Advances in artificial intelligence (AI) are growing quickly, but Bitmain, a Beijing-based company, wants to accelerate the process of data delivery.
Bitmain has launched a pair of new hardware products to expedite artificial intelligence (AI) applications. Bitmain’s first hardware products, the BM1680 and the SC1, are said to give better performance and optimise costs in comparison to conventional implementations using graphics processing units.
The BM1680 is a customized tensor computing Application Specific Integrated Circuit (ASIC) optimized for multiple types of inference and training functions for deep learning networks, while the SC1 is an advanced fan-cooled module which combines the BM1680 into a compact, easy-to-integrate package. The products are fully compatible with AI platforms including Caffe, Darknet, Googlenet, VGG, Resnet, Yolo, and Yoto2.
Micree Zhan, CEO of Bitmain, said: “AI hardware is an area that Bitmain is proactively developing to power the next generation of AI applications. Bitmain saw trends in the AI business that were similar to the early days of Bitcoin, and so we started to explore AI toward the end of 2015. Now after only a year and a half, we have the mass-production chips in hand.”
Meanwhile, Expert System hosted its first Cogito AI Day conference to discuss AI and its use in business. Forrester Research’s VP and Principal Analyst Boris Evelson, also the keynote speaker of the conference, has used ‘tsunami’ as a metaphor to indicate the rate at which AI technologies are being adopted by companies presently. The number of firms deploying AI technologies has increased 27% in 2017 from 2016. Intesa Sanpaolo and Lloyd’s of London were among others to participate in the conference.
Stefano Spaggiari, CEO of Expert System, said: “The impact of AI in the near future will be even more decisive. Artificial Intelligence allows companies to overcome the purely ‘numerical’ management of data by adding the ability to understand and manage information in a way that captures the maximum business value.”