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William Vorhies's Blog Posts Tagged 'intelligence' (43)

Big Ideas in AI for the Next 10 Years

Summary:  Despite our concerns about China taking the lead in AI, our own government efforts mostly through DARPA continue powerful leadership and funding to maintain our lead.  Here’s their plan to maintain that lead over the next decade. 

Think all those great ideas that have powered AI/ML for the…

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Added by William Vorhies on June 10, 2019 at 8:28am — No Comments

Should You Be Recommending Deep Learning Solutions in Your Company?

Summary:  If you are guiding your company’s digital journey, to what extent should you be advising them to adopt deep learning AI methods versus traditional and mature machine learning techniques.

 

By now everyone is at least familiar with using AI/ML as a required cornerstone of company strategy.  Frequently…

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Added by William Vorhies on May 20, 2019 at 8:33am — 1 Comment

Where AI/ML Creates Value in Consumer Goods & Retail and Where It Needs Help

Summary: Especially in consumer goods and retail the value of AI/ML is only part of the story.  AI/ML will increasingly need to integrate with helper technologies to deliver maximum value.  Up your game in IoT, 5G, and robotics to ensure you’re giving your operating team all the best options for their investment.

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Added by William Vorhies on May 13, 2019 at 8:06am — No Comments

What to Tell Your Board About AI/ML

Summary:  Communicating with your Board of Directors about AI/ML is different from conversations with top operating executive.  It’s increasingly likely your Board will want to know more and planning that communication in advance will make your presentation more successful.

 

As AI/ML becomes increasingly…

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Added by William Vorhies on April 29, 2019 at 9:35am — No Comments

Is Robotic Process Automation (RPA) Really AI?

Summary:  Based on a McKinsey study we reported that 47% of companies had at least one AI/ML implementation in place.  Looking back at the data and the dominance of RPA as the most widely reported instance makes us think that the number is probably significantly lower.

 

We’ve been trying to get a handle on…

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Added by William Vorhies on March 18, 2019 at 9:00am — 3 Comments

Faster Better Cheaper Image Recognition

Summary:  In the literal blink of an eye, image-based AI has gone from high cost, high risk projects to quick and reasonably reliable.  C-level execs looking for AI techniques to exploit need to revisit their assumptions and move these up the list.  Here’s what’s changed.

 

For data scientists these are miraculous times.  We tend to think of miracles as something that occurs instantaneously but in our world that’s not quite so.  Still the rate…

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Added by William Vorhies on March 4, 2019 at 9:41am — No Comments

Where and How is AI Actually Being Adopted

Summary:  Adoption of AI/ML by larger companies has more than doubled since last year according to these survey results from McKinsey and Stanford’s Human-Centered AI Institute.  This new data gives us a much better idea of which global regions and which industries are adopting which AI/ML techniques.

 

We know…

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Added by William Vorhies on February 25, 2019 at 9:00am — No Comments

Doctors are from Venus, Data Scientists from Mars – or Why AI/ML is Moving so Slowly in Healthcare

Summary: The world of healthcare may look like the most fertile field for AI/ML apps but in practice it’s fraught with barriers.  These range from cultural differences, to the failure of developers to really understand the environment they are trying to enhance, to regulatory and logical Catch 22s that work against adoption.  Part 3 of 3.

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Added by William Vorhies on January 21, 2019 at 7:59am — 2 Comments

The AI/ML Opportunity Landscape in Healthcare. Do It Right or It Will be More of a Mine Field.

Summary:  Despite hundreds of projects and thousands of data scientists devoted to bringing AI/ML to healthcare, adoption remains low and slow.  A good portion of this problem is our own fault for failing to see the processes being disrupted through the eyes of the physician users.  Here we lay out the healthcare opportunity landscape but for data scientists following classical disruption strategies, it may be more of a minefield.  Part 2 of…

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Added by William Vorhies on January 14, 2019 at 8:00am — No Comments

Seeing the AI/ML Future in Healthcare Through the Eyes of Physicians. It Doesn’t Look Quite the Way Data Scientists See It.

Summary: If you want to understand the promise of AI/ML in healthcare you need to see it through the eyes of physicians, the ultimate users.  Turns out these folks aren’t the rapid adopters you’d think they’d be and the problem is largely with the way data scientists have tried to implement.  Part 1 of 3.

