Data Generative AI Training 
CIO
FEBRUARY 25, 2025
This is particularly true for Generative AI, which presents several inherent security challenges. Here are some of the key risks related to AI that organizations need to bear in mind. No Delete Button The absence of a delete button in Generative AI technologies poses a serious security threat.
CIO
NOVEMBER 27, 2024
Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.
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TechCrunch
SEPTEMBER 30, 2023
As tech companies begin to monetize generative AI, the creators on whose work it is trained are asking for their fair share. But so far no one can agree on whether or how much artists should be paid. A recent open letter from the Authors Guild signed by more than 8,500 writers, including Margaret Atwood, […]
AWS Machine Learning - AI
MARCH 4, 2025
In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process. We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices.
TechCrunch
DECEMBER 27, 2023
The New York Times is suing OpenAI and its close collaborator (and investor), Microsoft, for allegedly violating copyright law by training generative AI models on Times’ content. All rights reserved.
CIO
NOVEMBER 28, 2024
Uber no longer offers just rides and deliveries: It’s created a new division hiring out gig workers to help enterprises with some of their AI model development work. Data labeling in particular is a growing market, as companies rely on humans to check out data used to train AI models.
AWS Machine Learning - AI
NOVEMBER 7, 2024
While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle.
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