The Machine Learning Market is Alive
Machine learning is nothing new, as it turns out. The underlying concepts and foundational technology have existed in various forms for many years. The difference is that we are interacting with AI in our daily lives at rapidly increasing rates.
For those of us in digital marketing arena this is an exciting prospect shrouded in mystery. Google’s important algorithm updates are becoming less distinct, less noticeable, and harder to quantify. While this means we are trying to hit a target that is moving faster than ever it also makes it more difficult to game the system, and creates a far better experience for users.
Amazon Web Services (AWS) is growing asset for Amazon powering their web presence and as a separate business open to public for many online services from including Computing, Storage & Content Delivery, Database, Networking and Analytics, Enterprise Applications, Mobile Services, Developer Tools, Management Tools, Security and Identity, Application Services, Game Development and Software. Part of their Analytics services is Machine Learning (ML) that allows users to receive analytic input: “Amazon Machine Learning provides visualization tools and wizards that guide you through the process of creating ML models without having to learn complex ML algorithms and technology.”
Google Cloud Platform (GCP) is a direct competitor to Amazon Web Services powering a similar set of services: Media, Mobile Applications, Big Data Analytics, Financial Services, Gaming, Retail & Commerce, Internet of Things, Websites & Web Apps, Development & Test. GCP “…provides modern machine learning services, with pre-trained models and a service to generate your own tailored models. Our neural net-based ML platform has better training performance and increased accuracy compared to other large-scale deep learning systems.” Google uses Cloud Machine Learning on the following products: Cloud Machine Learning, including Photos (image search), the Google app (voice search), Translate, and Inbox (Smart Reply).
IBM – Watson has four core functions for their machine learning: Language, Speech, Vision, and Data Insights. Watson can begin learning a new subject by first acquiring all the available data. All materials are loaded including Word documents, PDFs, and web pages. Next question and answer pairs are added to train Watson on the new subject. As the new information is published Watson is automatically fed the updated changes. Watson scans and reviews all the information to identify thousands of answers. The collected evidence is evaluated and scored by a specialized algorithm to measure the quality of Watson’s conclusions. All possible answers are scored based on the supporting evidence.
Watson’s four product offerings are as follows:
- Watson Dataworks Project: Built on Apache Spark. Adds composable, hybrid-cloud services.
- Watson Explorer: Combines cloud-based enterprise search and content analytics with cognitive capabilities – connecting data across silos and revealing insights
- Watson Virtual Agent: Provides automated services to your customers providing cognitive, conversational self-service practice that can provide answers and take action.
- IBM Watson Knowledge Studio: Enables developers to input new data and work with collaborators to identify relationships within the data in new industries.
Microsoft has their own hand in Machine Learning with their own Azure services:
- Microsoft Azure offers a robust set of services including: Compute, Storage and content delivery, Networking, Database, Analytics and big data, Internet of Things, Mobile services, Application services, Management and monitoring and Security and identity. Two of their services emphasis machine learning:
- Cognitive Services: “Enable natural and contextual interaction with tools that augment users’ experiences using the power of machine-based intelligence. Tap into an ever-growing collection of powerful artificial intelligence algorithms for vision, speech, language, and knowledge.”
- Cortana Intelligence Suite: A fully managed cloud service that enables you to build quickly, deploy, and share predictive analytics solutions.