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Sunday, August 26, 2018

Seeking Stages of Smart

Great piece in DSC about 'creating smart'.   What does it mean, anyway?  To begin with we are doing lots of misusing of the term, since it includes intention and embedding with context.  Here is the prologue, rest at the link:

3 Stages of Creating Smart in DSC    Posted by Bill Schmarzo  

“Tomorrow’s market winners will win with the smartest products.  It’s not enough to just build insanely great products; winners must have the smartest products!” – Bill Schmarzo

Okay, that’s a pretty bold statement on my part (especially to challenge the famous Steve Jobs statement about building insanely great products), but then again I’m an analytics dude and think that analytics should be a part of every product and space – smart cities, smart cars, smart vacuums, smart hospitals, smart Chipotle…

But it’s not just me that thinks this way.  Tesla’s forthcoming autonomous cars will be nothing more than an artificial intelligence machine on wheels.  Tesla is building its own “AI computer”, complete with Tesla-specific microprocessors (silicon), to power its autonomous vehicles (see “Tesla Earnings Bombshell Reminds Us That Tesla's a Tech Company” for more details).  And Google is creating the foundation for smart products with its new Edge TPU; a tiny AI accelerator that will carry out machine learning jobs “at the edge” of IoT (see “Google unveils tiny new AI chips for on-device machine learning” for more details).

The technology is advancing at a pace that should enable any company to create “smart” products, things and spaces. But how does one go about actually creating smart?  How does one decide where and how to integrate the growing power of machine learning, deep learning and artificial intelligence capabilities to power these smart products? 

Here’s my three step recipe for “Getting Smart” (with images of Maxwell Smart dancing in my head).

Step 1: Identify, Validate, Value and Prioritize the Decisions that Power “Smart”
The first step in “Getting Smart” involves identifying, validating, vetting, valuing and prioritizing the decisions[1](or use cases) that the smart entity or product needs to make in support of its operational goals.  For example, a “smart” city initiative would need to optimize decisions around traffic congestion, local events, crime, safety, road maintenance, building permits and more (see Figure 1). ... "

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