Stability AI releases its Image Upscaling API

Today Stability AI announces the release of its Image Upscaling API, an AI-powered tool that increases the size of any image without compromising its sharpness.  The Image Upscaling API is the latest addition to Stability AI’s existing set of image generation and editing APIs, like the popular text-to-image, image-to-image and inpainting APIs. Upscaling adds to …

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Exclusive Insights into Consumer Behavior Towards Financial Services

The economy constantly reshapes consumer behavior towards financial services and consumer sentiments around spending. Economic factors have a huge impact on how consumers approach their own finances and think about financial products. While it’s no secret that consumer behaviors are always changing, just how much and how fast they are changing might surprise even the …

f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation

Diffusion models (DMs) have recently emerged as SoTA tools for generative modeling in various domains. Standard DMs can be viewed as an instantiation of hierarchical variational autoencoders (VAEs) where the latent variables are inferred from input-centered Gaussian distributions with fixed scales and variances. Unlike VAEs, this formulation constrains DMs from changing the latent spaces and …

Cloud scalability: Scale-up vs. scale-out

IT Managers run into scalability challenges on a regular basis. It is difficult to predict growth rates of applications, storage capacity usage and bandwidth. When a workload reaches capacity limits, how is performance maintained while preserving efficiency to scale? The ability to use the cloud to scale quickly and handle unexpected rapid growth or seasonal shifts …

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Robust and efficient medical imaging with self-supervision

Posted by Shekoofeh Azizi, Senior Research Scientist, and Laura Culp, Senior Research Engineer, Google Research Despite recent progress in the field of medical artificial intelligence (AI), most existing models are narrow, single-task systems that require large quantities of labeled data to train. Moreover, these models cannot be easily reused in new clinical contexts as they …

ML Lifecycle

Deliver your first ML use case in 8–12 weeks

Do you need help to move your organization’s Machine Learning (ML) journey from pilot to production? You’re not alone. Most executives think ML can apply to any business decision, but on average only half of the ML projects make it to production. This post describes how to implement your first ML use case using Amazon …