Every day we create 2.5 quintillion bytes of data, a figure that’s only increasing. To make informed decisions, organizations must invest in technologies that allow them to analyze this data effectively. With such large amounts of data involved, traditional manual techniques are no longer viable if we want to capture even the smallest percentage of this information. This is why organizations are turning to AI-driven media monitoring and media intelligence. There’s still confusion and uncertainty about what exactly AI technology is, what it can do, and how it can impact business strategies.
There’s a lot of discussion around the use of AI to automate every task humanly possible, and dystopian visions of massive unemployment as the robots take over is spreading through the ether. The facts are that “there is no true silver bullet” and understanding and using technology to enable better results and experiences is critical but the human element is equally critical.
The rise of big data has propelled new conversations around how we source, organize and analyze information. With advances in natural language processing, machine learning and artificial intelligence, organizations are now able to apply computational power to process large amounts of unstructured data, something that was previously beyond our capabilities.
When the Greenwood, SC newspaper Index-Journal reported on a complaint that Dairy Queen was apparently serving up human meat in its burgers, they weren’t expecting to go viral. Unsurprisingly, the complaint was revealed to be baseless. But the story captured the imaginations of the online world – being shared widely across social media before ultimately being covered by the Washington Post.
Recent hiccups at the Department of Justice illustrate how keywords aren’t enough – they don’t adequately capture the context of a document or piece of information. This makes identifying and capturing the content you want increasingly complex in the “world of fake news.”
Integrating artificial intelligence into your organization’s daily work isn’t as effortless as flipping a switch, but it’s easier if you start with the right framework and the right people.
To be successful, all associations need strong member engagement strategies. One tactic is to use natural language processing and machine learning—two artificial intelligence technologies—to make member content feel more personalized and relevant.
In this first presentation of a series of discussions on Contexture’s Natural Language Processing and Machine Learning technology, CTO Craig…
In conversation with a customer the other week, she made the comment that “natural language processing (NLP) is all the buzz around here but nobody really knows what it is and how to use it.” And while there’s a lot of hype around how NLP, machine learning, blockchain, and AI are rapidly transforming all markets;
Those businesses that aren’t adopting innovative technologies around machine learning, natural language processing, artificial intelligence, and content personalization will be marginalized in the not too distant future.