Applied Materials vs Hewlett Packard Enterprise

Fab software that uses machine learning to predict metrology measurement values in real time with confidence scores, reducing reliance on physical measurement and auto-retraining models when drift is detected.

Software that augments existing run-to-run process control with machine learning models that recommend recipe parameter adjustments for high-mix, low-volume and nonlinear processes.

AI-based fab software that automatically detects and classifies wafer inspection images into more than 100 defect categories, replacing manual and rule-based defect review.

Applied's Actionable Insight Accelerator platform, which combines chamber sensors, inline metrology, digital twins and machine learning algorithms to optimise semiconductor process recipes from millions of wafer and chip measurements.

Data and model management platform that covers the full AI/ML lifecycle for fabs, from data preparation and model building through deployment and drift monitoring, without requiring coding expertise.

Brightfield optical wafer inspection system whose third-generation ExtractAI technology pairs its scan data with SEMVision eBeam review to separate yield-killing defects from millions of nuisance signals.

Integrated die-to-wafer hybrid bonding system for HBM, AI accelerators and co-packaged optics, with an AIx-powered software suite providing predictive maintenance, die-level traceability and multi-binning.

Cold field emission eBeam defect review system that integrates deep learning AI to automatically extract and classify yield-killing defects from wafer inspection data.

Modular wafer-processing platform holding four to twelve mixed ALD, CVD, epitaxy and etch chambers, instrumented with thousands of sensors that feed Applied's AIx software for machine-learning recipe acceleration.

Cloud-native network management and AIOps for HPE Aruba Networking wired, wireless and SD-WAN devices, with AI-driven insights, self-driving automation and a GreenLake copilot, deployable as a cloud service, on-premises, as-a-service or in a virtual private cloud.

AI network assistant that answers network questions in natural language and, when permitted, resolves WLAN, LAN, WAN and data-centre issues autonomously.

Hybrid cloud observability and AIOps software that unifies monitoring of on-premises, multicloud and AI workloads, uses an AI-powered Operations Copilot to cut alert noise and guide resolution, and automates routine fixes.

Cloud AI-native networking platform from Juniper (now HPE) that applies AI models to network telemetry for proactive insights, recommendations and automated resolutions across wireless, wired and WAN, with the Marvis AI assistant on top.

An agentic AIOps system HPE sells to its GreenLake subscription customers to automate and operate IT/network infrastructure.

8-GPU air-cooled server with NVIDIA Blackwell Ultra (B300 HGX) accelerators for large AI model training, tuning and inferencing, part of NVIDIA AI Computing by HPE.

4U rack server for AI inference supporting up to ten double-wide NVIDIA GPUs and Intel Xeon 6 processors.

Rack server for generative AI workloads with up to two NVIDIA GH200 NVL2 superchips, used to train and deploy larger AI models and as a building block of HPE Private Cloud AI.

10U rack server for production AI with two AMD EPYC 9006 processors and up to eight double-wide GPUs, for inference, RAG and agentic AI workloads.

8-GPU server for large AI model training with a choice of NVIDIA or AMD Instinct accelerators and AMD EPYC 9005 processors.