AI infrastructure

Enterprises investing in deep learning platforms need AI infrastructure sufficient enough to synthesize a massive amount of data. Here, you'll find the information you need to make decisions about AI-specific compute architectures -- from GPU-packed servers to highly-scalable clustered computing systems built for big data and machine learning applications.

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We designed this expert guide to help you better understand all of the considerations for building and maintaining the infrastructure and engine that support the initiatives. Plus, learn about the products and players, like Amazon, Google, IBM, and 16 more to help you make the best buying decision.

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AI infrastructure News

February 19, 2020 19 Feb'20
New Dell EMC PowerEdge servers are built for the rugged edge

New Dell Streaming Media Platform includes two small form factor PowerEdge servers and a Modular Data Center. Dell aims the products for use in harsh IT environments.
February 07, 2020 07 Feb'20
IBM's Policy Lab calls for AI regulation

Launched during the Davos World Economic Forum, IBM's Policy Lab seeks to unite governments and businesses on creating and adopting more regulation of AI.
February 04, 2020 04 Feb'20
Intel AI hardware roadmap shifts away from Nervana

Intel said it is ending development of its Nervana AI processors. The tech vendor will instead focus its efforts on its Habana Labs processors, which it acquired last year.
January 31, 2020 31 Jan'20
IBM CEO shakeup puts technologist Krishna at Big Blue's helm

Longtime executive Arvind Krishna will replace IBM CEO Ginni Rometty and Red Hat CEO Jim Whitehurst has been named IBM president. Analysts expect them to make AI acquisitions.

AI infrastructure Get Started

Bring yourself up to speed with our introductory content

Ignoring infrastructure leads to major challenges for AI adoption

While companies are stuck in the research phase of AI, a few simple infrastructure analyzations can jumpstart the process -- and ensure successful deployment. Continue Reading
How to build a neural network from the ground floor

Deep learning is powering the development of AI. To build your own neural network, start by understanding the basics: how neural networks learn, correlate and stack with data. Continue Reading
3 in-demand AI skills that boost data scientists' development

AI encompasses a wide range of disciplines, from advanced math to application development, and building a strong AI team starts with incredibly skilled data scientists. Continue Reading

Evaluate AI infrastructure Vendors & Products

Weigh the pros and cons of technologies, products and projects you are considering.

Standards for data sharing should guide AI government regulation

The White House has taken a deregulatory approach to AI and aims to inspire innovation. An expert weighs in on the role of government in AI and where the industry stands. Continue Reading
Why the future of AI storage may have to exclude flash

Discover why large, high-node count and hard disk-only scale-out storage architectures address the ever-growing capacity demands and challenges of AI architectures and workloads. Continue Reading
Where are we with machine translation in AI?

Machine translation has received a boost from cutting-edge technology like deep learning but continues to struggle with the complexities and nuances of human languages. Continue Reading

Manage AI infrastructure

Learn to apply best practices and optimize your operations.

Merging DevOps and machine learning requires restructuring

Companies that are restructuring in order to merge their traditional DevOps teams with their machine learning efforts to aid with accessibility need to include voices from multiple teams. Continue Reading
The rising use of AI in the energy sector

The energy industry has begun to ramp up the adoption of AI with the usage of smart grids among other technologies and has seen the benefits of the technology. Continue Reading
The complex nature of regulating AI

Regulating AI is a difficult task because the technology changes rapidly. Governments must be able to employ preventative regulation to prevent any misuse. Continue Reading

Problem Solve AI infrastructure Issues

We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.

How to create a data set for machine learning with limited data

A shortage of data for machine learning training sets can halt a company's AI development in its tracks. Turning to external sources and hidden data can solve the problem. Continue Reading
Serverless machine learning reduces development burdens

Getting started with machine learning throws multiple hurdles at enterprises. But the serverless computing trend, when applied to machine learning, can help remove some barriers. Continue Reading
Experts discuss pressing data science problems and solutions

Most data science projects end up facing similar problems, such as lack of robustness and data quality issues. In this feature, experts offer tips on how to overcome these challenges. Continue Reading