AI could run a million microbial experiments per year

Automation uncovers combinations of amino acids that feed two bacterial species and could tell us much more about the 90% of bacteria that humans have hardly studied. An artificial intelligence system enables robots to conduct autonomous scientific experiments — as many as 10,000 per day — potentially driving a drastic leap forward in the pace …

Self-Supervised Temporal Analysis of Spatiotemporal Data

*=Equal Contributors There exists a correlation between geospatial activity temporal patterns and type of land use. A novel self-supervised approach is proposed to survey landscape based on activity time series, where time series signal is transformed to frequency domain and compressed into embeddings by a contractive autoencoder, which preserve cyclic temporal patterns observed in time …

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Migrating Critical Traffic At Scale with No Downtime — Part 1

Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam Gala, Javier Fernandez-Ivern, Anup Rokkam Pratap, Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience. Behind the scenes, a myriad of systems and services are involved in orchestrating the product experience. These backend systems are consistently being …

Supporting teachers in their STEM skilling journeys

Three of my four grandparents were teachers. Their love of learning and passion for lighting a spark in their students impressed upon me the power that teachers have to change lives and shape the future. As I’m writing this, I am in Jacksonville, Florida, just a few miles from where my grandmother, Rosalie Gordon-Mills, was …

MAMMUT

MaMMUT: A simple vision-encoder text-decoder architecture for multimodal tasks

Posted by AJ Piergiovanni and Anelia Angelova, Research Scientists, Google Research Vision-language foundational models are built on the premise of a single pre-training followed by subsequent adaptation to multiple downstream tasks. Two main and disjoint training scenarios are popular: a CLIP-style contrastive learning and next-token prediction. Contrastive learning trains the model to predict if image-text …

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Achieve high performance with lowest cost for generative AI inference using AWS Inferentia2 and AWS Trainium on Amazon SageMaker

The world of artificial intelligence (AI) and machine learning (ML) has been witnessing a paradigm shift with the rise of generative AI models that can create human-like text, images, code, and audio. Compared to classical ML models, generative AI models are significantly bigger and more complex. However, their increasing complexity also comes with high costs …

All data cloud, all the time: Recapping the Google Data Cloud & AI Summit

The Data Cloud & AI Summit is Google Cloud’s global event that showcases latest innovations and how customers are transforming their business with a unified, open and intelligent data platform. At our third annual event, we shared the latest product launches across generative AI and Data Cloud, learnings from customers and partners, and provided best …