Friday, June 23, 2017

chart: Profit / Maintenance

How to Get More Cash Cows - Michael Hyatt


How to Fire a Monster Client: The Steps - Michael Hyatt

AI: Google MobileNets

Google Released MobileNets: Efficient Pre-Trained Tensorflow Computer Vision Models

"Google released several efficient pre-trained computer vision models for mobile phones in the Tensorflow Github repository. Developers can choose from several models that differ in the amount of parameters, computations for processing one image, and accuracy. The smallest model has 14 million "multiply and add operations" (MACs). Their largest model has 569 MACs. The more computations a model has to perform to predict the class of an image, the more battery power the phone uses.

Processing images on the smartphone itself is faster than uploading images to an online processing service. Is also means that no data has to leave the smartphone, ensuring the privacy of the user. The models are open source, developers can either download them directly or tweak them to meet their specific needs."



Wednesday, June 21, 2017

AI: Google for Jobs

LinkedIn is de-facto social network for jobs, with search features.
Google is now leveraging its search engine for job matching.

Official Google Webmaster Central Blog: Connect to job seekers with Google Search

"At Google I/O this year... announced Google for Jobs, a new company-wide initiative focused on helping both job seekers and employers, through collaboration with the job matching industry.
...
Get your job listings on Google. Implementation involves two steps:




AI future prediction

Here is a confident prediction from a professional technology futurist:

Will Artificial Intelligence Replace Human Intelligence, not just Our Processes? - Daniel Burrus

"So here is a prediction for you: During the next five years, we will have the technologies to transform every business process including how we sell, market, communicate, collaborate, train, educate, design, pay for things and much more. That is what I call a Hard Trend that will happen because it is based on future facts—the tools are real and they will be used to both disrupt and transform."


his new book:


Tuesday, June 20, 2017

Blockchain, Bitcoin



There is a lot of talk and investment recently around blockchain technology.

Blockchain - Wikipedia

Blockchain — What You Need to Know @HBR podcast

The Truth About Blockchain @HBR

IBM vs Microsoft: Two Tech Giants, Two Blockchain Visions - CoinDesk

Blockchain on Azure | Build 2017 | Channel 9

The Bitcoin Bubble: Deciphering Digital Currency | On Point

"If you bought a thousand dollars’ worth of Bitcoin in 2010, you’d be a multimillionaire today."

Processing Foundation: software + visual arts

Processing Foundation
"mission is to promote software literacy within the visual arts, and visual literacy within technology-related fields — and to make these fields accessible to diverse communities. Our goal is to empower people of all interests and backgrounds to learn how to program and make creative work with code"

in Java, JavaScript, Python

Saturday, June 17, 2017

AI startup studio: All Turtles

A new startup incubator by co-founder and CEO of Evernote Phil Libin
"Product first, not company first". Interesting approach.
The "Turtles" is a metaphor on "recursive definition", "turtles all the way down"

All Turtles
"All Turtles is a better way to build early-stage companies.
We work with founders to get from idea to pilot to product."
Process Chart

The focus is mostly on AI "bots"

Meet the first 8 startups backed by AI studio All Turtles | VentureBeat | Bots | by Khari Johnson
“We’re inspired by the modern generation of integrated content studios: HBO, Netflix, Amazon,” said Libin in a LinkedIn post Monday. “They can swing for the fences with every new show because the feedback loops are tighter, making the process more repeatable. They attract the most talented creators by letting them focus on making the best content with as little distraction as possible. We want to do the same for product creators. Focus on making the product, and we’ll help with everything else: AI expertise, design, data, HR, marketing, IP, analytics, distribution.”

Friday, June 16, 2017

Oracle: "Bare Metal Cloud Services"

"Late to cloud game", Oracle has interesting "spin" to it:
get more performance and security by skipping virtual machines, and still using containers.
Enterprise "lift and shift" then maybe transform as needed later.
Oracle claims offering identical hardware solutions on premise, hybrid and cloud.
Quite different from Azure and AWS platforms.

