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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

The manufacturing industry is in an unenviable position. Manufacturers are being called to reduce their carbon footprint, adopt circular economy practices and become more eco-friendly in general. And manufacturers face pressure to constantly innovate while ensuring stability and safety.

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EU Commission Issues Draft AI Regulation

Data Matters

Companies engaged in the development, manufacturing, importation, distribution, servicing, and use of AI – irrespective of industry – should assess to what extent their products are implicated and how they will address any regulatory requirements they are subject to.

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Leveraging generative AI on AWS to transform life sciences

IBM Big Data Hub

Life sciences industry has—for decades now—moved from the traditional discovery-based drug development to target market-based drug development paradigm. Yet, it is burdened by long R&D cycles and labor-intensive clinical, manufacturing and compliancy regimens.

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The Hacker Mind Podcast: The Internet As A Pen Test

ForAllSecure

That's an example of AI. So while I'm not going to log in as root or admin on the bottom for a lot of those kinds of scenarios, I absolutely help our clients understand based upon industry knowledge based upon what we see, etc. I will give you an example. And we're also on the cusp of ChatGPTs on everyone's terms.

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Best Fraud Management Systems & Detection Tools in 2022

eSecurity Planet

For example, Experian’s 2021 Global Identity and Fraud Report stated that 82% of surveyed businesses had adopted customer recognition strategies. In its 2021 Threat Force Intelligence Index , IBM reported that manufacturing and financial services were the two industries most at risk for attack, making up 23.2%

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