# Cloud APIs

Published articles for Cloud APIs.

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## NVIDIA Vera Storage Benchmarks: Faster Encryption, Compression, Integrity Checking, and Recovery for AI-Native Storage

DevFeed: [NVIDIA Vera Storage Benchmarks: Faster Encryption, Compression, Integrity Checking, and Recovery for AI-Native Storage](<https://devfeed.tech/articles/nvidia-vera-storage-benchmarks-faster-encryption-compression-integrity-checking-and-recovery-for-ai-native-storage-6914.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/nvidia-vera-storage-benchmarks-faster-encryption-compression-integrity-checking-and-recovery-for-ai-native-storage/>)

Author: Elizabeth Goodman

Published: 2026-08-03T16:00:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [Encryption](<https://devfeed.tech/topics/encryption.md>), [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [Security](<https://devfeed.tech/topics/security.md>), [Resilience](<https://devfeed.tech/topics/resilience.md>), [systems](<https://devfeed.tech/topics/systems.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [bluefield-dpu](<https://devfeed.tech/tags/bluefield-dpu.md>), [cloud-apis](<https://devfeed.tech/tags/cloud-apis.md>), [cloud-networking](<https://devfeed.tech/tags/cloud-networking.md>), [cloud-services](<https://devfeed.tech/tags/cloud-services.md>), [compression](<https://devfeed.tech/tags/compression.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [doca](<https://devfeed.tech/tags/doca.md>), [encryption](<https://devfeed.tech/tags/encryption.md>), [featured](<https://devfeed.tech/tags/featured.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [networking-communications](<https://devfeed.tech/tags/networking-communications.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [performance](<https://devfeed.tech/tags/performance.md>), [security](<https://devfeed.tech/tags/security.md>), [software-defined-data-center](<https://devfeed.tech/tags/software-defined-data-center.md>), [storage](<https://devfeed.tech/tags/storage.md>), [systems](<https://devfeed.tech/tags/systems.md>), [top-stories](<https://devfeed.tech/tags/top-stories.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>), [vera-rubin-nvl72](<https://devfeed.tech/tags/vera-rubin-nvl72.md>)

### AI overview

NVIDIA presents benchmark results for the Vera BlueField-4 STX Storage Processor in AI-native storage workloads. The results describe faster encryption and decryption, recovery, integrity checking, compression and decompression, and multi-stage storage processing than an x86 CPU, with lower CPU and power overhead.

### Source excerpt

Storage is an active part of every agentic AI workflow. As agents retrieve enterprise knowledge, access persistent memory, reuse key-value (KV) cache data,...

## See how ML Kit and ARKit play together

DevFeed: [See how ML Kit and ARKit play together](<https://devfeed.tech/articles/see-how-ml-kit-and-arkit-play-together-16302.md>)

Original publisher: [Read original article](<https://firebase.blog/posts/2018/12/see-how-ml-kit-and-arkit-play-together>)

Author: Ibrahim Ulukaya

Published: 2018-12-17T00:00:00Z

Content type: tutorial

Language: en

Sources: [Firebase Blog](<https://devfeed.tech/sources/firebase-blog.md>)

Topics: [ML Kit](<https://devfeed.tech/topics/ml-kit.md>), [Firebase](<https://devfeed.tech/topics/firebase.md>), [iOS](<https://devfeed.tech/topics/ios.md>), [Mobile](<https://devfeed.tech/topics/mobile.md>), [Cloud APIs](<https://devfeed.tech/topics/cloud-apis.md>), [object-detection](<https://devfeed.tech/topics/object-detection.md>)

Tags: [android](<https://devfeed.tech/tags/android.md>), [api](<https://devfeed.tech/tags/api.md>), [apple](<https://devfeed.tech/tags/apple.md>), [arkit](<https://devfeed.tech/tags/arkit.md>), [cloud-apis](<https://devfeed.tech/tags/cloud-apis.md>), [firebase](<https://devfeed.tech/tags/firebase.md>), [image](<https://devfeed.tech/tags/image.md>), [ios](<https://devfeed.tech/tags/ios.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [ml-kit](<https://devfeed.tech/tags/ml-kit.md>)

### AI overview

This tutorial explains how to combine ML Kit and ARKit in an iOS project. It describes processing camera frames with ML Kit image labeling, using on-device results for responsiveness and cloud-based labeling for higher accuracy, then displaying the detected label in a 3D scene.

### Source excerpt

News, tutorials, and updates from the Firebase team.

## Introducing ML Kit for Firebase

DevFeed: [Introducing ML Kit for Firebase](<https://devfeed.tech/articles/introducing-ml-kit-for-firebase-16268.md>)

Original publisher: [Read original article](<https://firebase.blog/posts/2018/05/introducing-ml-kit-for-firebase>)

Author: Sachin Kotwani

Published: 2018-05-10T00:00:00Z

Content type: release

Language: en

Sources: [Firebase Blog](<https://devfeed.tech/sources/firebase-blog.md>)

Topics: [Firebase](<https://devfeed.tech/topics/firebase.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [SDKs](<https://devfeed.tech/topics/sdks.md>), [Mobile](<https://devfeed.tech/topics/mobile.md>), [Android](<https://devfeed.tech/topics/android.md>), [iOS](<https://devfeed.tech/topics/ios.md>), [Cloud APIs](<https://devfeed.tech/topics/cloud-apis.md>), [Google](<https://devfeed.tech/topics/google.md>)

Tags: [android](<https://devfeed.tech/tags/android.md>), [api](<https://devfeed.tech/tags/api.md>), [apis](<https://devfeed.tech/tags/apis.md>), [cloud-apis](<https://devfeed.tech/tags/cloud-apis.md>), [firebase](<https://devfeed.tech/tags/firebase.md>), [google](<https://devfeed.tech/tags/google.md>), [google-i-o](<https://devfeed.tech/tags/google-i-o.md>), [ios](<https://devfeed.tech/tags/ios.md>), [launch](<https://devfeed.tech/tags/launch.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [ml](<https://devfeed.tech/tags/ml.md>), [ml-kit](<https://devfeed.tech/tags/ml-kit.md>), [mobile](<https://devfeed.tech/tags/mobile.md>), [news](<https://devfeed.tech/tags/news.md>), [updates](<https://devfeed.tech/tags/updates.md>)

### AI overview

Firebase introduces ML Kit in beta, an SDK that helps Android and iOS developers add machine-learning features without requiring extensive machine-learning expertise. It includes ready-to-use APIs for text recognition, face detection, barcode scanning, image labeling, and landmark recognition, with both on-device and cloud-based options.

### Source excerpt

News, tutorials, and updates from the Firebase team.