Summary:  Bias in modeling has long been a public concern that is now amplified and focused on the disparate treatment models may cause for African Americans.  Defining and correcting the bias presents difficult issues for data scientists that need to be carefully thought through before reaching conclusions.

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Summary:  Explaining data science to a non-data scientist isn’t as easy as it sounds.  You may know a lot about math, tools, techniques, data, and computer architecture but the question is how do you explain this briefly without getting buried in the detail.  You might try this approach.

We’ve all been…

Summary:  What is an AI Product Manager and how do you know when you need one.

The role of Product Manager (PM) can mean many things dependent on the specifics of the company, its markets, its channels, and the variety of its products.  It’s almost impossible to put a single label on the responsibilities of a…

Summary:  In a comprehensive study of 18 recently presented DNN advancements in top-N recommenders, only 7 presented sufficient data to allow reproduction.  Worse, of the 7 that could be reproduced none showed an actual improvement over simple linear and KNN techniques when those were properly optimized.

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Summary: As we have become ever more enamored with DNNs, and their accuracy and utility has been paced only by their complexity we will need to answer the question of whether we will ever really be able to explain what goes on inside.

As we have become ever more enamored with DNNs, and their accuracy and…

The world has been witness to some profound changes over the past couple of decades. For example, we can shop for furniture without needing to leave our house or even send money halfway across the world with a few taps on your smartphone’s screen. However, there is one aspect of human existence that has undergone some of the most profound changes of them all — learning. Yep. Today, education is no more confined to schools, colleges, or other educational facilities. Today, students have not…

Summary:  Analytic Platforms are rapidly being augmented with features previously reserved for data scientists.  They are presented as easy to use but require substantial data literacy and advanced DS skills for the most complex.  Business users and analysts can pursue more complex problems on their own, but need good oversight.

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Summary:  Now that you have a little time for introspection, how about reviewing the performance of your chatbots.

Chances are this lock down period has given you a little more time for introspection and observation than you had before.  Let me suggest that this would be a good time to take a look at how your…

Let’s start with some simple real-lie examples that we’re sure you all must have experienced. 

You watch Netflix and it offers you viewing suggestions.

Twitter shows you relevant tweets on your timelines instead of recent ones.

Quora offers specific answers to all types of questions you…

Summary:  COVID-19 and the changes it creates in the business environment for the next 12 to 24 months means our current AI strategies need to thoroughly reviewed and probably retargeted.

Whether you are a Zoom-connected CXX level living out your WFH isolation or one the ‘fortunates’ in essential industries…

Summary:  High stakes models like those that allocate scarce resources to competing hospitals are headline news.  New thinking contrasting model-based versus model-free learning are emerging to describe new conditions we must consider before building or evaluating those models.

At this point we’re all…

Summary: Whether trying to predict the life outcomes of disadvantaged kids or to model where ventilators will be most needed, a little humility is in order.  As this study shows, the best data and the broadest teams failed at critical predictions.  Getting the model wrong, or more importantly using it in the wrong way can hurt all of us.

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Summary:  An interesting documentary about the earliest days of AI/ML and my alternate take on how we should really be describing the development of our profession to the newly initiated.

What could be more natural in these days of the Corona Virus than binge watching great videos.  I was intrigued by a…

Summary: Since COVID-19 is occupying most of our thoughts these days, it seems appropriate to highlight where AI/ML is making a contribution to getting us out of our homes and back to work. 

Since COVID-19 is occupying most of our thoughts these days, it seems appropriate to highlight where AI/ML is making a…

Edge computing moves workloads from  centralized locations  to remote locations and it can provide faster response from AI applications.  Edge computing devices are getting deployed increasingly for monitoring and control of real world processes like people tracking, vehicle recognition, pollution monitoring etc.  The data collected at the devices gets transported to centralized cloud servers over data pipelines and are used to train machine learning models. Training models needs lot…

90% of data in existence has been generated in the last two years. On a daily basis, 7.5 sextrillion gigabytes of data are generated - around 147,000 gigabytes per person. These numbers are staggering, but it’s to be expected: the world is growing and the machine economy is growing exponentially. That's not to say that all of this data is immediately useful. Organizations can’t simply tap into these sources without massive amounts of pre-processing – but is anybody…

Summary:  If you’re planning your AI/ML business strategy watch out for the confusion in categories and overly risky ratings given by some research and review sources.  Read the research, then consult with your own data scientists for a better evaluation of risk. It’s likely not as bad as you think. 

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Machine learning uses a lot of data and algorithms to predict something unexplored. Machine learning is simplifying our way of living, communicating, travel and work. Everyone uses machine learning in their daily lives. There has been a data revolution in the last few years, which has modified the way we obtain, create and communicate with the data.…

Summary:  Centaur AI is the best marriage of the machine’s ability to remember, analyze, and detect issues along with the human’s intuition to evaluate or take action on those results.  Instead of focusing on AI replacing humans, we should focus on AI in its role of augmenting humans.

In this angsty age where…