Evaluate

Evaluate

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

• AI in fashion design and retail takes center stage

  AI and fashion are a natural pairing as clothing designers and retailers are using technology to monitor what's hot and improve the efficiency of manufacturing and supply chains. Continue Reading

• Countries need national strategy for AI to stay competitive

  With the Chinese government funding artificial intelligence at an aggressive pace, the U.S. and other countries are facing substantial pressure to step up their investment. Continue Reading

• Jumio identity verification technology benefits from AI

  ID verification technology is boosted by products of AI and machine learning, including natural language processing, image processing and biometric tools. Continue Reading

• AI cybersecurity tools help spot threats before they cause harm

  Security pros are increasingly using AI-based cybersecurity tools to stay one step ahead of hackers and minimize vulnerabilities before they can be exploited by bad actors. Continue Reading

• Nations sharpen AI strategies as global competition heats up

  The U.S. and China are the leading countries in AI research and development right now, but nations throughout the world are developing strategies to remain competitive. Continue Reading

• Healthcare and AI are a good pair -- until vendors overpromise

  Excessive promotion and grandiose promises from vendors like IBM are making it hard to accurately judge what the proper role of AI in healthcare should be.Continue Reading

• The steady evolution of RPA to intelligent automation

  New technologies have led to new RPA types, as advances in AI, machine learning and natural language processing have evolved the original RPA tools of the 1990s.Continue Reading

• On-device AI features make connected tools smarter

  As the number of connected devices grows, AI at the edge of networks is increasingly making connected devices smarter, enabling them to take advantage of emerging smart technologies.Continue Reading

• The present and future use of AI in healthcare

  The use of AI and machine learning in healthcare has already changed the way some clinical and administrative processes are handled, and it could help reinvent how care is provided.Continue Reading

• Current state of AI is poorly understood by the public

  Current applications of AI revolve entirely around machine learning. But researcher Zachary Lipton says that's not the message you get from most media coverage of AI.Continue Reading

• AI in policing is controversial but delivers results

  The drive toward more predictive policing is only growing stronger as computer vision and other AI tools are put to use. But not everyone is happy with the trend.Continue Reading

• Use of AI in video games boosts playing experience

  The combination of AI and gaming is not necessarily a new phenomenon, but it is gaining traction and contributing to more true-to-life and engaging experiences.Continue Reading

• Bot security through AI openness

  To ensure consumers interact with secure bots and AI tools, vendors like IBM and BotChain propose more AI transparency and have designed ways to achieve that.Continue Reading

• AI in sports helps teams and leagues engage with fans

  The use of artificial intelligence in sports industry is a growing trend that is helping leagues and teams engage with fans and improve the quality of in-game officiating.Continue Reading

• How to make a wise machine learning platforms comparison

  What data sources does it support? Is it easy to use? Does it have automation features? These are just a few questions to ask when making a machine learning platforms comparison.Continue Reading

• Music composed by AI breathes new life into video games

  AI-generated music could help indie video game developers incorporate another element into procedurally generated worlds, making them more dynamic and lifelike.Continue Reading

• IBM and AI: Researcher talks current and future projects

  The goal of numerous IBM AI projects is to ultimately create programs to augment human skills and jobs, not to take jobs away from humans, an IBM researcher says.Continue Reading

• What do businesses do with the top machine learning platforms?

  Take a deep dive into machine learning, including decision trees, clustering, reinforced learning, neural networks, as well as supervised and unsupervised machine learning.Continue Reading

• Machine learning applications: From lab to enterprise

  The process from lab idea to enterprise reality may challenge machine learning applications. Learn how implementers are navigating the journey to practical use.Continue Reading

• AI process automation offers benefits, but challenges remain

  Enterprises are starting to employ machine learning tools as part of their AI automation strategies, but several key challenges stand in the way of effective usage.Continue Reading

• How to find the best machine learning frameworks for you

  There's no shortage of open source deep learning tools today, and evaluating them can be a challenge. But there are some primary considerations to keep in mind.Continue Reading

• Data science tools of the trade fill skills gap

  Data science tools are becoming more intelligent and better at understanding intent and context. But don't stop advertising that data scientist job on the web just yet.Continue Reading

• At Intuit, machine learning enhances products, CTO says

  Intuit's machine learning and AI technology are transforming its many financial software products. CTO Tayloe Stansbury discusses what that means for Intuit.Continue Reading

• Customer support chatbots set to transform service functions

  AI-enabled chatbots are helping enterprises improve their customer service functions by automating some tasks, enabling human workers to focus on what really matters.Continue Reading

• Computer vision technology helps Trulia link buyers to homes

  In this podcast, Trulia's vice president of engineering discusses the importance of computer vision applications to the website's overall goal of helping buyers find homes.Continue Reading

• AI applications in healthcare smooth providers' operations

  Healthcare providers are embracing AI systems at an increasing rate as the potential benefits for both patient care and operational management become more apparent.Continue Reading

• Tech experts weigh in on the AI hype cycle

  AI expectations couldn't be any higher. Read why leading industry experts believe the hype is deserved and what developers can do to deliver on the technology's weighty promise.Continue Reading

• Industries evaluate collaborative robot applications

  Robotics has traditionally been viewed as a threat to jobs, but putting AI in robots can make machines more collaborative and empower human workers to be more effective.Continue Reading

• Enterprises explore AI voice assistant technology

  Intelligent voice assistant devices, so popular among consumers, are starting to make their way into enterprises, but businesses need to be mindful of several challenges.Continue Reading

• Limits of AI today push general-purpose tools to the horizon

  The future of AI should be focused on more general-purpose tools, but developers have a long way to go before achieving the kind of AI movies taught us to expect.Continue Reading

• New Intel toolkit OpenVINO supports deep learning on CPUs

  A new developer kit from Intel seeks to lower the bar for doing deep learning on CPUs and other types of chips to extract more intelligence from video.Continue Reading

• A look at the leading artificial intelligence infrastructure products

  The artificial intelligence infrastructure market is young and varied, with enterprise AI vendors offering everything from cloud services to powerful, and expensive, hardware.Continue Reading

• Data scientist vs. business analyst: What's the difference?

  Data science and business analyst roles differ in that data scientists must deep dive into data and come up with unique business solutions -- but the distinctions don't end there.Continue Reading

• 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

• 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 bias in 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