strategies for resilie …
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As AI-native cloud platforms scale to meet global demand, the data center IT infrastructure powering generative AI has become a prime target for attackers. In this session, Dr. Yuriy Bulygin—CEO of Ec …
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Cerebras Systems is redefining the future of AI with the world’s fastest inference engine—enabling breakthroughs in agentic intelligence, real-time reasoning, and AI coding assistants. Andrew Feldman, …
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In this session, learn how Amazon SageMaker HyperPod delivers a highly resilient and performant infrastructure purpose-built for training foundation models at scale. We will explore the latest HyperPo …
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The AI landscape is undergoing a monumental shift. After a decade where AI flourished in the cloud, scaled by hyperscalers, we are now entering the era of Physical AI. Physical AI is poised to touch e …
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As AI infrastructure outgrows tightly coupled systems, we’re witnessing a shift toward openness and modularity in designing full-stack solutions for AI. In this session, we’ll examine the rise of Soft …
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