By Ben Lorica, O’Reilly
Democratizing access to large training data will level the playing field. Because many of the models we rely on—including deep learning and reinforcement learning— are data hungry, the anticipated winners in the field of AI have been huge companies or countries with access to massive amounts of data. But services for generating labeled datasets (specifically companies that rely on human labelers) are beginning to use machine learning tools to help their human workers scale and improve their accuracy. And in certain domains, new tools like generative adversarial networks (GAN) and simulation platforms are able to provide realistic synthetic data, which can be used to train machine learning models. Finally, a new crop of secure and privacy-preserving technologies that facilitate sharing of data across organizations are helping companies take advantage of data they didn’t generate. Together, these developments will help smaller organizations compete using machine learning and AI.
https://www.oreilly.com/ideas/9-ai-trends-on-our-radar
Share on Facebook