Summary: Not enough labeled training data is a huge barrier to getting at the equally large benefits that could be had from deep learning applications. Here are five strategies for getting around the data problem including the latest in One Shot Learning.
In-memory database technology is fashionable in recent years as the price of RAM drops substantially and gigabyte chips become affordable. By taking advantage of the cost-performance value of RAM, leading edge database developers are boosting the performance of next-generation databases with in-memory technology. However, many developers who intend to adopt in-memory technology only think of speed in terms of RAM, and do not exploit the true power of in-memory technology.
The BigObject® - A Computing Engine Designed for Big Data
BigObject® presents an in-place* computing approach, designed to solve the complexity of big data and compute on a real-time basis. The mission of the BigObject® is to deliver affordable computing power, enabling enterprises of all scales to interpret big data. With the advances in what a commodity machine can perform, it…Continue
Added by Yuanjen Chen on November 20, 2013 at 5:29pm — No Comments
In general, computer scientists treats code and data in two very different ways. Virtual memory was originally developed to run big programs (code) in small memory, while data are entities kept in external storage and must be retrieved into memory before computing. As a result, today’s application developers think by instinct the programming model based on storage and explicit data retrieval. This model, referred to as storage-based computing, plays an important role and has done a great job…Continue
Added by Yuanjen Chen on October 31, 2013 at 7:24pm — No Comments