Artificial intelligence and analytics
- June 07, 2017
When deploying deep learning models into production, experts say it's important to take care of the basics, like model design and testing, to ensure optimal business impact.
- June 06, 2017
Databricks brings new features to its managed Spark platform -- as well as to open source Spark -- that it hopes will make the computing engine more widely usable.
- June 05, 2017
At Facebook it's all about user engagement, and to accomplish this, the company relies heavily on deep learning algorithms to tailor its products to the interests of individuals.
- May 31, 2017
Modern AI tools fall short of true artificial intelligence, and this could have implications for how the technology is used by enterprises in the near future.
- May 18, 2017
Deep learning may share some characteristics of traditional machine learning, but experienced users say it's really in a class by itself when it comes to model design and output.
- April 19, 2017
To get the most value from investments in advanced analytics techniques, like artificial intelligence and data science, businesses must embrace a specific mindset.
- April 05, 2017
Artificial intelligence apps provide invaluable insights and assistance for a host of business processes, and today's uses are just the tip of the iceberg.
- March 15, 2017
Simply hiring a data scientist doesn't mean you'll get the full benefits of data science. Several enterprises describe how they made the practice pay off for them.
- March 10, 2017
Last year saw a ton of hype around emerging AI tech, but as they penetrate further into the enterprise, experts are urging caution.
- December 23, 2016
Artificial intelligence applications were all the rage in 2016, but while some delivered impressive results, others didn't work quite as well as developers planned.
- September 09, 2016
Responses to a White House request for information on AI software show stakeholders are still split between worry and enthusiasm for this fast-developing technology.
- July 20, 2016
AI systems are generating huge hype right now, which makes it imperative for businesses to understand how the technology can be deployed most effectively.