 

It’s…

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Added by William Vorhies on January 7, 2019 at 8:00am — 4 Comments

5 Predictions about Data Science, Machine Learning, and AI for 2019

Summary:  Here are our 5 predictions for data science, machine learning, and AI for 2019.  We also take a look back at last year’s predictions to see how we did.

 

It’s that time of year again when we do a look back in order to offer a look forward.  What trends will speed up, what things will actually happen,…

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Added by William Vorhies on December 17, 2018 at 8:50am — No Comments

Who Do We Blame When an AI Finally Kills Somebody

Summary:  We’re rapidly approaching the point where AI will be so pervasive that it’s inevitable that someone will be injured or killed.  If you thought this was covered by simple product defect warranties it’s not at all that clear.  Here’s what we need to start thinking about.

 

So far the press…

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Added by William Vorhies on December 10, 2018 at 10:07am — 1 Comment

Can AI Make B2B Sales Better?

Summary: Sales is supposed to be an area that is more immune to replacement by AI than many others because of the high level of impromptu and improvisational human contact required.  That remains true.  But AI is showing that it can be a valuable augment to B2B sales and some early adopters are scoring big gains.

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Added by William Vorhies on December 4, 2018 at 9:59am — No Comments

The Two (Conflicting) Definitions of AI

Summary:  There are two definitions currently in use for AI, the popular definition and the data science definition and they conflict in fundamental ways.  If you’re going to explain or recommend AI to a non-data scientist, it’s important to understand the difference.

 

For a profession as concerned with accuracy as we are, we do a really poor job at naming things, or at least being consistent in the naming.  “Big Data” – totally misleading…

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Added by William Vorhies on November 27, 2018 at 8:23am — No Comments

The Best Opportunities in AI for Data Scientists

Summary:  Looking for your next job in an early stage company but want to make sure your startup has staying power.  Follow the expert rankings by CB Insights that also show us the changing trends in how AI startups should be focusing their offerings.

 

Let’s suppose you’re early in your data science career and your…

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Added by William Vorhies on November 5, 2018 at 4:18pm — No Comments

The Case for Just Getting Your Feet Wet with AI

Summary:  Even if you’re not big enough to have a full blown data science group that shouldn’t hold you back from benefiting from AI.  The market has evolved so that there are now industry and process specific vertical applications available from 3rd party AI vendors that you can implement.  There are just a few things to look out for.

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Added by William Vorhies on October 23, 2018 at 7:30am — No Comments

Practicing ‘No Code’ Data Science

Summary:  We are entering a new phase in the practice of data science, the ‘Code-Free’ era.  Like all major changes this one has not sprung fully grown but the movement is now large enough that its momentum is clear.  Here’s what you need to know.

 

We are entering a new phase in the practice of data science, the ‘Code-Free’…

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Added by William Vorhies on October 9, 2018 at 9:54am — 3 Comments

Democratizing Deep Learning – The Stanford Dawn Project

Summary:  How about we develop a ML platform that any domain expert can use to build a deep learning model without help from specialist data scientists, in a fraction of the time and cost.  The good news is the folks at the Stanford DAWN project are hard at work on just such a platform and the initial results are extraordinary.

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Added by William Vorhies on September 4, 2018 at 8:02am — No Comments

From Strategy to Implementation – Planning an AI-First Company

Summary:  Our recent series of articles on AI strategies shows the options available for the strategic direction of your AI-first company.  Here are some thoughts on moving from strategy to implementation, including some useful tools to help in planning.

 

Hope you’ve been following our latest series of articles describing and…

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Added by William Vorhies on August 7, 2018 at 7:25am — 1 Comment

Comparing the Four Major AI Strategies

Summary: Now that we’ve detailed the four main AI-first strategies:  Data Dominance, Vertical, Horizontal, and Systems of Intelligence, it’s time to pick.  Here we provide side-by-side comparison and our opinion on the winner(s) for your own AI-first startup.

 

In our last several articles we’ve taken a tour of the four major…

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Added by William Vorhies on July 31, 2018 at 8:20am — No Comments

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