The Machine Learning BIOD-ome

Posted by Sinan Ozdemir on 9/25/17

Business leaders from a wide variety of industries and from companies both large and small are feeling the pressure to implement viable and effective AI strategies to keep up with the many innovations happening in the field.

As a CTO and a former consultant in the data science and machine learning space, I often get asked the question, “How do I go about planning out and deploying a machine learning project at my company?” Most of the time, managers do not have intimate familiarity with machine learning or how to apply machine learning to their business problems. When I get asked this, I almost always reply with a simple answer, “BIOD”.

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Topics: Artificial Intelligence, Machine Learning, Customer Support

How Neural Networks Think

Posted by Shayaan Abdullah on 9/20/17

This blog post was originally posted by Larry Hardesty on MIT News.

Artificial-intelligence research has been transformed by machine-learning systems called neural networks, which learn how to perform tasks by analyzing huge volumes of training data.

During training, a neural net continually readjusts thousands of internal parameters until it can reliably perform some task, such as identifying objects in digital images or translating text from one language to another. But on their own, the final values of those parameters say very little about how the neural net does what it does.

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Topics: Artificial Intelligence, Neural Networks

Executive Guide to Artificial Intelligence

Posted by Josh Adragna on 9/19/17

Several recent studies and surveys’ across several sources has shown that implementing an artificial intelligence strategy can be a challenging maze to navigate. With a lack of extensive business cases and A.I. implementation examples it can create a needle in the haystack scenario for business leaders not only looking for relevant A.I. solutions, but also successfully creating A.I. initiatives.

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Topics: Customer Experience, Artificial Intelligence, Customer Support

MILABOT and the Amazon Alexa Prize Competition

Posted by Shayaan Abdullah on 9/18/17

In 2016 Amazon inaugurated the Alexa Competition dedicated to “accelerating the field of conversational AI”, with the winner to be determined in late 2017. As part of the competition, university research teams attempted to build a socialbot that could converse coherently and engagingly with humans on popular topics for 20 minutes.

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Topics: Artificial Intelligence, Deep Learning, Machine Learning, Reinforcement Learning, natural language processing

Data Alone Isn’t Ground Truth

Posted by Divya Susarla on 9/13/17

This blog post was originally posted on Medium by Angela Bassa

I saw a chart the other day that highlighted the importance of bringing skepticism to any data analyses and visualizations we encounter. This post isn’t a dissertation, and it necessarily does not address the topic fully. But I think there are some good point I can make on the topic, and if it sparks a good conversation that I think it’s served a good purpose.

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