Summary:  Things are getting repetitious and that can be boring.  Still, looking at lessons from the 90s it’s clear there are at least one or two decades of important economic advances that will based on our current AI/ML.  Then some thoughts on where that next really huge breakthrough will come from that will return our initial excitement.

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Summary:  There is now sufficient experience among mid and large sized companies starting their AI journey to identify a single best practice for moving from AI experimentation to scale-up: the AI COE (Center of Excellence).

If you are a mid-sized business, government organization, or educational…

Summary:  Let’s start by clarifying the difference between RPA (Robotic Process Automation) and IA (Intelligent Automation).  Then we’ll show why AI/ML inside Intelligent Automation is the secret sauce that really makes this work.

As we’ve tracked the adoption of AI/ML across industries…

Summary:  Some industries are a clear slam-dunk for AI/ML applications and some less so.  The legal, regulatory, and compliance businesses (law firms, internal legal departments, and the contract review and regulatory compliance departments of heavily regulated industries) fall in this last category.  This is a review of seven companies found by TopBots to be successful; pointing to opportunities others can follow.

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• Your in-house data science team is not the exclusive source of AI/ML based improvements. 
• Process Re-engineering is gaining new life as a way to optimize data processes.…

Summary: Since BERT NLP models were first introduced by Google in 2018 they have become the go-to choice.  New evidence however shows that LSTM models may widely outperform BERT meaning you may need to evaluate both approaches for your NLP project.

Over the last year or two, if you needed to bring in an NLP…

Summary: This is a discussion of social injustice, real or perceived, promulgated or perpetuated by machine learning models.  We propose a simple solution based on wide spread misunderstanding of what ML models can do.

This is a discussion of social injustice, real or perceived, promulgated or perpetuated by…

Summary:  The annual Burtch Works salary survey with data through April shows that opportunities and salaries are still excellent for both new and experienced data scientists.  They also offer some anecdotal observations about the impact of the first few months of COVID on our work and opportunities.

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Summary:  Transfer Learning (TL) may be the most important aid to adoption of deep learning in the last several years.  This new LEEP measure predicts the accuracy of the transfer and should make TL faster, cheaper, and better.

What is the single most important innovation in deep learning in the last several…

Summary:  Less than 9%?  What this study really shows and what we should take away from it.

Wow.  Less than 9%!  Can this be true?  Well according to a large scale survey study conducted by the US Census Bureau it’s actually a…

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…

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…

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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