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Learn to apply best practices and optimize your operations.

• Reskilling the analytics team: Math, science and creativity

  Technical skills are a must for data scientists. But to make analytics teams successful, they also need to think creatively, work in harmony and be good communicators. Continue Reading

• AI for business operations starts to offer value

  Businesses are starting to implement AI in operations to smooth out back-office processes and streamline repetitive tasks that currently take too much time for human workers. Continue Reading

• Threats of AI include malicious use against enterprises

  As sophisticated tools become easier to use, enterprises need to protect themselves against AI threats to ensure they do not become the victims of malicious attacks. Continue Reading

• How one company thinks chatbots and AI can change insurance

  Insurance agency management company In-Fi is hoping AI chatbots can streamline homeowner insurance applications and bring the process in line with customers' expectations. Continue Reading

• Harman's plan for AI in cars moving full speed ahead

  Can an AI virtual assistant in every car save the auto industry from sluggish sales and an uncertain future? Audio component manufacturer Harman argues that it can help. Continue Reading

• More curiosity could help narrow AI tools handle broader uses

  Today, engineers are developing AI tools primarily for individual applications, but programming a facsimile of curiosity into algorithms could help make them more general purpose.Continue Reading

• AI virtual assistant tools prove better for customer service than chatbots

  AI virtual assistant software is increasingly surpassing chatbots and natural language search, as enterprises see deeper value in enabling true conversation.Continue Reading

• Humans and AI tools go hand in hand in analytics applications

  Companies are keeping data analysts and other workers in the loop with AI applications to check the results generated by automated algorithms for accuracy, relevance and missing info.Continue Reading

• Insurer's machine learning use case: Changing driver behavior

  Machine learning tools can be put to use for more than targeted marketing and product recommendations. Auto insurer HiRoad is using them to help create safer drivers.Continue Reading

• Artificial intelligence data storage planning best practices

  AI storage planning is similar to the storage planning you're used to: Consider capacity, IOPS and reliability requirements for source data and the application's database.Continue Reading

• Chatbot applications must get better at chatting to engage users

  Today's AI chatbots are good at taking orders and delivering scripted responses, but experts say tomorrow's chatbots need to be more conversational in order to deliver bigger value.Continue Reading

• Wayfair's chief architect talks AI-driven innovation, impactful IT

  Wayfair sells home furnishings, but under the covers, it's a tech juggernaut. Chief Architect Ben Clark explains how AI-driven innovation propels the business.Continue Reading

• Why machine learning models require a failover plan

  Flawed machine learning models lead to failures and user interruptions. Expert Judith Myerson explains the causes for failures and how a failover plan can improve user experience.Continue Reading