Machine Learning Accuracy Assessment and How to Improve Outputs
Those who trust too much and those who don’t trust machine learning enough will both miss out on potentially better accuracy.
Amazon Releases AI-Based Enterprise Search Solution
The solution uses deep learning models to understand natural language queries and document content.
Selecting and Preparing Data for Machine Learning Projects
Data is the foundation of any machine learning model. Here's how to deal with bias, cross-contamination, and non-numeric inputs.
A Game Plan for Quantum Computing
Some companies may begin to reap gains from quantum computing within five years. Here's what they should know now.
U.S. Facing Threats to AI Tech Leadership
The AI race is inextricably linked with immigration policies and government investment, MIT researchers say.
Can Companies Come to Grips With AI Hype?
As artificial intelligence options pile up, it gets harder to tell what's real from what's fake. But there may be reason to hope for greater clarity: KPMG.
‘Alternative’ Data Drives S&P Global’s Growth
The Fortune 500 data company onboards AI and machine learning capabilities to make hay with unstructured datasets.
Transformation Requires a Scientific Approach
AI, machine learning, and other new technology must replace subjective rules of thumb and one-size-fits-all programs for business transformation to succeed.
Five Ways CFOs Can Use AI — Today
While AI is often overhyped, there are a number of practical applications that are available to finance chiefs.
Financial Application Buyers Are Stuck in the Present
In making software-buying decisions, finance organizations are too focused on gaining efficiencies and not enough on future digital needs, says Gartner.
Amid Data Deluge, Judgment Still Makes the Difference
No matter how much data is fed to machine learning and predictive analytics tools, the key is deciding which outputs are useful and how to act on them.