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 […].
CTOvision
SEPTEMBER 30, 2020
Read Bernard Marr explain the nine soft skills every employee should have in the age of artificial intelligence on Forbes: Technical skills and data literacy are obviously important in this […].
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IT Toolbox
JANUARY 18, 2024
The post Apple, Qualcomm, and AMD GPUs Susceptible To Putting Artificial Intelligence Data at Risk appeared first on Spiceworks. Millions of Apple, Qualcomm, and AMD chips are susceptible to the security flaw.
Forrester IT
DECEMBER 19, 2022
The Forrester Wave™: Artificial Intelligence For IT Operations, Q4 2022 evaluated 11 vendors on 35 different capabilities. Read the report to see the vendor that came out on top with the highest-ranked capabilities for the broadest set of organizations.
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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?
IT Toolbox
MAY 23, 2023
The post Securing Artificial Intelligence in Large Language Models appeared first on Spiceworks. Can we avoid the future risks of harmful sentient AI?
CTOvision
AUGUST 16, 2021
’s future is bright as more and more businesses transition to artificial intelligence backed big data working environments on Seeking Alpha : In a world where technology is advancing faster than ever, it is not outlandish to see life imitate […].
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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. Holding onto old BI technology while everything else moves forward is holding back organizations.
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In March 2020, the world was hit with an unprecedented crisis when the COVID-19 pandemic struck. As the disease tragically took more and more lives, policymakers were confronted with widely divergent predictions of how many more lives might be lost and the best ways to protect people.
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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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Democratization puts AI into the hands of non-data scientists and makes artificial intelligence accessible to every area of an organization. Brought to you by Data Robot. Aligning AI to your business objectives. Identifying good use cases. Building trust in AI.
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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). How can MLOps help data science teams, business leaders, and IT professionals build a resilient and scalable foundation for their AI initiatives? What are the core elements of an MLOps infrastructure?
Advertiser: Data Robot
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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