Bare Metal Cloud Services | Oracle Cloud

Architecture | Oracle Cloud


What Makes Oracle's IaaS Cloud Platform Unique - YouTube

A 360-degree Overview of Oracle Bare Metal Cloud OOW16 - YouTube


Docker and Container Apps on Oracle Bare Metal Cloud OOW16 - YouTube

Mark Hurd Talks Oracle Cloud With Bloomberg Business - YouTube

Oracle vs. Salesforce on AI: What to expect when | ZDNet


Amazon Fresh += Whole Foods !

High Tech + High Touch

Amazon is buying Whole Foods Market in $13.7-billion deal - LA Times

Amazon - Press Room - Press Release
"SEATTLE & AUSTIN, Texas--(BUSINESS WIRE)--Jun. 16, 2017-- Amazon (NASDAQ:AMZN) and Whole Foods Market, Inc. (NASDAQ:WFM) today announced that they have entered into a definitive merger agreement under which Amazon will acquire Whole Foods Market for $42 per share in an all-cash transaction valued at approximately $13.7 billion, including Whole Foods Market’s net debt."

Amazon is buying Whole Foods for $13.7 billion - Jun. 16, 2017



Amazon.com: : AmazonFresh

AmazonFresh | Start your FREE trial

Introducing AmazonFresh Pickup: Groceries delivered to your trunk - YouTube

Day in the Life - AmazonFresh - YouTube

Amazon is buying more than Whole Foods — it's getting 460 stores it can turn into warehouses and showrooms - LA Times

Amazon accounts for 43% of US online retail sales - Business Insider

Thursday, June 15, 2017

Wolfram|Alpha: ultimate AI answering machine

podcast interview: Stephen Wolfram: A New Kind of Data Science - The New Stack


"When it comes to scientific computing, few names are more well known than Stephen Wolfram. He was the creator of the Mathematica, a program that researchers have been using for decades to aid in their computations. Later Wolfram expanded Mathematica into a full multi-paradigm programming language, called Wolfram Programming. The company also packaged many of the Mathematica formulas, and a lot of outside data, into a cloud-based service and API."

be a seed for $ Trillion AI business predicted?
"THE WORLD'S FIRST TRILLIONAIRES ARE GOING TO COME FROM SOMEBODY WHO MASTERS AI."

It is a private research company but used by Apple for Siri. A big deal right there. 
Apparently it has a great set of products, and is in need of good sales. 
Maybe Microsoft, SalesForce, Amazon, Apple, or even Google?
It is a great tool! For example, it would be a phenomenal addition to MS Office :)





Amazon HW: Dash Wand with Alexa voice

While nobody was looking, Amazon become a biggest online store...
Then the first and largest public computing cloud provider
Then the primary tablet reader maker
Then the most prominent AI voice-powered gadget maker.
...

Amazon’s new Alexa-enabled Dash Wand is basically free for Prime subscribers - The Verge
"Amazon has released the Dash Wand, a new Alexa-enabled device that can help you scan grocery barcodes, convert measurements, and order household essentials from Amazon just by using your voice. The Wi-Fi-enabled Dash Wand is magnetic, so you can stick it on your fridge, and also offers some of the features of its bigger Echo sibling, allowing you to find recipes and restaurants without using your hands."

Wednesday, June 14, 2017

Azure Cosmos DB vs Amazon DynamoDB


Amazon DynamoDB vs. Microsoft Azure Cosmos DB Comparison

Amazon Aurora vs. Microsoft Azure Cosmos DB Comparison

Google Cloud Spanner vs. Microsoft Azure Cosmos DB Comparison

A technical overview of Azure Cosmos DB | Blog | Microsoft Azure
"Azure Cosmos DB is Microsoft’s globally distributed, horizontally partitioned, multi-model database service. The service is designed to allow customers to elastically (and independently) scale throughput and storage across any number of geographical regions. Azure Cosmos DB offers guaranteed low latency 99.99% high availability, predictable throughput, and multiple well-defined consistency models. "


CosmosDB - YouTube (Microsoft Channel 9)

CosmosTech_3CosmosTech_4

Monday, June 12, 2017

IoT: AWS Greengrass: scripts for devices & cloud

Fancy name "cloud functions" for what essentially are good old scripts. 
Thanks for performance improvements, both in hardware and software,
the original promise of Java is being realized: write once, debug everywhere :)

AWS Greengrass Runs Lambda Functions on IoT Devices @InfoQ
"Amazon has made available AWS Greengrass, a solution that allows developers to run Lambda functions on IoT devices and enable devices to communicate to each other and the cloud.
Built on AWS IoT and AWS Lambda, AWS Greengrass enables IoT devices to perform local computation, to communicate to the AWS cloud and to each other."

