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.
Download: Free AI Buyer's Guide
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.
AI infrastructure News
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December 20, 2019
20
Dec'19
AI vendors to watch in 2020 and beyond
The past 10 years have seen a surge of new AI vendors, and the trend isn't likely to end anytime soon, as investors continue to pour money into artificial intelligence.
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December 16, 2019
16
Dec'19
Intel acquisition of Habana Labs expected to enhance AI portfolio
By purchasing Habana Labs, an AI hardware startup, Intel now has a more diverse AI portfolio in a quickly growing multi-billion-dollar hardware market.
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December 12, 2019
12
Dec'19
AI trends 2020 outlook: More automation, explainability
Top AI trends for 2020 are increased automation to extend traditional RPA, deeper explainable AI with more natural language capacity, and better chips for AI on the edge.
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December 03, 2019
03
Dec'19
SageMaker Studio makes model building, monitoring easier
New SageMaker tools from AWS to open up machine learning models by making it easier for non-expert developers make, run, monitor and debug machine learning models.
AI infrastructure Get Started
Bring yourself up to speed with our introductory content
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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
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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
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How to develop a successful, modern AI infrastructure
Before AI can revolutionize business processes or decision-making, companies need a strong foundation. These tools, platforms and applications help enterprises get started with AI. Continue Reading
Evaluate AI infrastructure Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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How GE uses a 'Humble AI' approach to manufacturing
GE executive Colin Parris explains why a deliberate approach to deploying AI is needed when dealing with products that cost hundreds of millions of dollars to make. Continue Reading
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AI-driven development trends shake up the cloud market
Enterprises are increasingly interested in AI, and cloud vendors are in a race to adapt their platforms to meet those needs. See what initiatives are underway to meet the next wave of app development. Continue Reading
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3 intelligent process automation use cases and how they work
Enterprises are pursuing intelligent process automation to take their digital transformation and RPA applications to the next level. Here's a look at three use cases. Continue Reading
Manage AI infrastructure
Learn to apply best practices and optimize your operations.
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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
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AI in networking helps keep systems running
Network administrators are increasingly using AI tools to help them manage the growing complexity of their network infrastructure, a task that's getting more complicated by the day. Continue Reading
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AI and climate change: The mixed impact of machine learning
While AI can play a role in helping researchers and conservationists address the impacts of climate change, it can also contribute to carbon emissions, making it a mixed blessing. 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.
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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
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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
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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