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Machine Learning: Lack of Reproducibility Threatens Credibility

By Dick Weisinger

Reproducibility  and repeatability form the foundation of scientific research. Science works best when researchers have enough information and understanding of the parameters of research that has been done previously so they can reproduce those results and work to build on

Deep Reinforced Learning: Making AI More Accessible by Bootstrapping

By Dick Weisinger

Machine Learning and Deep Learning have become popular tools in the arsenal of Artificial Intelligence (AI), but while AI has generated a lot of interest, one problem is that AI techniques are complex and not enough people are properly trained

Data Science and Machine Learning: Trends Driving Wider Acceptance of ML Decisions

By Dick Weisinger

While Machine Learning is making a big impact across different industries, the fact is that less than ten percent of all companies say that they’ve made any investment in it at all.  ML technology is evolving quickly,and as it does,

Artificial Intelligence: Step-wise Advances Enable Machine Learning to Evolve

By Dick Weisinger

AI that can be used to self-build more complex and more accurate AI is beginning to happen.  Google’s NASNet researchers say that they have developed AI that can do just that.  The computer-generated AI system is called NASNet, and it

Artificial Intelligence Databases: Speeding Training for Machine and Deep Learning

By Dick Weisinger

One of Artificial Intelligence’s biggest roadblocks is data preparation and training.  Collecting and cleaning data and then training software on data to recognize patterns and develop some amount of insight takes a lot of time. New techniques to speed up