Building a Safer Accelerator with Model-Based Design Read how Jefferson Lab upgraded its Personnel Safety System for the Continuous Electron Beam Accelerator Facility with Simulink, achieving a major efficiency milestone https://
spr.ly/6014lyKwY
SYSTEMS
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Jefferson Lab Enhances Accelerator Safety System with Model-Based Design
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On-Premise AI Inference Deployment with Nutanix Partnership
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As 59% of organizations plan to run #AI inference workloads on-prem or in private clouds, the need for secure, compliant AI solutions is clear. Read how our partnership with @nutanix delivers cutting-edge AI directly to your on-prem environment, deployable in hours, not weeks:
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MagicDec: Speculative Decoding Enhances LLM Throughput and Latency
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7). MagicDec – shows how speculative decoding can enhance throughput, reduce latency, and maintain accuracy in long context generation scenarios; it finds that as sequence length and batch size increase, bottlenecks shift from compute-bound to memory-bound…
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Large-Scale ML Training Systems and Language Model CO2e Emissions
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I gave a talk at the MLSys conference in May this year, touching on various topics, including large-scale ML training systems, abstractions for embedding ML choices in computer systems, and CO2e emissions of language model training. https://
mlsys.org/virtual/2024/i
nvited-talk/2592
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Grok-2-mini Speed Upgrade: Inference Stack Improvements
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Grok-2-mini just got a speed upgrade. Over the past few days, we have substantially improved our inference stack. These gains come from using custom algorithms for computation and communication kernels, along with more efficient batch scheduling and quantization.
— xAI (@xai) 24 août 2024
Our inference… https://t.co/pwAG5EiMNAGrok-2-mini just got a speed upgrade. Over the past few days, we have substantially improved our inference stack. These gains come from using custom algorithms for computation and communication kernels, along with more efficient batch scheduling and quantization. Our inference
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Knowledge Bottleneck in Expert Systems: Scale Challenges
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However, knowledge is often tough to gather and maintain at scale. I built expert systems in the late 1980s and early 1990s for various applications and that was the biggest bottleneck.
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Einstein Derives OODA Loop from Fundamental Universe Equations
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Here Albert Einstein is deriving the OODA Loop from the fundamental equations that define our universe. #ooda #oodaloop
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Mind Upload to Cloud-Connected Humanoid Robots: Future Identity
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Eventually, you will probably be able to upload a good approximation of your memories & mind state to “the cloud” with the ability to download it to a humanoid robot. You obviously won’t be quite the same as you are today.
