Machine Learning and the Future of Agriculture
The world faces a fundamental food problem: quantity versus quality. For the last several decades these two notions have been at odds, with the gap widening. What can put a stop to this?
The world faces a fundamental food problem: quantity versus quality. For the last several decades these two notions have been at odds, with the gap widening. What can put a stop to this?
BMW Group seems to regard additive manufacturing as a source of new products and innovative business models rather than a manufacturing process to resolve existing issues.
The rise of big data and machine learning has created new opportunities for incumbent insurers and competitors alike.
How direct-to-consumer genotype company 23andMe uses open innovation to drive genetic research
AI-driven product development may help GM find an edge in an industry that has increasingly trended towards conformity in the face of uncertainty. Can GM use machine learning to transform from a company hedging its risk by dabbling in everything new – to a company that thrives on compressed, cost effective design cycles with measurable results?
The poor state of mineral exploration and the potential role machine learning will play in the future
Can Verb Surgical use advanced robotics and machine learning to deliver high quality surgical care to the 5 billion [16] people around the world who desparately need it?
Applying machine learning to agriculture, John Deere is committed to innovation.
Generally, machine learning is perceived for computer technology-driven firms. This article examines the use of machine learning in an old world industry such as oil and gas.
Managing sales and account management teams using data and machine learning