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Combating AI bias in the financial sector
Companies must use explainable AI to avoid making unfair and biased decisions about consumers. Some use machine learning tools; others avoid personally identifying information.
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How Cerebras CS-2 update stands up to competitors' offerings
The AI vendor's update now includes tighter support for PyTorch and TensorFlow. Focused on complex deep learning applications, Cerebras competes with Microsoft Azure and Nvidia.
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Stochastic processes have various real-world uses
The breadth of stochastic point process applications now includes cellular networks, sensor networks and data science education. Data scientist Vincent Granville explains how.
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Stochastic point processes and their practical value
Data scientists learn and utilize stochastic point processes for myriad pragmatic uses. Data scientist Vincent Granville explains this in his new book.
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AI infrastructure News
Nvidia shows updated AI, omniverse tools for enterprises
Software is the engine that powers many of the AI hardware and software giant's systems, including a new computing system for the omniverse, according to CEO Jensen Huang.
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AI technologies News
Combating AI bias in the financial sector
Companies must use explainable AI to avoid making unfair and biased decisions about consumers. Some use machine learning tools; others avoid personally identifying information.
-
AI platforms News
Fintech vendor releases AI tool for commercial real estate
Unlike the residential real estate market, growth in commercial real estate has been slow. A fintech vendor is seeking to fill a market need for commercial real estate data.
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Machine learning platforms News
How Cerebras CS-2 update stands up to competitors' offerings
The AI vendor's update now includes tighter support for PyTorch and TensorFlow. Focused on complex deep learning applications, Cerebras competes with Microsoft Azure and Nvidia.
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AI business strategies Manage
Use an AI governance framework to surmount challenges
As AI governance adapts to the rapidly expanding field of AI, businesses need a holistic framework to surmount challenges with clearly defined roles and responsibilities.
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Enterprise applications of AI News
Making AI systems responsible, competitive and functional
Many enterprises have a tough time building fair and trustworthy models. Doing so could be profitable for enterprises, while not doing so could be catastrophic.
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Find Solutions For Your Project
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Stochastic processes have various real-world uses
The breadth of stochastic point process applications now includes cellular networks, sensor networks and data science education. Data scientist Vincent Granville explains how.
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What is AI governance and why do you need it?
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How businesses can measure AI success with KPIs
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Interpretability and explainability can lead to more reliable ML
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Problem Solve
Expanding explainable AI examples key for the industry
Improving AI explainability and interpretability are keys to building consumer trust and furthering the technology's success.
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Migrating to the era of glass box AI
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Discover 2 unsupervised techniques that help categorize data
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Combating racial bias in AI
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Use an AI governance framework to surmount challenges
As AI governance adapts to the rapidly expanding field of AI, businesses need a holistic framework to surmount challenges with clearly defined roles and responsibilities.
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How companies can achieve AI ROI
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Enterprise hybrid AI use is poised to grow
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Automated machine learning improves project efficiency
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E-Handbook | August 2020
Machine learning and bias concerns weigh on data scientists
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E-Handbook | November 2019
Data visualization process yields 360 AI-driven analytics view
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E-Handbook | October 2019
Neural network applications in business run wide, fast and deep
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E-Handbook | July 2019
Machine learning platform architecture demands deep analysis
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Buyer's Handbook | June 2019
Pinpoint the right RPA products to advance your organization
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Enterprise Artificial Intelligence Basics
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data splitting
Data splitting is when data is divided into two or more subsets. Typically, with a two-part split, one part is used to evaluate or test the data and the other for training the model.
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artificial general intelligence (AGI)
Artificial general intelligence (AGI) is the representation of generalized human cognitive abilities in software so that, faced with an unfamiliar task, the AI system could find a solution.
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Stochastic point processes and their practical value
Data scientists learn and utilize stochastic point processes for myriad pragmatic uses. Data scientist Vincent Granville explains this in his new book.
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Machine learning platforms
How Cerebras CS-2 update stands up to competitors' offerings
The AI vendor's update now includes tighter support for PyTorch and TensorFlow. Focused on complex deep learning applications, Cerebras competes with Microsoft Azure and Nvidia.
-
Enterprise applications of AI
Making AI systems responsible, competitive and functional
Many enterprises have a tough time building fair and trustworthy models. Doing so could be profitable for enterprises, while not doing so could be catastrophic.
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AI technologies
Monitaur makes AI governance tool generally available
GovernML helps enterprises determine policies surrounding responsible and ethical AI. It also helps enterprises determine their risk management policies.