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William Vorhies's Blog (323)

Predictability of Life Outcomes - Guess We Can’t Predict Everything

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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Added by William Vorhies on April 6, 2020 at 2:56pm — No Comments

Binge Watching “The History of Artificial Intelligence”

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…

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Added by William Vorhies on March 30, 2020 at 2:52pm — 1 Comment

Building a COVID-19 Vulnerability Index

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…

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Added by William Vorhies on March 24, 2020 at 8:40am — 2 Comments

Mid-Career Switching into Data Science and Data Engineering

Summary:  Mid-career switching into data science is difficult.  But if you already have substantial data base experience becoming a Data Engineer can be a great career by itself, or even the first stepping stone to becoming a Data Scientist.

 

One of the most common requests we get is for advice on mid-career…

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Added by William Vorhies on March 16, 2020 at 11:26am — No Comments

Making Sense of the Hype Cycle for Artificial Intelligence

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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Added by William Vorhies on March 2, 2020 at 12:42pm — No Comments

With AI It’s Adoption That Matters

Summary:  How to measure the degree and value of AI adoption among companies or even countries is hard.  Here’s a beginning proposal on how to get started.

 

We talk a great deal about whether there are enough data scientists to go around, whether our advancements in AI techniques are better than others, if…

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Added by William Vorhies on February 25, 2020 at 10:07am — No Comments

Advanced Analytic Platforms – Changes in the Leaderboard 2020

Summary: The Gartner Magic Quadrant for Data Science and Machine Learning Platforms is just out the big news is how much more capable all the platforms have become.  Of course there are also some interesting winner and loser stories.

 

The Gartner Magic Quadrant for Data Science and Machine Learning Platforms is just out for 2020.  The really big news is how many excellent choices are now available.  In a remarkable move, the whole field of…

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Added by William Vorhies on February 17, 2020 at 12:19pm — 2 Comments

An Argument in Favor of Centaur AI

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…

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Added by William Vorhies on February 11, 2020 at 1:19pm — No Comments

Revisiting the Implementation of AI Strategies

Summary:  Can all AI strategies be defined by a few common needs or are the different AI strategy models sufficiently unique that they need to be considered as separate approaches.

 

There’s an article in the current Harvard Business Review titled “…

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Added by William Vorhies on February 3, 2020 at 11:15am — No Comments

AI Techniques for Workforce Forecasting

Summary:  Workforce forecasting and scheduling applications are rapidly upgrading their use of AI.  Techniques of time series forecasting ranging from the simple Holt Winters to the complex, DNNs and Multiple Temporal Aggregation are available on some but not all platforms.  Increasingly, AI differentiates the usefulness of these apps.

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Added by William Vorhies on January 28, 2020 at 2:15pm — No Comments

Just How Much Do You Trust Your AI?

Summary:  Just how much should you trust your AI systems?  Best practice points to constant review, strong governance, and the willingness to override results that seem illogical.

 

Just how much do you trust your AI?  This is not intended to be the skeptical consumer view about bias or black box outcomes. …

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Added by William Vorhies on January 20, 2020 at 8:26am — No Comments

Just How Much Does the Future Depend on AI?

Summary:  Looking at the 12 hottest world-changing segments in the VC-funded world shows that AI will play a key role.  Here’s a little more detail.

 

From the inside of the data science profession looking out it’s easy to imagine that almost everything that is or will be important somehow depends on AI.  Maybe…

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Added by William Vorhies on January 13, 2020 at 11:20am — 1 Comment

Six AI Strategies – But Only One Winner

Summary:  The results are in.  There is only one demonstrably successful strategy for creating big wins for AI-first companies.  We’ll briefly summarize the other contenders that have fallen by the wayside and then lift the curtain on the winner.

 

For the last three years we’ve been close observers of exactly…

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Added by William Vorhies on January 7, 2020 at 8:30am — No Comments

Can Reinforcement Learning Break Through in 2020

Summary:  Reinforcement Learning (RL) is going to be critical to achieving our AI/ML technology goals but it has several barriers to overcome.  While reliability and a reduction in training data may be achievable within a year, the nature of RL as a ‘black box’ solution will bring scrutiny for its lack of transparency.

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Added by William Vorhies on December 30, 2019 at 11:18am — No Comments

Reimagining Reinforcement Learning – Upside Down

Summary:  For all the hype around winning game play and self-driving cars, traditional Reinforcement Learning (RL) has yet to deliver as a reliable tool for ML applications.  Here we explore the main drawbacks as well as an innovative approach to RL that dramatically reduces the training compute requirement and time to train.

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Added by William Vorhies on December 23, 2019 at 7:30am — No Comments

Is AI About to Hit a Wall?

Summary:  There have been several stories over the last several months around the theme that AI is about to hit a wall.  That the rapid improvements we’ve experienced and the benefits we’ve accrued can’t continue at the current pace.  It’s worth taking a look at these arguments to see if we should be adjusting our plans and expectations.

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Added by William Vorhies on December 16, 2019 at 9:24am — 5 Comments

No Matter What You Call It, It’s all the Same Thing

Summary:  A little history lesson about all the different names by which the field of data science has been called, and why, whatever you call it, it’s all the same thing.

 

A little reminiscence, or for those of you who are only recently data scientists, a little history lesson. 

Our profession of…

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Added by William Vorhies on December 4, 2019 at 3:12pm — No Comments

The Logjam in AI/ML Platforms is About to Complicate Your Life

Summary:  Too many solutions.  We are at an inflection point where too many vendors are offering too many solutions for moving our AI/ML models to production.  The very real risk is duplication of effort, fragmentation of our data science resources, and incurring unintended new technical debt as we bind ourselves to platforms that have hidden assumptions or limitations in how that approach problems.

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Added by William Vorhies on November 25, 2019 at 9:44am — No Comments

Gartner and Forrester Begin to Weigh in on Automated Machine Learning (AML)

Summary:  AML has been around since at least 2016 but only in the last year have Gartner and Forrester begun to offer their opinions.  Here’s where we stand.

 

This has been a big year for AML (automated machine learning).  A number of new players have emerged and pretty much everyone acknowledges that some…

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Added by William Vorhies on November 18, 2019 at 12:00pm — No Comments

It’s Official – Our DNN Models are Now Commodity Software

Summary:  Booz Allen just launched a one-stop shop for all manner of pretested DNN models.  They’re even guaranteeing price.  This makes buying just like picking accounting, CRM, or HRIS software.  Equally as important, it’s a genius example of platform strategy to lock in customers and lock out competitors.

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Added by William Vorhies on November 12, 2019 at 4:00pm — 1 Comment

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