Blog archive, page 4

With the increased adoption of cloud computing and demand for managed applications and services, we are now able to offer a new choice of Software as a service (SaaS) deployment model for customers who need it. Let’s explore the organizational components that influence whether SaaS is the right choice for your organization when it comes to data science and MLOps.

If you are involved in work in the data science field, you may have heard about feature stores. This post will provide a basic overview of what feature stores are (For a deeper discussion, look here). Then, we will cover the problems they solve and how they work. Domino now incorporates a feature store into its platform. Finally, we will briefly introduce how you can use it. So let's get started!

We believe the companies that will soar above the rest and address the world’s challenges are those that put data science at the heart of their business. 76% of of U.S. data executives agree with us, making AI-led value generation one of their top three priorities in 2023.

OpenAI demonstrated the profound impact generative AI could have. Such techniques turn datasets into transformative tools and products. Tangible AI projects that are both inspiring and can save your company time and money. Better yet, you are in a good position to aim high.

In today's economic environment, all organizations need to unlock greater AI value, faster. 98% of CDOs and CDAOs say the companies that bring AI and ML solutions to market fastest will be the ones who survive and thrive in the upcoming times of economic uncertainty. More than ever, organizations need to scale the creation and operationalization of ML models across their businesses and bring to bear the latest, most powerful AI methods and tools.

Generative AI has captured the public imagination, with ChatGPT contextualizing the benefits of AI for more people than ever before. OpenAI reportedly used 10,000 NVIDIA GPUs to train ChatGPT, and NVIDIA owns 88% of the GPU market powering model training.