Microservices, Platforms, and the Infrastructure of AI: The Video

AI and Machine Learning are often at their best as composite services  performing as part of a coordinated platform. In this brief set of videos, we look at AI APIs, microservices, platforms, and how they can be brought together to achieve larger goals.  These are recent discussions in a rapidly evolving territory where exciting visions continue to emerge.

The videos are a mixture of seminars and discussions avaialable under standard YouTube license, with landing page descriptions added. Minor edits have been made where necessary.

Machine Learning APIs by Example (Google Cloud)

Published on Mar 9, 2017

Think your business could make use of Google’s machine learning expertise when it comes to powering and improving your business applications, but do you get stuck on building and training your own custom model? Google Cloud Platform (GCP) offers five APIs: Google Cloud Vision API, Cloud Speech API, Cloud Natural Language API, Cloud Translation API and Cloud Video API. These APIs access pre-trained machine learning models with a single API call. In this video, Sara Robinson shares an overview of each API. Then she dives into code with a live demo.

Fireside Chat: Crafting the Future of Technology – Microservices & Platforms (Zinnov Management Consulting)

Published on Mar 30, 2017

Kevin Prendeville, Managing Director – PE & LS, Accenture
Pankaj Chawla, MD & CTO – Products and Platforms Engineering, Accenture
Peter Schmutzer, Director Purchasing, Intel
Siddhartha Agarwal, VP, Product Management & Strategy, Oracle

We are in the midst of a revolution in artificial intelligence: the art and engineering of getting computers to perform tasks that, until recently, required natural intelligence — in other words, people. We can speak to our phones, software can identify faces, and algorithms can teach themselves to play Atari video games. Top-of-the-line sedans have the ability to drive autonomously on the open road. Progress has been driven by machine learning techniques, such as deep convolution networks, dating to the 1980s, by Moore’s law, and by continual improvements in machine architecture. Progress is so dizzying that a few futurists, technologists, and philosophers have publicly mused about where the swift ascension of machines is taking us. In this session, we will have a sneak-peek into the future of AI and what it holds for us.

APIs and Artificial Intelligence (Google Cloud)

Published on Mar 9, 2017

A fundamental goal for every business is to keep users attention and focus on their products or services. Combining APIs with AI leads to better stickiness.

Having Fun with Robots Using Microservices on Docker and Kubernetes (Devoxx)

Published on Nov 10, 2016

Controlling and building a single robot is already a challenge, but how would that work if you want to have a swarm of robots interact with each other? How do we control and interact with them whilst all robots are slightly different?


 


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