Deep learning (DL) is a fast-evolving field, and practitioners are constantly innovating DL models and inventing ways to speed them up. Custom operators are one of the mechanisms developers use to push the boundaries of DL innovation by …
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In this blog post, we catch a glimpse into drug discovery to see how Evolvere Biosciences has deployed a customized architecture w/ AWS Batch and Nextflow to quickly and easily run its macromolecule design pipeline. Read the Post on the AWS …
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Batch inference is a common pattern where prediction requests are batched together on input, a job runs to process those requests against a trained model, and the output includes batch prediction responses that can then be consumed by other …
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Running Jupyter notebooks as Hybrid Jobs on Amazon Braket, you get performance and convenience of jobs, without modifying code. In this post, we show how you can scale up from exploratory notebook to repeatable and reliable experiments on …
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In this post, we discuss the “tipping point” problem, using HPC at a large scale to simulate the impact of deforestation to the risk of accelerating damage to the Amazon rainforest. Read the Post on the AWS Blog Channel
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Innovations in deep learning (DL), especially the rapid growth of large language models (LLMs), have taken the industry by storm. DL models have grown from millions to billions of parameters and are demonstrating exciting new capabilities. …
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This is a guest post by Carter Huffman, CTO and Co-founder at Modulate. Modulate is a Boston-based startup on a mission to build richer, safer, more inclusive online gaming experiences for everyone. We’re a team of world-class audio …
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In this blog post, we’ll explore the benefits of computational chemistry for the circular economy, how it can help reduce waste, and describe the potential for new innovative materials. Read the Post on the AWS Blog Channel
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