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• Tailored content heads machine learning in digital marketing

  Consumers are no longer engaged with content alone -- companies need to create a robust digital marketing strategy personalized to each consumer. Machine learning is here to help. Continue Reading

• Data visualization in machine learning boosts data scientist analytics

  Data scientists offer practical insights into the role of visualization tools in building, exploring, deploying and monitoring their machine learning models. Continue Reading

• Using small data sets for machine learning models sees growth

  While massive data sets allow for easy training, developers are using new techniques to mine and transfer data that allows for training on limited labeled information. Continue Reading

• Training data in facial recognition use cases reveals bias

  Applications of facial recognition technology show incredible promise in law enforcement and personal privacy, but the risks are holding enterprises back from adoption. Continue Reading

• Fintech and retail lead the fray in AI adoption by industry

  Though AI enhances and drives the financial and manufacturing industries, others remain wary of the investment capital and research needed to insert AI into their enterprise. Continue Reading

• How to create a data set for machine learning with limited data

  A shortage of data for machine learning training sets can halt a company's AI development in its tracks. Turning to external sources and hidden data can solve the problem.Continue Reading

• AI in content management revolutionizes unstructured data

  Managing content and data can take business process from unrefined to streamlined. Enterprises can slowly apply technologies to climb the ladder of cognitive content intelligence.Continue Reading

• Using enterprise intelligent automation for cognitive tasks

  RPA is no longer comprised of simple chatbots or repetitive programmed tasks. Enterprises are looking at RPA to move up the ladder of cognitive automation.Continue Reading

• The future of data science and AI points to automatic tools

  The relationship between data scientists and companies using AI is evolving rapidly, shifting from a focus on trained professionals to experienced employees with automated tools.Continue Reading

• GPU analytics speeds up deep learning, other data insights

  GPU-based systems have become a popular platform for deep learning applications, and they're now also being used to accelerate analysis of IoT and geospatial data.Continue Reading

• Pushing past chatbot challenges will secure their longevity

  For chatbots to remain in enterprise futures, developers and data scientists need to get flexible. From open source to intelligent sharing, chatbot collaboration will boost benefits.Continue Reading

• AI and big data go perfectly together -- sometimes

  The combination of big data and AI tools enables new forms of analytics and automation, but use of the technologies in enterprise applications is still evolving.Continue Reading

• AI network security tool autonomously does microsegmentation

  To ensure network security, a U.S. law firm has turned to automated network microsegmentation vendor Edgewise. The startup uses machine learning to deploy microsegmentation.Continue Reading

• AI in professional services revolutionizes white-collar jobs

  Professional services and consulting firms are adopting AI at a rapid rate, even though these types of jobs, which mainly focus on interpersonal interaction, may not seem like strong targets for automation.Continue Reading

• How to improve candidate matching with AI in HR recruitment

  AI in HR recruitment can source talent externally but can also be used to improve internal projects. AI platforms can match qualified existing employees to potential open projects.Continue Reading

• How to recycle data from AI for employee engagement efforts

  By reusing the data collected for AI algorithms and the insights they generate, enterprises can boost employee performance and improve business processes.Continue Reading

• Better together: Predictive analytics and AI boost each other

  Enterprises have long seen the value of predictive analytics, but now that AI is starting to influence forecasting tools, the benefits may start to go even deeper.Continue Reading

• Machine learning bots enable immediate paperless workplaces

  Document digitization allows for the automatic extraction of data through rapid bot technology, as companies aim for a cost-effective, eco-friendly paperless workplace.Continue Reading

• AI bias, for good or ill

  Bias in AI algorithms can produce harmful results, but it can also help train models. This third part of a three-part series on AI ethics explains the pros and cons of AI bias.Continue Reading

• 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 managementContinue 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