The reality is that AI is still heavily-reliant upon smart, willing and trained humans in order for AI to behave in a manner that we would expect. Humans are needed to scope the problems, identify relevant examples and verify the results. Without humans as a guide, current AI is no more capable
IBM’s community of big data developers continues to grow. As our Big Data Developer meetup program moves into its fifth year, this worldwide community of customers, partners and IBM developers is on the verge of enlisting its 100,000th member—when we published this blog, we counted 99,100.
Without question, our lives are very different from only a couple decades ago, thanks in part to some pretty amazing technology advances including smartphones and other devices, mobile apps, an ever-growing array of social channels and more. Take a look at how one telecommunications organization
Women might make up 30 percent of the workforce at technology companies—for now—but they’re a force to be reckoned with no matter their numbers. Are you trying to balance work and life while advancing in your career? Or are you considering pursuing a career in tech? Find how IBM is embracing the
The movie Deepwater Horizon that depicts the oil spill disaster of the same name serves as an example of how government agencies and corporations need to collect a lot of data and disseminate information immediately as events quickly unfold. Not only are all parties involved asked for a tremendous
Sooner or later, you will likely adopt a hybrid cloud. Regardless of how you arrived at that point, you realize that you need to understand how to deploy and manage a mixed environment efficiently—and you have to do it soon.
Many marketing concerns have seen the light when it comes to the application of big data analysis as a means of outthinking the competition. Discover three best practices for implementing big data analytics for good data science in marketing initiatives.
Open source is a disruptor that never quits, and it is seemingly penetrating and transforming every aspect of established data, analytics and application ecosystems. Give this podcast, recorded at IBM InterConnect 2016, a listen to learn how open source initiatives are transforming machine learning.
Open source is a disruptor that never quits. It seems to be penetrating and transforming every aspect of established data, analytics and application ecosystems. In this podcast, recorded at IBM InterConnect 2016, listen to David Taieb, a cloud data services developer advocate at IBM, share his
Open source is a disruptor that never quits, and it seems to be penetrating and transforming every aspect of established data, analytics and application ecosystems. In this podcast, recorded at IBM InterConnect 2016, listen to Kamille Nixon, portfolio marketing manager at IBM, share her expert
Apache Spark not only excels at data warehousing, in-memory environments for building data marts and other functions, it also is well suited for pulling data from a wide range of sources and transforming and cleansing that data in an Apache Hadoop cluster. And then there is Spark’s complementary