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IT IS LIVE: Get your copy

Oct 9: 6 EMA Top 3 Product Showcases went live

Oct 2: EMA Press Release

Oct 11: Continuous news-feed now available

Oct 2: New AI rants with Umair Khan, Andi Mann, Andrew Hillier, and Adam Carmi

​Sep 26: Report Launch Date: Tue, Oct 2, 2018: 6a.m.

Sep 25: Machine Learning (not only) for Kids mini site goes live.

Sep 15: EMA Speaking at DevOps Enterprise Summit (DOES) in Las Vegas: AI and DevOps

Sep 11: Security Risks of Enterprise AI

Sep 10: 6 Best Practices to Prevent Bias in Artificial Intelligence
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Sept 7: How to leverage AI for DevOps

Sept 6: 6 Best Practices to Recognize and Prevent AI Bias

Sept 3: EMA Speaking at DOES 2018: AI in DevOps

Aug 21: How AI "thinks" versus how the human brain works (example)



Aug 21: Added report launch timeline.

Aug 17: Comprehensive Q&A in terms of report content and vendor selection. 

Aug 16: Naming the EMA Top 3 categories.

Aug 16: FAQ page

[BLOG POST]: The 10 Most Common Misconceptions in AI/ML in 2018 (August 15)

EMA has started to schedule press briefings on the EMA Top 3 AI/ML decision guide for enterprise (August 14).

First demo videos recorded with EMA Top 3 winners. Exciting! (August 13)

AI Product Showcases and AI Rants

AI/ML Are the #1 Priority in 2018

EMA End User Research Facts

Artificial Intelligence and Machine Learning (AI/ML) are at the top of the list of IT, Business, and DevOps priorities for 2018.

This EMA Enterprise Decision Guide presents 33 EMA Top 3 products in 11 categories (4 DevOps, 4 IT Ops, 3 Business). 

5 Critical Selection Criteria
The EMA Top 3 products were selected based on their ability to enable customers to better leverage AI/ML for real-life projects. 

1. Does the product address one or more of today's AI/ML key pain points?

2. Will the customer receive quantifiable value compared to solutions that do not leverage or support AI/ML?

3. Can the customer implement and maintain the product without major rearchitecting efforts and without hiring additional staff?

4. Is the product sufficiently reliable to enable customers to replace their existing solution?

5. Does the product help tie together business, IT, and DevOps?

To prevent another AI Winter, we need to emphasize the tremendous business impact of what AI/ML can do today. This image shows IBM Visual Insights correctly checking an industrial part for quality issues, without ever having seen those exact defects before. This shows that today’s top-down approach of creating narrow inference models through providing large numbers of pre-labeled examples can exceed human performance in many cases.

AI/ML Breakthroughs

1993: The First Convolutional Neural Network by Yann LeCun

Yann LeCun's one minute demo of the first convolutional neural network (CNN) shows the vast potential of CNNs. Rule-based programming could never come close to recognizing everyone's individual handwriting under difficult conditions.

2003: The first CNN-based face detection software

In 2003, 10 years after LeCun's initial CNN breakthrough in handwriting recognition, his team successfully used CNN for facial recognition. 

EMA AI Publications

How AI really Thinks
Don't be discourage by this piece, as our thoughts are purely directed toward setting realistic expectations. Knowing what you can and cannot expect from AI/ML is key to successfully leveraging these technologies. Read Article

AI Project Cheat Sheet
Questions to ask software vendors when talking about AI. This will eventually be merged into the Top 3 report, but currently stands alone to provide basic guidance through the AI marketing jungle. Read Article 

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