AWS emerged organically to be a Trillion Dollar baby, not invented by any one person

Medium has a 4 year old post from Jan 2015 interviewing Andy Jassy. The paragraph that caught my eye is Andy describing the beginning. The invention of AWS.

Amazon Web Services wasn’t any one person’s single idea. No proverbial apple fell on some Newton’s head, no Henry Ford or Steve Jobs-like character had a brainstorm. Instead, it rather emerged. The idea grew organically out of the company’s frustration with its ability to launch new projects and support customers.

The other part was the willingness to experiment and fail.

Invention”, says Jassy, “requires two things: 1. The ability to try a lot of experiments, and 2. not having to live with the collateral damage of failed experiments.

These are good lessons to think about when creating new services.

Solving multiple problems with a picture, Amazon takes pictures of delivery

The verge has an article on Amazon taking pictures of front door deliveries. 

“Amazon has been quietly rolling out a new program over the past few months where delivery people will use photos to confirm your package has been delivered. The photo of exactly where the package has been placed will be included in the notice of delivery so Amazon users know when it arrived and where it is, as first spotted by USA Today.” 

Most think about here is the proof the package is delivered.  But it is also a quality control event to document package delivery and information about the delivery site. The information can be used for quality control and other ideas to improve the quality of delivery. 

Once I received items where the contents of the box where not what I ordered. Seeing the package could confirm whether it was possible that the label got put on the wrong box.

A visit to Amazon Go, the really hard part is tracking of people

I was at University of Washington today meeting with a supply chain professor and had time to add a visit to the Amazon Go store. The store is next to Amazon domes.


Before I went I found this coconut cake I wanted to try. I also picked up a drink, chips, and a sandwich.


what was interesting is the 2D code that amazon packaged items had versus a UPC code. Which then got me to think that there are cameras pointing from the bottom and surrounding areas to read the UPC code and detect it gets moved to your bag. When you put it back it removes from your cart. OK. easy.

Then i thought what is the hard part is uniquely identifying all the people. When you look at the the number of cameras it makes sense to track the people. See this Arstechnica article for more details.

So basically by watching me. Amazon know my height. Can guess my weight. Can track my movements. How i walk. Facial recognition. Most likely. I have now been cataloged by Amazon. tracking thousands of people a day as unique individuals is much harder than tracking a few hundred grocery skus with known locations and bar codes.

I will go back to the Amazon store with a Microsoft friend and do a walk through. Yes I still a friend at Microsoft. :-). 

The store was interesting and got me thinking of some new stuff.  But actually my talk with University of Washington Supply Chain Professor was 10X more valuable. But I am keeping that conversation to myself and friends.

AWS IOT platform will be a new platform for DCIM

A couple of weeks ago I wrote about Implementing DCIM on an IOT Platform. And that the end of DCIM is coming. What I didn’t think about was how quickly things can change and AWS would be at the center of this change.

AWS Re:invent is going on. I have never gone, but have plenty of friends who are there and I can chat with them. What I did do yesterday was watch Andy Jassy’s opening keynote and the best part was the last 15 minutes where Andy covered the AWS IOT Platform. Below are the 8 parts of the platform.

Also I placed a pre-order for an AWS DeepLens

With the AWS Platform the current ways of building DCIM are shown to be in the past. The future is to build DCIM on IOT. All you DCIM vendors get ready to compete against AWS and its partners. This includes Litbit who was trying to do a subset of AWS IOT. Luckily for DCIM vendors AWS IOT is not targeting the DCIM market. AWS IOT is going after the industrial IOT market which is magnitudes bigger. I checked out the vendor list to run their services on at the edge and it is impressive for a start at launch.

AWS IOT is good enough that I am looking to add it to a lab environment to play with it more. 

AWS IoT Services

AWS IoT Core 

AWS IoT Core is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices. IoT Core can support billions of devices and trillions of messages, and can process and route those messages to AWS endpoints and to other devices reliably and securely.

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AWS IoT Device Management 

AWS IoT Device Management is a service that makes it easy to securely onboard, organize, monitor, and remotely manage IoT devices at scale.

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AWS Greengrass

AWS Greengrass is software that lets you run local compute, messaging & data caching for connected devices in a secure way. With AWS Greengrass, connected devices can run AWS Lambda functions, keep device data in sync, and communicate with other devices securely - even when not connected to the Internet.

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AWS IoT Analytics

AWS IoT Analytics is a fully-managed service that makes it easy to run sophisticated analytics on massive volumes of IoT data without having to worry about all the cost and complexity typically required to build your own IoT analytics platform. It is the easiest way to run analytics on IoT data and get insights to make better and more accurate decisions for IoT applications and machine learning use cases.

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Amazon FreeRTOS

Amazon FreeRTOS is an operating system for microcontrollers that makes small, low-power edge devices easy to program, deploy, secure, connect, and manage.

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AWS IoT 1-Click 

AWS IoT 1-Click is a service that makes it easy for simple devices to trigger AWS Lambda functions that execute a specific action. Some examples of possible actions include calling technical support, reordering goods and services, or locking and unlocking doors and windows.

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AWS IoT Button

The AWS IoT Button is a programmable button based on the Amazon Dash Button hardware. This simple Wi-Fi device is easy to configure and designed for developers to get started with AWS IoT CoreAWS LambdaAmazon DynamoDBAmazon SNS, and many other Amazon Web Services without writing device-specific code.

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AWS IoT Device Defender

AWS IoT Device Defender is a fully managed service that helps you secure your fleet of IoT devices. AWS IoT Device Defender continuously audits the security policies associated with your devices to make sure that they aren’t deviating from security best practices. AWS IoT Device Defender also lets you monitor devices for behavior that deviates from what you have defined as appropriate behavior for each device. 

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Microsoft and AWS AI partnering, some one must have driven the idea

Technology wars are dumb like many other wars. Years and years ago I realized the font war between Microsoft and Adobe was dumb and the users were losing out as the Typographers at Adobe and Microsoft would fight the battle between TrueType and Type 1. I was behind the scenes brokering the deal between Microsoft and Adobe independent of the font teams at each company. It is sometimes what you have to do stop war.  

AWS and Microsoft have press releases on its AI partnership. Gluon 

“What is Gluon?

Gluon is a concise, dynamic, high-level deep learning library, or interface, for building neural networks. It can be used with either Apache MXNet or Microsoft Cognitive Toolkit, and will be supported in all Azure services, tools and infrastructure. Gluon offers an easy-to-use interface for developers, highly-scalable training, and efficient model evaluation–all without sacrificing flexibility for more experienced researchers. For companies, data scientists and developers Gluon offers simplicity without compromise through  high-level APIs and pre-build/modular building blocks, and more accessible deep learning.”

"The potential of machine learning can only be realized if it is accessible to all developers. Today’s reality is that building and training machine learning models requires a great deal of heavy lifting and specialized expertise,” said Swami Sivasubramanian, VP of Amazon AI. “We created the Gluon interface so building neural networks and training models can be as easy as building an app. We look forward to our collaboration with Microsofton continuing to evolve the Gluon interface for developers interested in making machine learning easier to use.” 

Digging around a bit I was trying to find more behind the scenes information.

”According to a report in the New York Times, the two rival tech firms were reportedly coordinating behind the scenes for the past year to make artificial intelligent assistants Alexa and Cortana communicate with each other.” 

There are lots of ex-Microsoft people in AWS. And there are lots of ex-AWS in Microsoft. With all those people moving back and forth and the companies are less than 10 miles apart it is relatively easy to have discussions like Gluon.  

How many more discussion are AWS and Microsoft having that we don’t hear about?