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Learn to apply best practices and optimize your operations.

• Wield AI to personalize consumer products and aid logistics

  Companies using AI to sell consumer products seek brand loyalty by using personalization, online sales capabilities and optimized inventory management Continue Reading

• Data scientists urged to take AI security threats more seriously

  AI security hasn't been the top concern of most data scientists using machine learning. But as these systems move closer to the core of the business, security is becoming critical. Continue Reading

• Address anonymity and data privacy in chatbot security

  A key to successful enterprise chatbot security is to program your chatbot to recognize personal or sensitive information and treat it accordingly. Continue Reading

• Chatbots in banking at Norway's largest financial company

  By deploying semantics technology over neural networks, startup Boost.ai has created a conversational AI product that is used by the largest financial services company in Norway. Continue Reading

• Researchers race for quantum AI as quantum computing advances

  Machine learning is likely to be an early application of quantum computers, as researchers and developers look for the key to a more human-like artificial intelligence. Continue Reading

• AI in accounting boosts compliance and fraud detection

  Accounting and finance teams are using AI tools to speed document review and other error-prone processes, which gives a boost to fraud detection and compliance efforts.Continue Reading

• Enterprise AI tools help cultivate better business health

  AI technologies can give companies a business boost, enough so that the number of available jobs for humans may increase instead of declining due to more automation.Continue Reading

• Recruiting data scientists for AI and machine learning

  When hiring data scientists, be sure to include your data science team in the interview process, and strive to build a data-literate HR department. AI tools may also help.Continue Reading

• Using AI in manufacturing processes surges quality and design

  The addition of AI in manufacturing leads to increased workflow -- from design to production. Production plants are turning to technology to supplement the manufacturing skills gap.Continue Reading

• Machine learning in production challenges developers' skills

  Deploying machine learning models requires an entirely different skill set than developing them, and data scientists and engineering teams need to be ready to bridge this gap.Continue Reading

• Data science skills spawn success in AI, big data analytics

  AI and big data analytics initiatives require a broad set of skills, and putting those skills in place often takes teams of data scientists with different strengths.Continue Reading

• 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