We have created Artificial Intelligence as a way to amplify human intelligence and promote growth like never before. AI can help us solve numerous problems of varying complexities. One such type of problem is the case where one has to predict outcomes using the given pool of knowledge. Here, the knowledge base is given and using logical rules and reasoning, one has to predict the outcome. These problems are usually solved using Inference Engines, which utilize their two special modes: Backward Chaining and Forward Chaining.

Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning. It can reduce your labeling costs by up to 70% using automatic labeling. This blog post explains the Amazon SageMaker Ground Truth chaining feature with a few examples and its potential in labeling your datasets. Chaining reduces time and cost significantly as Amazon SageMaker Ground Truth determines the objects that are already labeled and optimizes the data for automated data labeling mode. As a prerequisite, you might want to check the post "Creating hierarchical label taxonomies using Amazon SageMaker Ground Truth" that shows how to achieve multi-step hierarchical labeling and the documentation on how to use the augmented manifest functionality.

Artificial Intelligence will remain a high profile topic for years to come and rightfully so: research firms expect the market to grow at a CAGR of 50% to reach $37 billion by 2025. This will generate game-changing productivity gains and transform entire industries. Since the first successful AI experiments in 1955, progress has accelerated dramatically. AI is now broadly used, providing tangible applications for many consumers daily. Examples include Amazon's algorithms making pointed recommendations, Siri answering questions with real-time data from the internet and Watson entering many commercial markets, where AI was absent yesterday.

The world of computing has followed Moore's Law for generations. The "law," which was developed by researcher Gordon Moore in the 1970s, says that the number of transistors that can be squeezed into a set amount of space will double every two years. It's been a reliable gauge ever since. Moore's Law may be nearing its end, however. Tom Simonite at the MIT Technology Review writes that Intel has declared in a regulatory filing what insiders have suspected: The company is slowing the release of new chips in a manner that doesn't keep pace with the law.