Cognitive simulation (CogSim) is an important and emerging workflow for HPC scientific exploration and scientific machine learning (SciML). This presentation will discuss recent tests with hybrid workflows that intertwine data-driven, learning models with traditional scientific simulation.  These workflows include complex physical simulation with a surrogate model “inside” the computational loop.

The major driver behind Machine Learning going mainstream is the exponential growth of chip performance through Moore’s law over the last four decades. However, when it comes to ML for the future, Moore’s law is not enough. Mere scaling through going to a lower node is not sufficient to keep pace with the ever-increasing complexity of ML workloads for both training and inference. Add energy efficiency to the mix and we need a dramatically new class of hardware – silicon optimized for specific domains.

Many companies today are focused on trying to deliver peak efficiency in machine learning (ML) inference by encouraging customers to move from less efficient traditional processors, to purpose-built accelerators for ML inference. 

While this is directionally correct, oftentimes hardware specific solutions are unable to match customers’ performance and efficiency goals. The issue, solving for ‘peak efficiency’ cannot be accomplished by simply throwing a combination of silicon and power at the problem; this is especially true at the edge.

Many companies today are focused on trying to deliver peak efficiency in machine learning (ML) inference by encouraging customers to move from less efficient traditional processors, to purpose-built accelerators for ML inference.  While this is directionally correct, oftentimes hardware specific solutions are unable to match customers’ performance and efficiency goals. The issue, solving for ‘peak efficiency’ cannot be accomplished by simply throwing a combination of silicon and power at the problem; this is especially true at the edge.

This webinar, hosted by Diversigen, will provide insights on how metatranscriptomics can provide insights into human health, disease and intervention and how to navigate the complexities around sample collection, processing, rRNA deletion and analysis.

Researchers will be able to understand how to optimize their workflows. Directors and Managers will be able to understand the tools that are available to support their R&D teams.

Innovative and creative formats are at the heart of reshaping the beauty & personal care industry. While new consumer preferences have emerged during the pandemic era, other enduring trends continue to prevail. Clariant is joined by brand & formulation experts for a stimulating dialogue on some of the most relevant factors influencing BPC consumer demand today: ingredient transparency, evolving sustainability metrics, new self-care needs, and mindful minimalism.

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Personalized Beauty Webinar - Dash Hudson