Software development is one arena where we are already seeing significant impacts from generative AI tools. The benefits are many, and significant productivity gains are currently available to enterprises that embrace these tools. A McKinsey study claims that software developers can complete coding tasks up to twice as fast with generative AI. The consulting firm’s …
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Posted by Omar Benjelloun, Software Engineer, Google Research, and Peter Mattson, Software Engineer, Google Core ML and President, MLCommons Association Machine learning (ML) practitioners looking to reuse existing datasets to train an ML model often spend a lot of time understanding the data, making sense of its organization, or figuring out what subset to use …
Read more “Croissant: a metadata format for ML-ready datasets”
In this post, we demonstrate how to efficiently fine-tune a state-of-the-art protein language model (pLM) to predict protein subcellular localization using Amazon SageMaker. Proteins are the molecular machines of the body, responsible for everything from moving your muscles to responding to infections. Despite this variety, all proteins are made of repeating chains of molecules called …
Read more “Efficiently fine-tune the ESM-2 protein language model with Amazon SageMaker”
Kubernetes is a popular way to run AI workloads like training, and large language model (LLM) serving, including our new open model Gemma. Google Kubernetes Engine (GKE) in Autopilot mode provides a fully managed Kubernetes platform that offers the power and flexibility of Kubernetes but without the need to worry about compute nodes, so you …
On Tuesday the country’s techiest city backed a ballot proposition that tapped into concerns about crime, giving the police more freedom to use drones and other surveillance technology.
A Microsoft engineer is sounding alarms about offensive and harmful imagery he says is too easily made by the company’s artificial intelligence image-generator tool, sending letters on Wednesday to U.S. regulators and the tech giant’s board of directors urging them to take action.
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Paper abstract: Large-scale web-crawled datasets are fundamental for the success of pre-training vision-language models, such as CLIP. However, the inherent noise and potential irrelevance of web-crawled AltTexts pose challenges in achieving precise image-text alignment. Existing methods utilizing large language models (LLMs) for caption rewriting have shown promise on small, curated datasets like CC3M and CC12M. …
Read more “VeCLIP: Improving CLIP Training via Visual-enriched Captions”
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