Features

Features

• Machine learning ops to lead AI in 2020

  The increased usage of pre-trained models, machine learning ops coming to the fore and increased transparency are all poised to lead the new year in AI.  Continue Reading

• AI trends 2020 outlook: More automation, explainability

  Top AI trends for 2020 are increased automation to extend traditional RPA, deeper explainable AI with more natural language capacity, and better chips for AI on the edge.  Continue Reading

• A year of AI events points to AI predictions for 2020

  A thoughtful reflection on the most important AI technology news of 2019 as well as a look to what 2020 may have in store for the world of AI.  Continue Reading

• How GE uses a 'Humble AI' approach to manufacturing

  GE executive Colin Parris explains why a deliberate approach to deploying AI is needed when dealing with products that cost hundreds of millions of dollars to make.  Continue Reading

• AI in networking helps keep systems running

  Network administrators are increasingly using AI tools to help them manage the growing complexity of their network infrastructure, a task that's getting more complicated by the day.  Continue Reading

• Vendor 3PM uses AI and analytics to prevent Black Friday fraud

  Using AI, analytics and Google Cloud tools, e-commerce intelligence vendor 3PM Solutions helps identify and take down counterfeit products for major e-commerce players.  Continue Reading

• Supervise data and open the black box to avoid AI failures

  As AI blooms, marketers and vendors are quick to highlight easy positive use cases. But implementation can -- and has -- gone wrong in cases that serve as warnings for developers.  Continue Reading

• How to achieve explainability in AI models

  At its core, AI is a complex modeling process with layers of information. In order to be able to explain the algorithm's decision-making process, start with its input data.  Continue Reading

• Tailored content heads machine learning in digital marketing

  Consumers are no longer engaged with content alone -- companies need to create a robust digital marketing strategy personalized to each consumer. Machine learning is here to help.  Continue Reading

• How to build a neural network from the ground floor

  Deep learning is powering the development of AI. To build your own neural network, start by understanding the basics: how neural networks learn, correlate and stack with data.  Continue Reading

• AI in advertising captures audiences with personalized ads

  Using AI technology, AdGreetz generates millions of personalized ads over the web and social media for its client Flipkart, an e-commerce vendor based in India.  Continue Reading

• How to build a chatbot with personality and not alienate users

  Adding personality to a chatbot can push it toward the uncanny valley and raises ethical questions. But enterprises can make their bots more engaging, while avoiding these hurdles.  Continue Reading

• How Getty Images reduces bias in AI algorithms to avoid harm

  In applications from internal job recruiting to law enforcement technology, AI bias is a widespread issue. Here's what enterprises can do to reduce bias in training and deployment.  Continue Reading

• Data visualization in machine learning boosts data scientist analytics

  Data scientists offer practical insights into the role of visualization tools in building, exploring, deploying and monitoring their machine learning models.  Continue Reading

• AI and climate change: The mixed impact of machine learning

  While AI can play a role in helping researchers and conservationists address the impacts of climate change, it can also contribute to carbon emissions, making it a mixed blessing.  Continue Reading