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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

encouraging and rewarding) a culture of experimentation across the organization. These rules are not necessarily “Rocket Science” (despite the name of this blog site), but they are common business sense for most business-disruptive technology implementations in enterprises. Test early and often.

Strategy 290
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How the DataRobot AI Platform Is Delivering Value-Driven AI

DataRobot Blog

Collaborative Experimentation Experience – the new experience, called the Workbench, comes packed with new capabilities such as new integrated data prep for modeling and notebooks providing a full code-first experience. New Snowflake integrations and the SAP joint solution have tightened the data to experimentation to deployment loop.

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AI Governance: Break open the black box

IBM Big Data Hub

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. This includes capturing of the metadata, tracking provenance and documenting the model lifecycle. The post AI Governance: Break open the black box appeared first on Journey to AI Blog.

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Bring light to the black box

IBM Big Data Hub

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation to become business critical for many organizations. Read the AI governance e-book The post Bring light to the black box appeared first on IBM Blog.

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Unlock data across organizational boundaries using Amazon DataZone – now generally available 

AWS Big Data

In this blog post, we share what we heard from our customers that led us to create Amazon DataZone and discuss specific customer use cases and quotes from customers who tried Amazon DataZone during our public preview. The metadata forms types, and asset types can be used as templates for defining your assets.

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Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes

AWS Big Data

The following examples are also available in the sample notebook in the aws-samples GitHub repo for quick experimentation. Update your-iceberg-storage-blog in the following configuration with the bucket that you created to test this example. Note the configuration parameters s3.write.tags.write-tag-name

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AI in Analytics: The NLQ Use Case

Sisense

In my previous blog , I wrote about Natural Language Query (NLQ, or search analytics for some), as one of the major topics that we, the AI group in Sisense, are working on. In this blog, I would like to expand on NLQ and discuss how this AI technology can be leveraged in our domain.