AWS Greengrass – Embedded Lambda Compute in Connected Devices - Amazon Web Services
"Local compute, messaging, data caching, and synch capabilities for connected devices.
Run IoT applications seamlessly across the AWS cloud and local devices using AWS Lambda and AWS IoT."
Diagrams_greengrass-core

"Extend cloud intelligence to edge devices
...Build advanced analytics, machine learning, and artificial intelligence in the cloud and deploy to physical devices using IoT Edge."

Saturday, June 10, 2017

GraphQL vs REST API

REST API downfalls, and dawn of GraphQL – Otto von Wachter – Medium
"The basic premise of both GraphQL and Falcor is that the server exposes a comprehensive data schema to the client, and the client decides exactly what it needs. Unlike with discrete REST endpoints, all the data for any given UI (page) can be sent in one trip to the client.
Ultimately, GraphQL is the more flexible and complete solution of the two, while Falcor provides 
out-of-the-box simplicity and is GraphQL-like."



GraphQL vs REST: Overview | Phil Sturgeon

Is GraphQL The End of REST Style APIs? | Nordic APIs |

Netflix Falcor: One Model Everywhere (JavaScript data library)
GraphQL Logo.svg


GitHub GraphQL API is Out of Early Access @ InfoQ

"Announced at GitHub Universe last year, GitHub GraphQL API aims to add more flexibility to GitHub API. The main advantage of GraphQL is its ability to define exactly what data are required, which makes it possible to replace multiple REST request with a single call. Additionally, GraphQL schemas are strongly typed and introspective."


Introducing GitHub Marketplace and more tools to customize your workflow @ GitHub

GitHub API | GitHub Developer Guide @ GitHub

GraphQL  spec, by Facebook, @GitHub

GraphQL - Wikipedia

GraphQL | A query language for your API

Code | GraphQL


From REST to GraphQL (Marc-Andre Giroux) - Full Stack Fest 2016 - YouTube

Zero to GraphQL in 30 Minutes – Steven Luscher - YouTube

Apollo GraphQL - YouTube





AI: Apple Core ML

Apple Announces Core ML: Machine Learning Capabilities on Apple Devices @ InfoQ

"At WWDC 2017 Apple announced ways it uses machine learning, and ways for developers to add machine learning to their own applications.
Their machine learning API, called Core ML, allows developers to integrate machine learning models into apps running on Apple devices with iOS, macOS, watchOS, and tvOS. Models reside on the device itself, so data never leaves the device."

"Supported machine learning tools are Keras (with Tensorflow backend), Caffe, Scikit-learn, libsvm and XGBoost. It is not possible to import an existing Tensorflow model into Core ML, which would be possible with Tensorflow Lite on Android."


Core ML integrates a trained machine learning model into your app.

The machine learning stack



Is Core ML related to Apple's acquisition of Turi last year?
Apple execs explain why the tech giant acquired machine learning startup Turi – GeekWire

While typically used from Python, Turi's GraphLab ML toolkit is written in C++,
so Apple could have embedded in the Core ML to be used from any supported language.

Is TensorFlow better than other leading libraries such as Torch/Theano? - Quora

Amazon goes open source with machine-learning tech, competing with Google’s TensorFlow – GeekWire

Microsoft/CNTK: Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit




Thursday, June 08, 2017

Domino's Pizza > Amazon, Google, Facebook, Apple

Domino's (DPZ) stock has outperformed Google (GOOG), Facebook (FB), Apple (AAPL), and Amazon (AMZN) this decade — Quartz

"In an incredible feat for a pizza company, Domino’s share price growth has outperformed all of the world’s largest tech companies so far this decade. An investment in Domino’s at the start of 2010 has grown by more than 2,000% to date, leaving the likes of Amazon, Google, Facebook, and Apple in the dust."

