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.

January 13, 2021 13 Jan'21
The power and limitations of enterprise AI

A panel at CES 2021, held virtually this year, discusses the areas in which modern-day AI and automation shine, and where they still struggle.
January 06, 2021 06 Jan'21
Intel launches RealSense ID for facial authentication

Amid a surge of facial recognition technology systems from vendors, Intel introduces RealSense ID, a system that Intel claims can accurately and quickly identify human faces.
December 18, 2020 18 Dec'20
AWS digs into its new machine learning industrial products

Amazon Monitron and Lookout for Equipment use sensor data to help industrial customers predict when their machines will break. Amazon's GM of machine learning and AI explains.
December 17, 2020 17 Dec'20
Emerging AI startups to look at in 2021

AI startups in the legal, MLOps, NLP and data training markets make this year's list of emerging AI vendors to look out for.

Bring yourself up to speed with our introductory content

artificial intelligence

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. Continue Reading
Understanding motion analytics, where it is and where it's going

Machine learning is helping make motion analysis more usable for the average enterprise, creating new use cases and applications that can drive value. Continue Reading
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

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

Defining enterprise AI: From ETL to modern AI infrastructure

The promise of enterprise AI is built on old ETL technologies, and it relies on an AI infrastructure effectively integrating and processing loads of data. Continue Reading
KDD in data mining assists data prep for machine learning

While data scientists are often familiar with data mining, the deeper knowledge discovery in databases (KDD) procedure can help prepare data to train machine learning algorithms. Continue Reading
AI trends in 2020 marked by expectation shift and GPT-3

In the past year, AI hyperscalers got serious about their machine learning platforms, expectations were reset and transformer networks empowered the GPT-3 language model. Continue Reading

Learn to apply best practices and optimize your operations.

Finding the balance between edge AI vs. cloud AI

Centralized cloud resources allow AI to continuously improve while edge AI allows for real-time decision-making and larger models. The best approach combines them. Continue Reading
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

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