Next generation material that adapts to its history

Inspired by living systems, researchers have developed a new material that changes its electrical behavior based on previous experience, effectively giving it a basic form of adaptive memory. Such adaptive materials could play a vital role in the next generation of medical and environmental sensors, as well as in soft robots or active surfaces.

Solving brain dynamics gives rise to flexible machine-learning models

Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job and can adapt to changing conditions, for real-world safety-critical tasks, like driving and flying. The flexibility of these “liquid” neural nets meant boosting …

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Interoperability: The ins and outs of sharing data (Palantir RFx Blog Series, #4)

As data ecosystems evolve over time, organizations must establish strong interoperability expectations for their software to ensure utility and impact into the uncertain future. Editor’s note: This is the fourth post in the Palantir RFx Blog Series, which explores how organizations can better craft RFIs and RFPs to evaluate digital transformation software. Each post focuses …

Bridge the data literacy skills gap with data storytelling

Being a data-driven organization goes well beyond building a modern data architecture. With vast amounts of data flowing through the enterprise, the challenge lies in making sense of all of that complex information so that everyone, not just the data scientists or machine learning engineers, can interpret it for better decision-making. For CDOs and other …

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Refit trained parameters on large datasets using Amazon SageMaker Data Wrangler

Amazon SageMaker Data Wrangler helps you understand, aggregate, transform, and prepare data for machine learning (ML) from a single visual interface. It contains over 300 built-in data transformations so you can quickly normalize, transform, and combine features without having to write any code. Data science practitioners generate, observe, and process data to solve business problems …

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Run machine learning inference workloads on AWS Graviton-based instances with Amazon SageMaker

Today, we are launching Amazon SageMaker inference on AWS Graviton to enable you to take advantage of the price, performance, and efficiency benefits that come from Graviton chips. Graviton-based instances are available for model inference in SageMaker. This post helps you migrate and deploy a machine learning (ML) inference workload from x86 to Graviton-based instances …