trusted-ai 
Analytics Vidhya
JULY 3, 2023
In today’s rapidly evolving technological landscape, artificial intelligence (AI) has emerged as a powerful tool influencing many aspects of our lives. However, concerns about the ethical use of AI have grown in parallel with its advancements. The misuse of AI can lead to biased outcomes and erode public trust.
Cloudera
DECEMBER 1, 2023
Recent Government Initiatives on Public Sector AI Solutions In recent years, governments across the globe have recognized the transformative potential of artificial intelligence (AI) and have embarked on initiatives to harness this technology to drive innovation and serve their citizens more effectively.
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Cloudera
JANUARY 30, 2024
In the dynamic landscape of modern manufacturing, AI has emerged as a transformative differentiator, reshaping the industry for those seeking the competitive advantages of gained efficiency and innovation. There are many functional areas within manufacturing where manufacturers will see AI’s massive benefits.
Cloudera
OCTOBER 24, 2023
The AI technologies of today—including not just large language models (LLMs) but also deep learning, reinforcement learning, and natural-language processing (NLP) tools—will equip telcos with powerful new automation and analytics capabilities. AI-powered automation is already driving significant margin growth by reducing costs.
Advertiser: Data Robot
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. Are you ready to deliver fair, unbiased, and trustworthy AI?
Dataiku
DECEMBER 18, 2023
With the provisional agreement on the EU AI Act reached last week, it is tempting for companies to take the easy path and tailor their response precisely to the law. The best strategy for global organizations is to create a resilient system which allows for adaptation while ensuring trust in AI models, projects, and programs.
DataRobot
JULY 16, 2021
Just as trust needs to be established in our personal and business relationships, it also needs to be established between an AI user and the system. Transformative technologies such as autonomous vehicles will be possible only when there are clear methods and benchmarks to establish trust in AI systems. Performance.
Advertiser: Data Robot
Trust is an essential part of doing business. Whether it is the reliability of the supply chain, the accuracy of financial predictions, or the assurance of product availability, trust from customers, vendors, and suppliers is non-negotiable. AI operations, including compliance, security, and governance.
Advertiser: Data Robot
Capitalizing on the incredible potential of AI means having a coherent AI strategy that you can operationalize within your existing processes. Download this eBook to learn about: Achieving ROI with AI and delivering valuable results with urgency. AI storytelling in communicating value to your organization.
Advertiser: Data Robot
Democratization puts AI into the hands of non-data scientists and makes artificial intelligence accessible to every area of an organization. But in order to reap the rewards that AI offers, it is essential that businesses first address how their organizations are set up, from their people to their processes. Building trust in AI.
Advertiser: Data Robot
AI is becoming ubiquitous. The number of critical touch points is growing exponentially with the adoption of AI. But with the incredible pace of the modern world, AI systems continually face new data patterns, which make it challenging to return reliable predictions. Brought to you by Data Robot.
Advertiser: Data Robot
Many organizations are dipping their toes into machine learning and artificial intelligence (AI). Machine Learning Operations (MLOps) allows organizations to alleviate many of the issues on the path to AI with ROI by providing a technological backbone for managing the machine learning lifecycle through automation and scalability.
Advertiser: Data Robot
But we can take the right actions to prevent failure and ensure that AI systems perform to predictably high standards, meet business needs, unlock additional resources for financial sustainability, and reflect the real patterns observed in the outside world.
Advertiser: Data Robot
And more is being asked of data scientists as companies look to implement artificial intelligence (AI) and machine learning technologies into key operations. Sharing data with trusted partners and suppliers to ensure top value. Fostering collaboration between DevOps and machine learning operations (MLOps) teams.
Advertiser: Data Robot
The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology. Download the report to gain insights including: How to watch for bias in AI.
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