AI technologies
Forward-looking enterprises have to be aware of emerging artificial intelligence technologies. Get the latest on AI technologies such as NLP, bots, machine learning, deep learning and open source AI tools.
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AI technologies News
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May 12, 2021
12
May'21
IBM Think 2021 news, trends and analysis
The role of technologies like AI and the cloud in business is changing. This year's IBM Think conference seeks to help enterprises understand how to capitalize on these tools.
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May 11, 2021
11
May'21
IBM Watson Orchestrate poised to take tasks workers hate most
IBM Watson Orchestrate is the latest technology from a major vendor that promises to save employees from highly repetitive job responsibilities.
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May 11, 2021
11
May'21
DataRobot looks to enterprise AI coders with Zepl acquisition
By acquiring cloud data science and analytics platform vendor Zepl, DataRobot gives data scientists a cloud-native, self-service notebook to write tasks and custom models.
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May 04, 2021
04
May'21
Pegasystems to release Process AI amid hyperautomation surge
Pegasystems will add intelligent automation features to its Pega Platform that apply event stream processing, machine learning and natural language processing to business actions.
AI technologies Get Started
Bring yourself up to speed with our introductory content
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Guidelines to implement storage for AI workloads
Organizations with AI-enabled projects need an effective way to store, retrieve and share massive amounts of complex data. These tips will help meet AI data storage challenges. Continue Reading
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robotic process automation (RPA)
Robotic process automation (RPA) is a technology that mimics the way humans interact with software to perform high-volume, repeatable tasks. Continue Reading
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machine learning
Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input ... Continue Reading
Evaluate AI technologies Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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What does NLP mean for augmented analytics?
Explore how NLP is being used by augmented analytics platforms to improve employees' search capabilities, expand data visualization and build a data-driven culture. Continue Reading
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The future of data science jobs
The title of data scientist may soon become obsolete, as new technologies change the responsibilities of data scientists. It may also soon change the nature of the job. Continue Reading
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Moving beyond NLP to make chatbots smarter
Machine reasoning could help chatbots better understand context, which is crucial to understanding human emotions and formulating emotionally relevant responses. Continue Reading
Manage AI technologies
Learn to apply best practices and optimize your operations.
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How to detect bias in existing AI algorithms
While enterprises can't eliminate bias from their data, they can significantly reduce bias by establishing a governance framework and employing more diverse employees. Continue Reading
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Prepare to train AI models for IT Ops non-stop
Algorithms have the potential to revolutionize IT organizations with carefully deployed models. Explore the learning approaches needed to successfully implement and maneuver these AI deployments. Continue Reading
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Transformer neural networks are shaking up AI
Transformers are revolutionizing the field of natural language processing with an approach known as attention. That's just the beginning for this new type of neural network. Continue Reading
Problem Solve AI technologies Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
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5 reasons NLP for chatbots improves performance
Experts say chatbots need some level of natural language processing capability in order to become truly conversational. Without language capabilities, bots are simple order takers. Continue Reading
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How to avoid overfitting in machine learning models
Overfitting remains a common model error, but data scientists can combat the problem through automated machine learning, improving AI literacy and creating test data sets. Continue Reading
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How to troubleshoot 8 common autoencoder limitations
Autoencoders' ability for automated feature extraction, data preparation, and denoising are complicated by their common problems and limitations in usage. Continue Reading