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.

February 24, 2021 24 Feb'21
Robotics company Berkshire Grey will go public

Berkshire Grey is the latest AI firm to go public, after the robotics vendor said it will merge with a special-purpose acquisition company. The move comes amid a surge in AI IPOs.
February 19, 2021 19 Feb'21
CTO on the need for AI ethics and diversity

A CTO talks about the importance of diverse data sets when creating AI models and how a lack of diversity can create bias in systems.
February 19, 2021 19 Feb'21
Nvidia opens paid, instructor-led AI workshops to the public

While many technology vendors offer online courses on how to use their AI products, it still might not be enough to educate the global workforce.
February 17, 2021 17 Feb'21
AI deployed as employee burnout detection tool

Employee burnout is one of the mental health issues that AI tools are helping HR to identify. The technology can analyze employee activities and communications for potential risk.

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.

Businesses pivot back to AI adoption after year of slow growth

AI adoption has taken a step back when it comes to enterprise IT spending priority, but it remains a steady investment for enterprises across industries. 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
How AI adoption by industry is being impacted by COVID-19

While COVID-19 has impacted budgets and businesses plans, some industries are seeing improved processes and consumer relationships due to new investments in AI and automation. Continue Reading

Learn to apply best practices and optimize your operations.

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
Data democratization strategy for machine learning enterprise

In the enterprise, data democratization works to break down data silos by opening access to an organization's data across teams in an effort to improve workflows. Continue Reading
Building trustworthy AI is key for enterprises

Organizations need to focus on transparency in models, ethical procedures and responsible AI in order to best comply with guidelines for developing trustworthy AI systems. 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