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MaRDIFlow: Automating Metadata Abstraction for Enhanced Reproducibility in Computational Workflows

Marktechpost

Emerging tools like Jupyter notebooks and Code Ocean facilitate documentation and integration, while automated workflows aim to merge computer-based and laboratory computations. FMI’s container-based approach aids in replicating simulations but requires metadata for broader reproducibility and adaptation.

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OpenAI takes steps to boost AI-generated content transparency

AI News

OpenAI is joining the Coalition for Content Provenance and Authenticity (C2PA) steering committee and will integrate the open standard’s metadata into its generative AI models to increase transparency around generated content. of non-AI images incorrectly flagged.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Journey to AI blog

Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. ” Are foundation models trustworthy?

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ChatGPT Can Now Automate Operational Tasks: The DAM Example

Towards AI

Last Updated on June 28, 2023 by Editorial Team Author(s): Emil Novakov Originally published on Towards AI. By leveraging AI bots and ChatGPT, businesses can streamline operations, increase productivity, and enhance customer experiences. But how do these AI-powered language models actually work in business situations?

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Judicial systems are turning to AI to help manage its vast quantities of data and expedite case resolution

IBM Journey to AI blog

As such, the judiciary has long been a field ripe for the use of technologies like automation to support the processing of documents. Efforts to further expand the use of emerging technologies to address this ongoing need put responsible artificial intelligence (AI) at the center of possible solutions.

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Bring light to the black box

IBM Journey to AI blog

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation to become business critical for many organizations. While the promise of AI isn’t guaranteed and may not come easy, adoption is no longer a choice. So what is stopping AI adoption today? It is an imperative.

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A New AI Paper from UC Berkeley Introduces Anim-400K: A Large-Scale Dataset for Automated End-To-End Dubbing of Video in Japanese and English

Marktechpost

Even with the advances in automated subtitling facilitated by Machine Translation (MT) and Automatic Speech Recognition (ASR), automated dubbing is still a laborious and expensive procedure that frequently requires human involvement. It also offers strong metadata support for a range of difficult video operations.