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

May 29, 2020 29 May'20
Enterprises should not neglect AI digital transformation

Enterprises should focus on automation to augment their workforces as they recover from the COVID-19 economic downturn, and not lose sight of larger digital transformation projects.
May 20, 2020 20 May'20
Microsoft supercomputer looks to create AI models in Azure

Microsoft has expanded its AI initiative up to the supercomputer market, unveiling a system focused on helping users build large AI models that work with its Azure cloud platform.
May 15, 2020 15 May'20
IBM Think 2020: AI, security, COVID-19 news, trends and analysis

News at the IBM Think 2020 digital conference focused on paths to modernization -- including advanced AI and automation -- IoT, hybrid cloud infrastructure and cybersecurity.
May 14, 2020 14 May'20
Nvidia unveils A100 GPU for demanding AI workloads

Designed for demanding AI and data science workloads, Nvidia's new A100 processor is a powerhouse, but it's also power-hungry and high-heat-producing.

AI infrastructure Get Started

Bring yourself up to speed with our introductory content

Use of AI-assisted surgery remains limited despite its benefits

While AI adoption to assist with surgeries remains limited, the technology holds great potential to increase quality of care and decrease patient risk. Continue Reading
artificial intelligence

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. Continue Reading
4 main types of AI explained

The emergence of artificial superintelligence will change humanity, but it's not happening soon. Here are the types of AI leading up to that new reality. Continue Reading

Evaluate AI infrastructure Vendors & Products

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

Cloud computing for machine learning offers on-demand tools

Automated machine learning and MLaaS tools are now being developed for the cloud, and enterprises need better workflows and infrastructure to successfully integrate the technology. Continue Reading
AI document processing remains a subtle but powerful use case

Artificial intelligence has found strong use cases in content summarization and document categorization within the medical, marketing and legal fields. Continue Reading
Ultimate guide to artificial intelligence in the enterprise

AI in the enterprise will change how work is done, but companies must overcome several challenges to derive value from this powerful and rapidly evolving technology. Continue Reading

Manage AI infrastructure

Learn to apply best practices and optimize your operations.

Are giant AI chips the future of AI hardware?

Giant AI chips like the Cerebras WSE are dazzlingly fast and could transform AI models, but how soon is the question for CIOs. Experts mull the merits of small vs. big AI chips. Continue Reading
How to create NLP metrics to improve your enterprise model

As standardized NLP framework evaluations become popular, experts urge users to focus on individualized metrics for enterprise success. Continue Reading
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

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