IBM Journey to AI blog

FEBRUARY 14, 2024

When thinking of artificial intelligence (AI) use cases, the question might be asked: What won’t AI be able to do? The easy answer is mostly manual labor, although the day might come when much of what is now manual labor will be accomplished by robotic devices controlled by AI. We’re all amazed by what AI can do.

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Computer Vision Automation Robotics AI 221

IBM Journey to AI blog

FEBRUARY 6, 2024

There would be no e-commerce, remote work capabilities or the IT infrastructure framework needed to support emerging technologies like generative AI and quantum computing. Cloud computing enables organizations to use infrastructure and applications over the internet without installing and maintaining them on-premises or in-house.

DevOps 273

DevOps Automation Software Development Big Data 273

The MLOps Blog

OCTOBER 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Nice to have you here, Miki.

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Bugra Akyildiz

NOVEMBER 20, 2022

2:20 AM ∙ Nov 20, 2022 3 Likes 1 Retweet Articles Google improves upon NIMA (Neural Image Assessment) through MUSIQ , MUSIQ stands for Multi-scale Image Quality Transformer and yes, you have guessed right, the model is a variant of a Transformer model.

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Heartbeat

JULY 24, 2023

And then it is scaled and resampled to 1mm isotropic voxels. How does the team at Uber manage to keep their data organized and their team united? This Meshnet model is inspired by multi-scale context aggregation by dilated convolutions, which is a technique that expands the input layer by introducing holes in it. link] [3] F.

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Convolutional Neural Networks Neural Network Deep Learning Machine Learning 52

The MLOps Blog

AUGUST 11, 2023

There comes a time when every ML practitioner realizes that training a model in Jupyter Notebook is just one small part of the entire project. At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. What are ML pipeline architecture design patterns?

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The MLOps Blog

MAY 9, 2023

One of the most prevalent complaints we hear from ML engineers in the community is how costly and error-prone it is to manually go through the ML workflow of building and deploying models. Building end-to-end machine learning pipelines lets ML engineers build once, rerun, and reuse many times. If all goes well, of course ?

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