AI infrastructure

Enterprises investing in deep learning platforms need AI infrastructure sufficient enough to synthesize a massive amount of data. 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.

August 02, 2022 02 Aug'22
UiPath acquires NLP vendor in effort to expand beyond RPA

The vendor's acquisition aligns with its strategy of expanding beyond its robotic process automation footprint to try to compete more effectively with tech giants.
July 14, 2022 14 Jul'22
AI21 secures $64M in funding as NLP market grows

AI21 Labs is now worth $664 million. Its growth shows the demand for more language models and tools despite the dominance of models like OpenAI's GPT-3, GPT-J and GPT-Neo.
May 10, 2022 10 May'22
IBM Think 2022 news, trends and analysis

AI adoption is driving advancement of cybersecurity and other business processes. At IBM Think 2022, enterprise leaders will learn how to capitalize on game-changing technologies.
May 04, 2022 04 May'22
TeamViewer's AiStudio: AI is the next evolution for AR

Frontline's new add-on enables enterprises to train models for image and object recognition. The system can detect shop floor warning signs and other safety problems.

Bring yourself up to speed with our introductory content

What an AI-driven network looks like

Log analysis and wireless management are common AI use cases in networking. Future applications could include chatbot alerts, digital experience monitoring and traffic engineering. Continue Reading
scientific method

The scientific method is the process of objectively establishing facts through testing and experimentation. Continue Reading
Why NetOps is a bridge to AIOps

As IT infrastructure grows more complex, NetOps teams should identify ways to ensure their networks remain operational and perform at peak levels. One option is AIOps. Continue Reading

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

10 top AI and machine learning trends for 2022

Tiny ML, multi-modal learning, responsible AI -- learn about the top trends in AI for 2022 and how they promise to transform how business gets done. Continue Reading
What's the status of AI in networking?

The use cases for AI are expanding, but despite the advantages, network pros have yet to implement AI fully. Three analysts explain the status of AI in enterprise networks. Continue Reading
How cloud RPA is key to automation's future

Companies have traditionally used robotic process automation (RPA) as on-premises software but are now embracing cloud RPA as its business benefits are outweighing the drawbacks. Continue Reading

Learn to apply best practices and optimize your operations.

How AI and automation play a role in ITOps

Tech professionals agree that AI, intelligent automation and cybersecurity play important roles in the enterprise and can revolutionize ITOps when implemented and used correctly. Continue Reading
Use an AI governance framework to surmount challenges

As AI governance adapts to the rapidly expanding field of AI, businesses need a holistic framework to surmount challenges with clearly defined roles and responsibilities. Continue Reading
Piloting machine learning projects through harsh headwinds

To get machine learning projects off the ground and speed deployments, data science teams need to ask questions on a host of issues ranging from data quality to product selection. Continue Reading

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 are keys to building consumer trust and furthering the technology's success. Continue Reading
Addressing 3 infrastructure issues that challenge AI adoption

One of the biggest problems enterprises run into when adopting AI infrastructure is using a development lifecycle that doesn't work when building and deploying AI models. 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