Big Data Engine Leads to AI Generation

By: GIGABYTE & Infinities

More and more companies are eager to embrace AI, but facing difficulties to start. The cycle of AI workflow involves experimentation, exploration, and perfection. In different stages, the resource scale and tools used to differ. According to the experience shared by AI scientists, it usually takes two to three weeks to prepare the infrastructure for the cloud environment. Reports also point out that AI scientists usually spend 35% of the workload on infrastructures. It is quite time-consuming!

To solve the problems mentioned above, GIGA-BYTE TECHNOLOGY CO., LTD.InfinitiesSoft Solutions Inc., and Bigtera Inc. are to provide an AI/Data Science cloud platform to streamline data, tools, and workflows in AI training & Big Data analysis. This cloud platform allows you to virtualize and share the GPU and CPU resources of your bare-metal hardware deployment, maximizing time and cost efficiency when running GPU-based AI/DNN training or CPU-based analysis workloads.

AI-Stack enables companies to use AI faster and easier, without spending too much time thinking about how to deploy for the computing/development/training environment required to adopt AI/Big Data. AI-Stack provides a ready-to-use work environment for AI and data scientists/engineers, enabling AI professionals to spend their time and effort on AI and development rather than the basic environment.

AI-Stack provides enterprises with a self-sufficient, controllable, sharable, and horizontally expandable private cloud/computing environment to provide enterprises with reliable, powerful, cost-competitive, resource-efficient and efficient AI and big data development environment. AI-Stack supports GPU and AI process automation, reducing the complexity and learning curve used by AI engineers and scientists with Tensorflow, Caffe and other deep learning tools. With AI-Stack, AI engineers and scientists can focus on AI and Machine Learning tasks without spending a lot of time on system maintenance, tuning, and deployment.

The views and opinions in this piece reflect those of GIGABYTE & Infinities and not necessarily those of GSMA.