Evaluate

Evaluate

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

• Getting to machine learning in production takes focus

  Bridging the gap between training and production is one of the biggest machine learning development hurdles enterprises face, but some are finding ways to streamline the process. Continue Reading

• CTO Simon Crosby explains edge intelligence, talks AI uses and risks

  Edge intelligence is the newborn child of edge analytics and machine learning. In this podcast, CTO Simon Crosby explains the tech and discusses AI uses, data breaches and more. Continue Reading

• Designing and building artificial intelligence infrastructure

  Building an artificial intelligence infrastructure requires a serious look at storage, networking and AI data needs, combined with deliberate and strategic planning. Continue Reading

• Defining enterprise AI: From ETL to modern AI infrastructure

  The promise of enterprise AI is built on old ETL technologies, and it relies on an AI infrastructure effectively integrating and processing loads of data. Continue Reading

• IT, finance and marketing have uses for AI -- do you?

  AI in healthcare improves patient outcomes. AI in IT aids employee compliance and security. AI in logistics, AI in marketing, AI in finance -- learn how your company can use AI. Continue Reading

• AI functionality limited today but could be a game-changer

  Limited AI capabilities could soon give way to technology that is truly transformative for enterprises, surpassing the overhyped functionality that we see today.Continue Reading

• Hype surrounding AI technologies nears atomic proportions

  Amid the infiltration of artificial intelligence into business and society, spawning fears from some of Armageddon, humankind's greatest AI threat may very well come from within.Continue Reading

• Big data throws big biases into machine learning data sets

  AI holds massive potential for good, but it also amplifies negative outcomes if data scientists don't recognize data biases and correct them in machine learning data sets.Continue Reading

• Cognitive computing in healthcare mends doctor-patient gaps

  Cognitive computing and healthcare data aggregation may prove to be important bedside companions to doctors treating their patients in the era of medical specialization.Continue Reading

• AI technologies have come far, but the road is long

  Machine learning and other artificial intelligence technologies are poised to offer businesses big benefits, but companies have to walk before they run with AI.Continue Reading

• Machine vision makes paper a thing of the past for insurers

  The insurance industry is buried in paper-based processes. Former MetLife CIO Gary Hoberman aims to change that with a platform that runs on AI and machine vision.Continue Reading

• How to do a machine learning platform comparison

  Experts share their top criteria for choosing the right machine learning vendor in a market that has become crowded and confusing in the last couple years.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

• Synthetic data could ease the burden of training data for AI models

  Sometimes it's better to manufacture training data for machine learning models than it is to collect it.Continue Reading

• Dun & Bradstreet's chief data scientist: Don't ignore these eight AI topics

  Anthony Scriffignano's list of AI topics to watch in 2018 highlights the benefits and complications the widespread application of artificial intelligence technology will have on the enterprise in the coming year.Continue Reading