Published: 22 May 2023
Summary
Cloud AI developer services enable developers to build intelligent applications by using AI models out of the box, fine-tuning them or creating custom models. Software engineering leaders should use this research to guide their teams in choosing services that will deliver the most business value.
Included in Full Research
Overview
Key Findings
Cloud AI developer services (CAIDS) vendors are developing a family of large language models that can deliver a range of general-purpose and domain-specific language capabilities. Vendors are offering proprietary models, models sourced from trusted partners and open-source models.
Nearly every vendor has improved its image and video understanding capabilities, with 10 of the 11 vendors receiving a score of three or higher for the vision services use case.
Smaller vendors continue to lead innovation of automatic machine learning (autoML) capabilities, but large vendors are catching up. Their autoML capabilities enable software engineers to rapidly develop, deploy and maintain models in
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Strategic Planning Assumptions
- Alibaba Cloud
- Amazon Web Services
- Baidu
- Clarifai
- Google
- H2O.ai
- Huawei Cloud
- IBM
- Microsoft
- Oracle
- Tencent
- Speech to Text
- Language Understanding/Processing
- Natural Language Generation/TTS
- Translation
- Sentiment Analysis
- Text Analytics
- Image Recognition/Labeling
- Image Generation
- Video AI
- ML Enabled OCR
- Automated Data Preparation
- Responsible AI
- Feature Engineering
- Automated Model Building
- Model Management/Operationalization
- Language
- Vision
- AutoML
Gartner Recommended Reading
Critical Capabilities Methodology