Evaluate

Evaluate

Weigh the pros and cons of technologies, products and projects you are considering.

• 3 GAN use cases that showcase their positive potential

  GANs' ability to create realistic images and deepfakes have caused industry concern. But, if you dig beyond fear, GANs have practical applications that are overwhelmingly good. Continue Reading

• 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

• Chatbots in customer service find success with focused goals

  Chatbots can be a great adjunct to customer service, but a successful rollout requires careful planning, flexibility and clear objectives. Continue Reading

• Wayfair takes a dip into NLP image processing technology

  At Wayfair, using computer vision and NLP to understand the meaning behind images and searches is the key to customer recommendation, satisfaction and easy substitutability. Continue Reading

• 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

• AI for retailers is progressing

  AI in retail adoption has been relatively slow, but it's starting to pick up as retailers see the benefits of AI technologies and the realities of e-commerce competition.Continue Reading

• Use of AI in government makes agencies smarter

  Government agencies are starting to embrace some of the same AI technologies that typical enterprises use, and many are finding increased efficiencies along the way.Continue Reading

• Reinforcement learning and deep learning pairing pushes AI limits

  The pairing of reinforcement and deep learning is enabling researchers to push the boundaries of what AI can do and could help contribute to advanced applications.Continue Reading

• Mapping adoption of artificial intelligence in the enterprise

  As many enterprises focus on use case research, the mature uses of AI are concentrated in supervised learning, structured data extraction and using a small number of platforms.Continue Reading

• Machine learning platform architecture demands deep analysis

  This handbook offers advice on choosing machine learning platforms and using them to get accurate and meaningful information from analytics applications.Continue Reading

• More to machine learning platforms than meets the AI

  To reach full analytics potential, machine learning platforms powered by AI must provide scalability, handle multiple models, integrate with data sources and be cloud-friendly.Continue Reading

• 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

• How AI in physical security makes public places safer

  Deep learning-based tools are increasingly finding a home in physical security to enhance the protection of real-world assets and make public spaces safer.Continue Reading

• AI in the legal industry focuses on augmenting research

  From billable time invoice generation to patent attribute data mining, the implementation of AI in law firms has aided in reducing low-value, time-consuming paralegal work.Continue Reading

• Consider these 12 RPA software vendors for deployment

  RPA technology can help companies successfully automate their tasks and processes if they can sift through the options to determine the right system for their enterprise.Continue Reading