Few fields change as fast as digital. New channels, new methods, new business models – and all of it demands new methods of measurement and analytics. As new technologies and practices disrupt the field, digital analytics practitioners adapt. In any given year, a few themes dominate, and right now, the topics dominating discussion at the enterprise digital analytics table are four P’s: prioritization, personalization, people and perspective.
1-800-Flowers’ three new AI tools (the chatbot, its integration with Amazon Alexa and its online IBM Watson concierge service) have together attracted orders in the tens of thousands.
Drones have numerous applications in security, inspection, and other major roles at industrial facilities, but in many cases manual control is still the standard.
Globally, 82 percent of content shared on mobile is shared through messaging, email or text.
Interactive neural network “playground” visualization offers insights on how machines learn.
Patagonia, long known for eschewing traditional retail models, announced today that it is disabling its mobile app, a result of enhanced mobile web capabilities that may render certain apps obsolete.
And just like that, social networking is no more. The sites formerly known as social networks are pivoting to something else.
Today the average webpage is about the same size, data-wise, as the classic computer game Doom, according to software engineer Ronan Cremin.
If you’re just tuning in, the tech world is thumbs up on Internet of Things—and thumbs down on PCs—right now. Now, this week Intel is looking like it’s out to become the poster child for the shift.
A group of MIT researchers has sketched out a way to address a gap in cybersecurity that exists between human and machine. Human-made rules, which are meant to alert the system of an attack, don’t work unless an attack exactly matches one of those rules. Machine-learning measures typically rely on anomaly detection. Consequently, false alarms aren’t uncommon and the system starts to distrust itself.