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William Vorhies's Blog (331)

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

Contextually Intelligent NLP Assistants – AI’s Next Big Technical Challenge

Summary:  Contextually intelligent, NLP-based interactive assistants are one of the next big things for AI/ML.  The tech is already here from recommendation engines.  The need to be more efficient and to become AI-augmented in our decision making is now.  Getting the contextual awareness is the hard part.

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Added by William Vorhies on October 28, 2019 at 9:43am — No Comments

The Next Big Thing in AI/ML is…

Summary:  AI/ML itself is the next big thing for many fields if you’re on the outside looking in.  But if you’re a data scientist it’s possible to see those advancements that will propel AI/ML to its next phase of utility.

 

“The Next Big Thing in AI/ML is…” as the lead to an article is probably the most…

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Added by William Vorhies on October 21, 2019 at 9:18am — 1 Comment

Surprise – Model Improvements Don’t Always Drive Business Impact

Summary:  Data Scientists from Booking.com share many lessons learned in the process of constantly improving their sophisticated ML models.  Not the least of which is that improving your models doesn’t always lead to improving business outcomes.

 

The adoption of AI/ML in business is at an inflection point. …

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Added by William Vorhies on October 14, 2019 at 9:28am — 1 Comment

Complete Hands-Off Automated Machine Learning

Summary:  Here’ a proposal for real ‘zero touch’, ‘set-em-and-forget-em’ machine learning from the researchers at Amazon.  If you have an environment as fast changing as e-retail and a huge number of models matching buyers and products you could achieve real cost savings and revenue increases by making the refresh cycle faster and more accurate with automation.  This capability likely will be coming soon to your favorite AML platform.

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Added by William Vorhies on October 7, 2019 at 7:28am — No Comments

We See in 3D – So Should Our CNN Models

Summary:  Autonomous vehicles (AUVs) and many other systems that need to accurately perceive the world around them will be much better off when image classification moves from 2D to 3D.  Here we examine the two leading approaches to 3D classification, Point Clouds and Voxel Grids.

 

One of the well-known…

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Added by William Vorhies on September 23, 2019 at 2:24pm — No Comments

NLP Picks Bestsellers – A Lesson in Using NLP for Hidden Feature Extraction

Summary:  99% of our application of NLP has to do with chatbots or translation.  This is a very interesting story about expanding the bounds of NLP and feature creation to predict bestselling novels.  The authors created over 20,000 NLP features, about 2,700 of which proved to be predictive with a 90% accuracy rate in predicting NYT bestsellers.

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Added by William Vorhies on September 3, 2019 at 7:35am — 1 Comment

Automated Machine Learning for Professionals - Updated

Summary: As the Automated Machine Learning (AML) movement got underway a few years back there was an early branch between proprietary platforms and open source platforms.  In this article we’ll update you on leading open source AML tools.  Since they continue to require fluency in Python or R we label them “professional”.

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Added by William Vorhies on August 5, 2019 at 7:11am — No Comments

Calibrated Quantum Mesh – Better Than Deep Learning for Natural Language Search

Summary:  Move over RNN/LSTM, there’s a new algorithm called Calibrated Quantum Mesh that promises to bring new levels of accuracy to natural language search and without labeled training data.

 

There’s a brand new algorithm for natural language search (NLS) and natural language understanding (NLU) that not…

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Added by William Vorhies on July 29, 2019 at 8:02am — No Comments

Measuring Progress Toward AGI Is Hard

Summary:  Artificial General Intelligence (AGI) is still a ways off in the future but surprisingly there’s been very little conversation about how to measure if we’re getting close.  This article reviews a proposal to benchmark existing AIs against animal capabilities in an Animal-AI Olympics.  It’s a real thing and just now accepting entrants.

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Added by William Vorhies on July 22, 2019 at 7:33am — No Comments

Thinking about Moving Up to Automated Machine Learning (AML)

Summary: Are you wondering about moving up to Automated Machine Learning (AML)?  Here are some considerations to help guide you.

 

Are you wondering about moving up to Automated Machine…

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Added by William Vorhies on July 15, 2019 at 7:30am — No Comments

Privacy and AI - How Much Should We Really Care

Summary:  More data means better models but we may be crossing over a line into what the public can tolerate, both in the types of data collected and our use of it.  The public seems divided.  Targeted advertising is good but the increased invasion of privacy is bad.

 

Headlines are full of alarm.  The public is up in arms.  The internet is stealing their privacy.  Indeed, the Future of Humanity Institute at Oxford rates this as the most…

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Added by William Vorhies on July 8, 2019 at 7:30am — 1 Comment

Where’s the Love – Trends in Data Science Career Opportunities

Summary:  The annual Burtch Works salary survey tells us a lot about which industries are using the most data scientists and the difference between higher and lower skilled data scientists.  Salary increases show us whether demand is increasing, and finally we take a shot at determining which skills are most in demand.

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Added by William Vorhies on July 1, 2019 at 8:00am — No Comments

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