AI business strategies

Artificial intelligence software is changing how enterprises conduct business. Machine learning supports data-driven decisions, customer service chatbots follow up on leads, robots in manufacturing boost productivity -- the list goes on. Get advice for building and implementing AI business strategies.

May 14, 2021 14 May'21
Biden sets stage for national AI strategy

Biden's focus on AI includes funding research and development, manufacturing chips in the U.S. and preparing a workforce to use AI tools.
May 11, 2021 11 May'21
DataRobot looks to enterprise AI coders with Zepl acquisition

By acquiring cloud data science and analytics platform vendor Zepl, DataRobot gives data scientists a cloud-native, self-service notebook to write tasks and custom models.
May 11, 2021 11 May'21
IBM hangs its hopes on hybrid clouds, AI to revive growth

After a decade of stagnant growth, IBM is betting all of its chips that hybrid clouds, new partnerships and AI will catapult it to a more competitive position.
April 21, 2021 21 Apr'21
IBM Watson updates focus on data privacy and explainability

Updates include new federated learning capabilities within IBM Watson Studio and more insights into how predictions are made in IBM Planning Analytics with Watson.

Bring yourself up to speed with our introductory content

5 examples of effective NLP in customer service

Through use cases such as chatbots, recommendation systems and customer relationship management, NLP and AI are playing an important role in enterprise customer service. Continue Reading
Do you have competitive data science key skills?

Data scientists should be familiar with a variety of programming languages, machine learning algorithms and databases and must be able to communicate these skills across teams. Continue Reading
responsible AI

Responsible AI is a governance framework that documents how a specific organization is addressing the challenges around artificial intelligence (AI) from both an ethical and legal point of view. Resolving ambiguity for where responsibility lies if ... Continue Reading

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

The future of data science jobs

The title of data scientist may soon become obsolete, as new technologies change the responsibilities of data scientists. It may also soon change the nature of the job. 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
Supervised vs. unsupervised learning: Use in business

Learn how LinkedIn, Zillow and others choose between supervised learning, unsupervised learning and semi-supervised learning for their machine learning projects. Continue Reading

Learn to apply best practices and optimize your operations.

How to hire data scientists

Enterprises tend to want data scientists who have a drive to continue their training, through peer training or online platforms, to keep up with ongoing changes in the field. Continue Reading
How to detect bias in existing AI algorithms

While enterprises can't eliminate bias from their data, they can significantly reduce bias by establishing a governance framework and employing more diverse employees. Continue Reading
Tackling the AI bias problem at the origin: Training data

Though data bias may seem like a back-end issue, the enterprise implications of an AI software using biased data can derail model implementation. Continue Reading

We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.

9 data quality issues that can sideline AI projects

The quality of your data affects how well your AI and machine learning models will operate. Getting ahead of these nine data issues will poise organizations for successful AI models. Continue Reading
How to avoid overfitting in machine learning models

Overfitting remains a common model error, but data scientists can combat the problem through automated machine learning, improving AI literacy and creating test data sets. Continue Reading
AI security concerns keeping infosec leaders up at night

Conversations about 'AI as a solution' may overlook potentially grave AI security issues. Explore the potential infosec implications of the emerging technology in this video. Continue Reading