Extreme Analytics
6 predictions for the future of deep learning
The potential of deep learning seems boundless, but developers are still figuring out how to put it to work. These near-term trends will help move it along
'Transfer learning' jump-starts new AI projects
Machine learning, once implemented, tends to be specific to the data and requirements of the task at hand. Transfer learning is the act of abstracting and reusing those smarts
How cognitive computing will touch your life in 2017
Cognitive computing has already affected your life, but expect your encounters with machine intelligence to be more frequent and profound
Deep learning is already altering your reality
If we’re living in an algorithmic bubble, we should know how it’s bending and coloring whatever rays of light we’re able to glimpse through it
Data science predicts election winner!
Statistical predictions are fragile flowers. They can inspire confidence, but often only under specific, ephemeral circumstances
Know when your big data is telling big lies
Data scientists face an existential dilemma every single day: How do you distinguish signal from noisy illusion?
IoT's big challenge: Managing billions of devices
IoT will soon permeate every aspect of our lives -- the very definition of sprawl. How will we derive meaningful analytics from the endless IoT fabric?
Advancing the art of the cognitive chatbot
Frameworks are just beginning to emerge for a microservices approach to intelligent personal assistants
How to monetize the fuzzy narratives of social listening
Social media present at best a skewed portrait of how people truly feel or are likely to behave under various circumstances
3 safeguards for intelligent machines
How can we ensure that autonomous devices, including Internet of things endpoints, will never go rogue? Start with these three basic principles
Graph analysis: Not the dots, but the connections
When relationships between entities are more important than the entities themselves, you have a business problem made for graph analysis
Machine learning models need love, too
Machine learning is infusing applications with predictive power -- but unless you give machine learning models ongoing attention, that power will fade away
2020 vision: The triumph of cognitive IoT
In a few years, smart endpoints will distribute cognitive capability everywhere, and we'll wonder how we ever did without it
It's springtime at last for cognitive computing
Artificial intelligence suffered a long winter, but a new name -- cognitive computing -- and a flood of data, innovation, and compute power now has thousands smart applications flourishing
Streaming analytics enter the fast lane
Already we've moved on to a new phase in analytics where data never rests
Algorithms for eyes: How deep learning can help the blind
Algorithms for real-time collision avoidance, geospatial nav, and situational awareness -- coupled with haptic feedback -- may soon provide the visually impaired with invaluable aid
Humans vs. algorithms: Who -- or what -- should decide?
Increasingly, big data algorithms make decisions on customers' behalf. Sometimes they're wrong. Then again, human beings can be even more wrong
No, the data warehouse is not dead
Every surge in new tech prompts declarations that existing tech is circling the drain, but the data warehouse isn't going anywhere -- in fact, it's healthier than ever
The all-consuming future of cloud analytics
An explosion of use cases is driving runaway growth in cloud analytics -- but can anyone really declare that the cloud is the omega of IT platforms?
Hadoop is probably as mature as it's going to get
Five years ago, Hadoop came roaring into the mainstream as the solutions to all big data problems. Now that reality has settled in, it's time for a more realistic assessment
