AI integration
Organizations need to update enterprise IT systems to deliver intelligent platforms. Get information about how to integrate AI technologies, such as speech recognition and natural language generation, into existing systems to deliver intelligence platforms across the enterprise.
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We designed this expert guide to help you better understand all of the considerations for building and maintaining the infrastructure and engine that support the initiatives. Plus, learn about the products and players, like Amazon, Google, IBM, and 16 more to help you make the best buying decision.
AI integration News
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August 21, 2019
21
Aug'19
With ThoughtSpot, GlobalTranz makes AI in logistics platform
GlobalTranz, a logistics company, uses AI and analytics in logistics to predict driver behaviors and plan shipping routes that will keep the shippers and the drivers happy.
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July 31, 2019
31
Jul'19
AI council examines emerging trends in AI
Experts on the Illinois Technology Association's AI Council urge companies to use their AI investments to connect with community members to make the best use of the technology.
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July 25, 2019
25
Jul'19
Augmented intelligence applications showing ROI, broad success
Enterprise uses have shown that utilizing augmented intelligence technology increases ROI, productivity and linear success as compared to general AI or AGI.
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July 19, 2019
19
Jul'19
Agricultural equipment maker uses AI for customer experience
Using AWS services Redshift, S3 and SageMaker, as well as third-party tools, AGCO has created new AI marketing tools and a customer portal to better compete in a tight market.
AI integration Get Started
Bring yourself up to speed with our introductory content
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social robot
A social robot is an artificial intelligence (AI) system that is designed to interact with humans and other robots. Continue Reading
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Enterprise AI collaboration tools take tips from dating apps
Enterprise AI collaboration is turning to an unlikely source for inspiration: dating apps that have long used machine-learning based personalization and communication. Continue Reading
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Data science and machine learning platforms advance analytics
Data science platforms include a variety of technologies for machine learning and other advanced analytics uses. This handbook examines them and how they can be used. Continue Reading
Evaluate AI integration Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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Key considerations for operationalizing machine learning
Once a machine learning model is trained, developers need to operationalize it. This turns out to be a significant challenge for many enterprises. Continue Reading
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Causal deep learning teaches AI to ask why
Most AI runs on pattern recognition, but as any high school student will tell you, correlation is not causation. Researchers are now looking at ways to help AI fathom this deeper level. Continue Reading
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Enterprise consumer relationships are building trust in AI
Transparency is an increasingly important component of consumer trust. If you want to win over consumers whose data is being collected, start with explainability and collaboration. Continue Reading
Manage AI integration
Learn to apply best practices and optimize your operations.
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AI in professional services revolutionizes white-collar jobs
Professional services and consulting firms are adopting AI at a rapid rate, even though these types of jobs, which mainly focus on interpersonal interaction, may not seem like strong targets for automation. Continue Reading
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Timeline of AI winters casts a shadow over today's applications
Past generations have had to deal with rounds of inflated expectations and crushing disappointment when it comes to AI. This timeline charts the history of AI's rises and falls. Continue Reading
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How to recycle data from AI for employee engagement efforts
By reusing the data collected for AI algorithms and the insights they generate, enterprises can boost employee performance and improve business processes. Continue Reading
Problem Solve AI integration 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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Experts discuss pressing data science problems and solutions
Most data science projects end up facing similar problems, such as lack of robustness and data quality issues. In this feature, experts offer tips on how to overcome these challenges. Continue Reading
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Mastercard CTO talks AI for fraud prevention, data and hiring
Kush Saxena, CTO of Mastercard, answers three questions about his company's use of AI fraud prevention technology, machine learning and driving commercial value from data at the MIT CIO Symposium. Continue Reading
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Berklee uses SnapLogic for its AI in higher education needs
Berklee College of Music needed intelligent integration for its two student portals after a merger with the Boston Conservatory. The college chose SnapLogic to connect the systems. Continue Reading