Domino's stock price growth vs. Big Tech

Failure IS An Option: Patrick Doyle, President & CEO – Domino’s 
“How to Transform a Legacy Company into a Technology-Enhanced, Nimble, Category-Disrupting Machine: What’s Needed? An appetite for risk And more importantly: The stomach for it"


How Domino’s Pizza Reinvented Itself @ HBR
"Domino’s is not just in the pizza-making business,
but in the pizza-delivery business,
which means it has to be in the technology business."

Domino's moves online ordering from AWS to Azure - Software - iTnews
"The retailer recently made the decision to take the OneDigital system out from AWS globally and shift it onto the Microsoft Azure cloud technology. While the majority of its core platforms will remain in AWS, late last year the pizza chain decided to move its .NET proprietary OneDigital platform into Microsoft Azure PaaS globally. OneDigital is the online ordering platform that is used by all Domino’s markets across the globe to process orders... Big pieces of work included a rewrite of the service layer given the move from SQL Server in AWS to DocumentDB in Azure"

Azure Service Bus Messaging Labs



Wednesday, June 07, 2017

Azure IoT Edge

By using containers, Azure IoT Edge enables migration of functionality between "cloud" and "cloud edge". Original promise of Java, realized in a bit more generic way. 

Azure IoT Edge | Microsoft Azure

"IoT Edge provides easy orchestration between code and services, so they flow securely between cloud and edge to distribute intelligence across IoT devices."

"Extend cloud intelligence to edge devices
  • Run artificial intelligence at the edge
  • Perform edge analytics
  • Deploy IoT solutions from cloud to edge
  • Manage devices centrally from the cloud
  • Operate with offline and intermittent connectivity
  • Enable real-time decisions
  • Connect new and legacy devices
  • Reduce bandwidth costs"
Azure IoT Edge | Build 2017 | Channel 9

Azure Cosmos DB Graph APIs

Introduction to Azure Cosmos DB Graph APIs | Microsoft Docs
Azure Cosmos DB graph architecture
Graph language "Gremlin"

TinkerPop3 Documentation


"A graph’s structure is the topology formed by the explicit references between its vertices, edges, and properties. A vertex has incident edges. A vertex is adjacent to another vertex if they share an incident edge. A property is attached to an element and an element has a set of properties. A property is a key/value pair, where the key is always a character String. The graph structure API of TinkerPop3 provides the methods necessary to create such a structure. The TinkerPop graph previously diagrammed can be created with the following Java 8 code. Note that this graph is available as an in-memory TinkerGraph using TinkerFactory.createClassic()."














Graph graph = TinkerGraph.open(); (1) Vertex marko = graph.addVertex(T.label, "person", T.id, 1, "name", "marko", "age", 29); (2) Vertex vadas = graph.addVertex(T.label, "person", T.id, 2, "name", "vadas", "age", 27); Vertex lop = graph.addVertex(T.label, "software", T.id, 3, "name", "lop", "lang", "java"); Vertex josh = graph.addVertex(T.label, "person", T.id, 4, "name", "josh", "age", 32); Vertex ripple = graph.addVertex(T.label, "software", T.id, 5, "name", "ripple", "lang", "java"); Vertex peter = graph.addVertex(T.label, "person", T.id, 6, "name", "peter", "age", 35); marko.addEdge("knows", vadas, T.id, 7, "weight", 0.5f); (3) marko.addEdge("knows", josh, T.id, 8, "weight", 1.0f); marko.addEdge("created", lop, T.id, 9, "weight", 0.4f); josh.addEdge("created", ripple, T.id, 10, "weight", 1.0f); josh.addEdge("created", lop, T.id, 11, "weight", 0.4f); peter.addEdge("created", lop, T.id, 12, "weight", 0.2f);


Alternative, a bit simpler to use, graph query language is Cypher from Neo4j.
graph databases - Neo4j - Cypher vs Gremlin query language - Stack Overflow



jbmusso/gremlin-javascript: JavaScript graph database client for TinkerPop3 Gremlin Server @GitHub
client.execute('g.V().has("name", name)', { name: 'Alice' }, (err, results) => {
  if (err) return console.error(err);
  console.log(results);
})

The Gremlin Graph Traversal Language @ SlideShare

Azure Cosmos DB: NoSQL capabilities everyone should know about | Build 2017 | Channel 9



How to build globally-distributed, fast, billion-user applications with Azure Cosmos DB | Build 2017 | Channel 9