Artificial intelligence platforms

Whether you've only just begun to evaluate artificial intelligence platforms or have already invested in AI tools such as machine learning, it's important to be aware of what's available in the market. Find valuable insights into how to make enterprise AI software and device decisions and how to integrate those AI tools into your existing IT infrastructure.

June 30, 2022 30 Jun'22
Siemens forges digital twin deal with Nvidia for metaverse

The industrial powerhouse partners with AI hardware/software vendor Nvidia on digital twins, a metaverse technology increasingly used in industrial and manufacturing settings.
May 26, 2022 26 May'22
Tech stock sell-off signals tough times for data vendors

In addition to lowering the values of publicly traded data, analytics and AI vendors, the stock market's decline is making it difficult for companies still in their funding phase.
May 25, 2022 25 May'22
Microsoft invites access to Azure OpenAI Service, GPT-3

Microsoft has invited corporate developers to apply for access to its cloud-based AI model for natural language processing. The service was invitation only.
May 05, 2022 05 May'22
Domino Data Lab releases latest MLOps platform update

Domino 5.2 includes new features for data scientists to find the best model development environment and use Snowflake by automating model deployment to Snowflake's Data Cloud.

Bring yourself up to speed with our introductory content

conversational AI

Conversational AI is a type of artificial intelligence that enables consumers to interact with computer applications the way they would with other humans. Continue Reading
The expanding universe of enterprise accounting software

Enterprises of all sizes are finding today's accounting software accurately and reliably automates payables and receivables, while AI derives intelligence from numbers. Continue Reading
9 top business process modeling techniques with examples

Business process modeling techniques and tools provide a visual representation critical to monitoring, improving and streamlining the flow of tasks along numerous processes. Continue Reading

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

6 top business process management benefits, advantages

Streamlined workflows, greater agility and scalability, tighter process controls, reduced risks, lower costs and better customer engagements are among the notable BPM benefits. Continue Reading
Interpretability and explainability can lead to more reliable ML

Interpretability and explainability as machine learning concepts make algorithms more trustworthy and reliable. Author Serg Masís assesses their practical value in this Q&A. Continue Reading
What is data science? The ultimate guide

Data science is the process of using advanced analytics techniques and scientific principles to analyze data and extract valuable information for business decision-making, strategic planning and other uses. Continue Reading

Learn to apply best practices and optimize your operations.

RPA vs. BPM: How are they different?

Don't confuse RPA with BPM. These process-oriented initiatives are distinctly different yet highly complementary when planning, automating and improving key business operations. Continue Reading
Enterprise hybrid AI use is poised to grow

Hybrid AI is an approach for businesses that combines human insight with machine learning and deep learning networks. Despite certain challenges, experts believe it shows promise. Continue Reading
Automated machine learning improves project efficiency

Until recently, machine learning projects had a small chance of success given the amount of time they require. Automated machine learning software speeds up the process. Continue Reading

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

7 business process management challenges and how to fix them

On the road to a successful BPM initiative, missing C-level support, unclear goals, cultural change and poor testing environments are among the roadblocks that can be overcome. Continue Reading
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
Combating racial bias in AI

By employing a diverse team to work on AI models, using large, diverse training sets, and keeping a sharp eye out, enterprises can root out bias in their AI models. Continue Reading