The Race is on: comparing Google and Microsoft's Cognitive Services
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The document discusses the competitive landscape of cognitive services between Microsoft and Google as of June 2017, highlighting various technologies and services such as Microsoft's Cortana and Azure Machine Learning, and Google's Assistant and Cloud APIs. It outlines the focus on agent bots, machine learning, and augmented reality, emphasizing the importance of winning developers in the cognitive arms race. Additionally, it presents observations and recommendations on implementing these technologies effectively.
The Race is on: comparing Google and Microsoft's Cognitive Services
- 1. Comparing Google and Microsoft’s Cognitive Services The Race Is On June 2017 Jeff Fried CTO, BA Insight
- 2. The Cognitive Arms Race
- 3. Agent Bots Cognitive Machine Learning Augmented Reality Microsoft Cortana Bot Framework Cognitive Services - Vision - Speech - Language - Knowledge - Search - Labs Azure ML Cognitive Toolkit Hololens Google Google Assistant API.AI Cloud Vision API Cloud Video Intelligence Cloud Speech API Cloud Natural Language API Google Knowledge Graph Google Custom Search ML Advanced Solutions Lab Cloud ML Engine TensorFlow Glass at Work Daydream/Tango IBM Watson Virtual Agent Watson Conversation Watson APIs - Vision - Speech - Language - Data Insights Watson ML Service Apache SystemML Amazon Alexa Amazon Lex Rekognition Polly Amazon ML Apple Siri SiriKit Speech Core ML ARKit Facebook Facebook M ParlAI FastText CommAI Torch Oculus Rift The Cognitive Arms Race Today, we’ll focus on Microsoft and Google events/messages; cognitive services; example project; DX
- 8. Agent Applications Services Infrastructure Microsoft AI Portfolio Cortana Office 365 Dynamics 365 SwiftKey Pix Customer Service and Support Bot Framework Cognitive Services Cortana Intelligence Cognitive Toolkit Azure Machine Learning Azure N Series FPGA People
- 9. Microsoft Cognitive Services Give your apps a human side
- 11. Image Classifier and Search project libraries and issue detection Search Visualization Workflow
- 13. Sales Assistant: Logical Architecture Client App/Device CRIS Voice to Text LUIS Semantics Extraction Web Service App/API Data Sources Text to Speech ML Studio Service EndPoints Power BI Bot FX SQL Server or DW Document Db Key/ValueGraph Db Table Store BLOB Microsoft Azure Voice Data Text + Tabular Data & Power BI Visuals Human User Voice Capture Polyglot
- 14. The Cognitive Arms Race: focus is now on winning developers
- 18. Agent Bots Cognitive Machine Learning Augmented Reality Microsoft Cortana Bot Framework Cognitive Services - Vision - Speech - Language - Knowledge - Search - Labs Azure ML Cognitive Toolkit Hololens Google Google Assistant API.AI Cloud Vision API Cloud Video Intelligence Cloud Speech API Cloud Natural Language API Google Knowledge Graph Google Custom Search ML Advanced Solutions Lab Cloud ML Engine TensorFlow Glass at Work Daydream/Tango IBM Watson Virtual Agent Watson Conversation Watson APIs - Vision - Speech - Language - Data Insights Watson ML Service Apache SystemML Amazon Alexa Amazon Lex Rekognition Polly Amazon ML Apple Siri SiriKit Speech Core ML ARKit Facebook Facebook M ParlAI FastText CommAI Torch Oculus Rift The Cognitive Arms Race
- 19. Content Content Processing Search Index Search UI ML applied to search Query Processing Learning about content structure Learning about user intent Analytics Behavioral data to drive learning Learning to rank
- 21. Quickstart guide Graph data Get curious – ask a question See some results – how well did it go Pick a common ML tool and sample data Disease or not disease? MicrosoftML
- 22. Option A – Prebuilt Solutions Cognitive Services API Azure Gallery
- 23. Option B – Manual Solutions Microsoft R Server Azure Machine Learning Studio
- 24. Option B – Manual Solutions (cont’d) Cognitive Toolkit Tensor Flow