Machine Learning Times
EXCLUSIVE HIGHLIGHTS
AGI Is Infeasible. Instead, Pursue Superhuman Adaptable Intelligence
  Originally published in Forbes On a recent episode of the...
Artifact-Driven Development: Making It Possible to Query Large Analytics and AI Projects
 A practical introduction to making complex project structure explicit...
Incoherent AGI Hype Spurs An Industrywide Pivot To Hybrid AI
  Originally published in Forbes Recently on The Dr. Data Show,...
The AI Paradox: More Humanlike Means Less Autonomous
  Originally published in Forbes The AI executives are at...

biopharmaceutics

Applications of Predictive Modeling in Drug Development

 Recently, various empirical and semi-empirical models embedded in different modeling tools have been developed and recognized for their role in predicting pharmacokinetics of drugs in humans. These models have also been used to evaluate the effects of intrinsic (e.g., organ dysfunction, age, genetics) and extrinsic (e.g., drug-drug interactions) factors, alone or in combinations, on drug