Building a successful AI infrastructure strategy starts with IBM
Whether it’s apps, purpose-built hardware for AI server workloads, or AI- or cloud-based services to support your cognitive business, IBM gives you the hardware and capabilities to get the job done.
Reimagine infrastructure for the AI era
With the right processor architecture and server hardware, you’ll unlock the fastest deployment for accelerated databases and deep learning frameworks, all backed by enterprise-class software and services support.
Revolutionize analytics and capture insights in real time. Machine learning on IBM Z® makes transactional, operational and social data available instantly, allowing you to extract its hidden value and pivot quickly.
Discover the key to data science productivity. Learn how IBM Storage for AI delivers pipeline optimization and superior performance to improve data governance and accelerate time to actionable insights.
Applications built with machine learning and deep learning push system demands. To crunch volumes of data at the speed AI requires, you need massive processing power, high throughput, and GPU acceleration.
Gain real-time insight without moving data
Machine learning allows computers to learn without explicit programming. IBM z14 can use machine learning for real time analytics of system data right on your mainframe.
of companies expect AI will impact customers’ perceptions of their brands
of companies report AI is an opportunity, not a threat
Build your competitive advantage with AI software and learning frameworks
IBM provides complete AI software platforms and industry-specific deep learning frameworks for fast access and insights. You’ll find the software you need to optimize AI workloads across the AI IT infrastructure environments of your choice.
Unlock the value of your data
Watson™ on IBM Cloud allows you to integrate the world’s most powerful AI into your application, and store, train and manage your data in the most secure cloud.
Developing AI programs to master chess drove AI progress. However, research in such “clean” game domains did not really address most real-life tasks—which is why IBM has kept pushing the deep learning required to solve business issues