Last Week in AI

Every week, Invector Labs publishes a newsletter that covers the most recent developments in AI research and technology. You can find this week’s issue below. You can sign up for it below. Please do so, our guys worked really hard on this:

From the Editor: The Biggest Roadblock for the Mainstream Adoption of Machine Learning

One word: data. Up to this day, we haven’t seen the complete potential of unsupervised models and supervised methods rule the machine learning space. Supervised training requires high quality labeled datasets and those are incredibly expensive to produce on an ongoing basics. These challenge have prevented even large organizations from adopting machine learning at scale and are a major roadblock for startups entering the space.

The labeled data hurtle has two man solutions: Either we develop methods for producing labeled datasets more effectively or we develop methods that can learn with smaller datasets. In the first solution, areas such as generative models are showing some promise to generate high quality training datasets. In terms of the latter, we have seen incredible advances in research in areas such as semi-supervised models, one-shot or zero-shot learning are improving very rapidly. While the adoption of these techniques remain in a very nascent stage, the problem that they are…