Artificial Intelligence Related Topics 
IT Toolbox
AUGUST 1, 2024
The EU's landmark Artificial Intelligence Act took effect on August 1, 2024. Learn about the world's first artificial intelligence regulations and what they mean for organizations and the artificial intelligence industry worldwide.
IT Toolbox
AUGUST 16, 2024
The Massachusetts Institute of Technology (MIT) has released the world's first comprehensive database to catalog artificial intelligence risks. The post MIT Unveils Comprehensive Database of Artificial Intelligence Risks appeared first on Spiceworks Inc. Learn more about the effort and its importance for end users.
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IT Toolbox
APRIL 12, 2024
Meta has revealed the latest version of its custom artificial intelligence chip, the Meta Training and Inference Accelerator(MTIA). The post Meta Launches New Custom Artificial Intelligence Chip appeared first on Spiceworks. Learn more about the development and its significance for the social media giant.
Forrester IT
APRIL 3, 2024
US federal agencies must now have a chief artificial intelligence officer responsible for operationalizing the safe use of AI. Learn more about this move and the implications in this blog post.
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As artificial Intelligence (AI) becomes more prevalent, it’s crucial that firms adopt AI technology responsibly. This World Economic Forum-GEP report offers a holistic procurement process and structured framework to select responsible AI tools. Download the report today.
IT Toolbox
MARCH 14, 2024
Lawmakers in the European Union have approved the world’s first law to govern artificial intelligence. The post European Lawmakers Approve World’s First Comprehensive Artificial Intelligence Law appeared first on Spiceworks.
CTOvision
MAY 27, 2020
Read Stephanie Overby define five types of artificial intelligence on Enterprisers Project : Artificial intelligence (AI) is redefining the enterprise’s notions about extracting insight from data. Indeed, the vast majority […].
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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.
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In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your application’s analytics capabilities?
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Finally, there’s some breathing room, and the opportunity to create long-term strategy, build resilience and explore the growing potential of artificial intelligence.
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What’s Inside: How organizations can most effectively focus on long-term value creation, not just short-term cost savings The impact that embracing innovation and new technologies such as artificial intelligence (AI) can have The essential elements every organization needs to balance cost, risk, and sustainability
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You know you want to invest in artificial intelligence (AI) and machine learning to take full advantage of the wealth of available data at your fingertips. But rapid change, vendor churn, hype and jargon make it increasingly difficult to choose an AI vendor.
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While everyone is talking about machine learning and artificial intelligence (AI), how are organizations actually using this technology to derive business value? Renowned author and professor Tom Davenport conducted an in-depth study (sponsored by DataRobot) on how organizations have become AI-driven using automated machine learning.
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The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data.
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Many organizations are dipping their toes into machine learning and artificial intelligence (AI). However, for most organizations embarking on this transformational journey, the results remain to be seen. And for those who are already underway, scaling their results across their organizations is completely uncharted waters.
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