Evaluate

AI integration

• Applications of autonomous robots lead in the enterprise

  In enterprise AI, bot technology is leading the charge. Seamless integration and process streamlining are initial benefits, but the true profit lies in what comes next -- auto-AI. Continue Reading

• Computer vision tools reach into test, healthcare, security

  Gaining a reputation as a viable technology in niche applications like X-ray scans, fingerprint matching and robotics, computer vision looks to mainstream, commodified apps. Continue Reading

• AI at the edge spurs decentralization, IoT interconnectivity

  As AI spreads into most enterprises, it's imperative that devices or programs can make immediate smart decisions. Localized AI at the edge is aiming to tackle the lag. Continue Reading

• Inventory optimization machine learning tool sharpens pricing

  Retailers are chasing data-driven process automation in hopes of boosting sales and streamlining margins. But how do you decide which processes to automate or vendor to implement? Continue Reading

• Deep learning recognition use cases grow as tech matures

  As deep learning image and voice recognition technology improves, enterprises are finding novel ways to apply the technology to sharpen and improve their operations. Continue Reading

• Use of AI in payments industry is set to explode

  Payment processors are making wider use of AI technologies as part of an effort to make better use of their vast troves of data and connect more directly with customers.Continue Reading

• AI for knowledge management boosts information accessibility

  Integrating AI for knowledge management systems builds intelligent searches. Enterprises benefit from streamlined, smart content platforms that make information accessible.Continue Reading

• Federated deep learning offers new approach to model training

  Training deep learning models puts a massive strain on enterprise infrastructure, but federated learning, which trains models on endpoint devices, could lessen some of the demand.Continue Reading

• Enterprises are crowdsourcing AI development

  By crowdsourcing AI development, enterprises can broaden the knowledge base of their machine learning applications, and early adopters are showing promising results.Continue Reading

• Data preparation for machine learning still requires humans

  Looking to AI to automate more of your processes? Don't overlook the labor that's still needed to prepare data for training machine learning and AI algorithms.Continue Reading

• Data science and machine learning platforms advance analytics

  Data science platforms include a variety of technologies for machine learning and other advanced analytics uses. This handbook examines them and how they can be used.Continue Reading

• Data science platforms boost automation, collaboration

  Data scientists can choose from a growing list of commercial and open source platforms that ease data access, analytics, model building and management in a collaborative way.Continue Reading

• Enterprises need to develop an AI strategy now

  Business leaders who approach AI as a future concern are likely to miss the boat on this influential technology. The time to explore AI implementation is now.Continue Reading

• Common sense AI approaches point to more general applications

  The race to attain artificial general intelligence is on. Ranging from predictions of 10 to 200 years away, the one thing experts can agree on is that common sense AI is the next step in the journey.Continue Reading

• Perfect AI-defined infrastructure by analyzing your data center

  Before implementing AI, evaluate your IT team and data storage center. Experts explain the fundamental elements of data storage required to tailor an AI-defined infrastructure.Continue Reading