The focus of artificial-intelligence spending has gone from training models to using them. Here’s how to understand the difference—and the implications.
Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. Inferences, love them or hate them. You decide. One thing that ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More California-based MosaicML, a provider of generative AI infrastructure, ...
Inference is rapidly emerging as the next major frontier in artificial intelligence (AI). Historically, the AI development and deployment focus has been overwhelmingly on training with approximately ...
Artificial intelligence startup Runware Ltd. wants to make high-performance inference accessible to every company and application developer after raising $50 million in Series A funding. It’s backed ...
Ambitious artificial intelligence computing startup Cerebras Systems Inc. is raising the stakes in its battle against Nvidia Corp., launching what it says is the world’s fastest AI inference service, ...
Kubernetes has become the leading platform for deploying cloud-native applications and microservices, backed by an extensive community and comprehensive feature set for managing distributed systems.
In my day-to-day work, I have spent countless hours optimizing model performance, only to confront a sobering reality: In 2026, the primary barrier to widespread AI adoption has shifted. While raw ...
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