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

October 21, 2020 21 Oct'20
IBM cloud revenues climb as hardware continues to decline

IBM cloud revenues continue to increase as hardware sales drop, sharpening the company's strategy to focus on hybrid cloud.
October 08, 2020 08 Oct'20
Nvidia Jarvis, new conversational AI tool, now in open beta

A speech recognition services vendor in Great Britain turned to Nvidia Jarvis, a new framework for creating conversational AI models on GPUs, to quickly build a product.
October 08, 2020 08 Oct'20
Nvidia adds DPUs to GPU lineup for artificial intelligence apps

Nvidia has rolled out a new chip technology that supplements its GPUs, along with a new development kit and architecture to create more capable AI-based applications.
September 25, 2020 25 Sep'20
Google, Unilever partnership uses AI for sustainable sourcing

Unilever says it will use Google Earth Engine, Google Cloud Storage and BigQuery, as well as AI technologies, to create a deforestation-free supply chain by 2023.

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.

Combining AI and predictive analytics crucial for the enterprise

Predictive analytics, when combined with artificial intelligence, can assist organizations with their risk management, as well as their planning and optimization. Continue Reading
Machine learning limitations marked by data demands

Machine learning has impressive capabilities in the enterprise, but with high-data requirements and struggles with explainability, it remains unable to reach widespread use. Continue Reading
In-depth guide to machine learning in the enterprise

Enterprises are adopting machine learning technologies at rapid rates. In this machine learning guide, we break down what you need to know about this transformative technology. Continue Reading

Manage AI infrastructure

Learn to apply best practices and optimize your operations.

AIoT applications prove the technology's adaptability

The combination of artificial intelligence and IoT has led to better predictive capabilities for devices, informed data storage, and enterprise machine optimization. Continue Reading
Find out how smart you are about machine learning and AI

Machine learning can help businesses gain powerful analytics value from their data -- but only if it's done right. How much do you know about machine learning and related forms of AI? Continue Reading
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. 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.

Expanding explainable AI examples key for the industry

Improving AI explainability and interpretability is key to the continued building of trust with consumers and the continued success of the technology. Continue Reading
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