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SYSTEMS
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VMware Unified Approach Simplifies Multi-Cloud Enterprise Solutions
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Centralized AI Model Management Platform for Enterprise Scale
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Maintaining models at scale across different systems and teams is a critical bottleneck for the AI lifecycle. A centralized platform to monitor, manage, and govern all of your AI assets can significantly reduce operational overhead and improve efficiency. The DataRobot AI
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55.7 Billion IoT Devices by 2025 Edge Computing
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#IDC predicts there will be 55.7 billion connected #IoT devices by 2025. At the same time, more than half of enterprise-managed data is expected to be created and processed outside the data center or cloud. My POV: Workloads that generate large amounts of data requiring quick
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Building Systems for ML: Storage, Compilers, and IR Design
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storage systems, compilers, … all will be useful. A talk I gave at Stanford a while back has some material on this (although focuses on building systems in the context of more traditional IR systems rather than ML systems).
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Software Engineering Skills Essential for ML Systems Development
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I think there's a lot of benefit in general software engineering and computer systems skills for people doing ML engineering. ML systems are often part of a larger system, so understanding good SW engineering practices, networking, performance engineering, OSes, …
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Systems Engineering: The Most Valuable Skill Across Domains
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the most valuable skill in the world is systems engineering: the ability to debug, understand, and improve a complex system with limited/poor measurement THIS is what makes great scientists, engineers, PMs, operators, doctors & investors not truly taught in school outside STEM
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Bigtable handles 6 billion requests per second at peak
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Not that many systems handle 6B QPS. "Bigtable has been in continuous production use at Google for more than 15 years now, processing over 6 billion requests per second at peak and with over 10 exabytes of data under management. "
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Neural Operators for Multi-Scale Science and Engineering
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My talk on neural operators for science and engineering at the U.S. National Congress on Computational Mechanics. We have made exciting progress in applying neural operators to challenging multi-scale problems like weather forecasting, nuclear fusion
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Systems Thinking Framework for Decision Factor Analysis
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Use systems thinking to specify the importance value of each factor that should be considered for making a decision.
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LLMs for Industrial HVAC Control Systems and Prompt Generation
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9/ LLMs for Industrial Control – an approach to select demonstrations and generate high-performing prompts used with GPT for executing tasks such as controlling (Heating, Ventilation, and Air Conditioning) for buildings.