About This Constellation ShortList™
Artificial intelligence (AI) platforms enable organizations and individuals to build intelligent applications based on data. AI platforms must provide the facilities to ingest complex data, address rapidly generated or constantly evolving data, rectify and amplify hard-to-find signals, craft models where human-powered analytics are slow, enable resolution for highly iterative models, decrease the time to generate models and improve accuracy rates.
Seven key components for AI success include the ability to handle large amounts of complex data, deliver massive compute power, compress time, provide math talent, embody domain expertise, leverage human user experience and support contextual decisions.
The end goal of AI platforms is to provide the infrastructure to support contextual decisions. These contextual decisions power an array of AI-driven smart services required to deliver next best action across a range of business processes.
Constellation considers the following key criteria for these solutions:
- Provides cloud-based scalable computing infrastructure
- Offers compute power acceleration
- Delivers advanced natural language processing (NLP)
- Furnishes microservices and application programming interface (API)-driven access to algorithm libraries and services
- Addresses classification
- Supports automation of processes
- Supplies supervised and unsupervised learning
- Facilitates machine learning interpretability
- Enables automatic visualization
- Detects anomalies
- Facilitates a tool kit or low-code algorithm creation
- Provides recommendations, rankings, and data labeling
- Supports ML Ops pipelines
The Constellation ShortList™
Constellation evaluates more than 10 solutions categorized in this market. This Constellation ShortListis determined by client inquiries, partner conversations, customer references, vendor selection projects, market share and internal research.
- Alibaba Cloud Machine Learning Platform for AI
- Amazon Machine Learning Services
- Google AI
- IBM Watson Studio
- Microsoft Azure Machine Learning Studio
- SAS Machine Learning
Frequency of Evaluation
Each Constellation ShortList will be updated at least once per year. There could be an update after six months, should the analyst deem it necessary.
Constellation clients may work with the analyst and research team to conduct a more thorough discussion of this ShortList. Constellation can also provide guidance in vendor selection and contract negotiation.