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Tuesday, April 23, 2019

P&G Direct to Consumer Very Quickly Growing

GMA Smartbrief quotes CNBC:
P&G CFO: Direct-to-consumer category is "very quickly growing"
(Procter & Gamble)

Procter & Gamble is working to ensure its products are in all shopping channels, and it is considering the direct-to-consumer market an area of opportunity, said Chief Financial Officer Jon Moeller. "Direct-to-consumer itself is still a relatively small segment of the overall market; I would estimate less than 2%. That doesn't mean it's not relevant -- it's very quickly growing, and it's something we're increasingly competing in," he said.  ... ."

Waymo to Build L4 Autonomous Cars in Detroit

A move ahead it seems.  Coming soon to a road near you?  We note that Waymo is part of Google via Alphabet.

Waymo will build its self-driving vehicle fleet in Detroit
The company will repurpose an existing facility in Motor City.

By Amrita Khalid, @askhalid in Engadget

Waymo will build its autonomous vehicles in Detroit. CEO John Krafcik wrote Tuesday in a Medium post that the company will repurpose an existing facility in Motor City with the goal of being operational by mid-2019. Back in January, the company announced it had chosen Southwest Michigan as the location of its new facility for the mass production of L4 autonomous vehicles, the first of its kind in the world.

The company will create anywhere between 100 to 400 jobs as a result of the venture, according to The Detroit Free Press. Waymo will also receive incentives from the Michigan Economic Development Corporation. ... " 

So what is the definition of a Level 4 Autonomous car?  From the Wikipedia:

" ... Level 4 ("mind off"): As level 3, but no driver attention is ever required for safety, e.g. the driver may safely go to sleep or leave the driver's seat. Self-driving is supported only in limited spatial areas (geofenced) or under special circumstances, like traffic jams. Outside of these areas or circumstances, the vehicle must be able to safely abort the trip, e.g. park the car, if the driver does not retake control. ... " 

Level 5 is what might be considered fully autonomous;   'Steering wheel optional' ... "   

And in the Skies:     Google Wing Drones FAA Approved for US home deliveries

Market Basket Analysis

Some of the very earliest analysis (1970s) we supported in the enterprise were variants on market basket analysis.    So I was pleased to find this relatively simple example posted in DSC, by Ayumi Owada,  here using Apriori in Python.   Every marketing person should know of this capability, answering the question: What do people buy with this?

Maximizing Sales with Market Basket Analysis    Posted by Ayumi Owada  

Sales data analyses can provide a wealth of insights for any business but rarely is it made available to the public. In 2018, however, a retail chain provided Black Friday sales data on Kaggle as part of a Kaggle competition. Although the store and product lines are anonymized, the dataset presents a great learning opportunity to find business insights! In this post, we’ll cover how to prepare data, perform basic analysis, and glean additional insights via a technique called Market Basket Analysis.

Let’s see what the data looks like. We use Pivot Billions to analyze and manipulate large amounts of data via an intuitive and familiar spreadsheet style. After importing, we see that the data contains over 500K rows at the bottom, along with example data for each column.  ... "

Cloaking Resource Operations Data in the Cloud

Fascinating play.  How this differ from methods like blockchains?  Maybe better than BC methods?

Creating a Cloak for Grid Data in the Cloud   By Argonne National Laboratory 

Delivering modern electricity is a numbers game. From power plant output to consumer usage patterns, grid operators juggle a complex set of variables to keep the lights on. Cloud-based tools can help manage all of these data, but utility owners and system operators are concerned about security. That concern is keeping them from using the cloud—a collective name for networked Internet computers that provide scalable, flexible, and economical computing power.

Scientists at the U.S. Department of Energy's Argonne National Laboratory are developing and deploying tools to facilitate cloud computing for grid operations and planning. A framework being developed at Argonne masks sensitive data, allowing grid operators to perform complex calculations in the cloud to determine where and when to dispatch resources. By facilitating these calculations without compromising data security and integrity, the framework helps grid operators take the electricity system into the future while avoiding costly investments in computer infrastructure. ... " 

Prescribing Fruits and Veggies

A clever idea, well worth a trial.   Though there is usually no direct joy in prescriptions,  unless they directly kill pain, so I wonder that they feed into the immediate gratification that comes from less than healthy food.   Not the same as cash payment.   Will track progress.    Read more of the expert comments in the link.

Giant Food to fill prescriptions for fruits and veggies in Retailwire   by George Anderson

Giant Food has announced that it is participating in a single-store pilot program in Washington, DC that will allow Medicaid beneficiaries suffering from diet-related chronic illnesses to receive a $20 coupon at the pharmacy to buy fresh fruits and vegetables in the produce section if they bring a doctor’s prescription.

The program, which kicks off tomorrow, is run in concert with DC Greens, a local nonprofit dedicated to giving the city’s residents access to healthy foods.  

“We believe that cross-sector partnerships are the only way to achieve health equity in our city,” said Lauren Shweder Biel, executive director of DC Greens, in a statement. “Doctors and patients both need more tools to address food insecurity and diet-related chronic illness. Through Produce Rx, our healthcare system can be a driver to get patients access to the healthy food that they want and need.”
.... '

Process Mining

A mostly historical look at process mining.    Not a convincing enough view of why you should use it,  and in particular link it to AI.   Also its need to actual know the process, in other words model it, both current and proposed, and its links to BPM.   We did to great success. 

What Process Mining Is, and Why Companies Should Do It
Thomas H. Davenport, Andrew Spanyi in the HBR  ....

Monday, April 22, 2019

Can a Computer Write a Script? Or an Ad? Or Manage a Marketing plan?

A writer of ads, or a manager of marketing plans learns what works based on results in context.  So why not?      The idea of 'a script' was used in the earliest days of AI to create directions and goals to forge results.  We did parts of what is described here to efficiently fit ads into TV and radio slots.  The idea is not far away.  And a marketing plan is a known process based on data, so use it to deliver.

Can a Computer Write a Script? Machine Learning Goes Hollywood   By Los Angeles Times 

The idea of using machine learning programs to help write scripts and other tasks is becoming increasingly popular in Hollywood.

Entertainment companies are using the technology to color-correct scenes, identify popular themes in book adaptations, and craft successful marketing campaigns.

In addition, talent agencies are using the technology for suggestions on how to market actors and actresses.

Machine learning can provide vast amounts of data on why certain movies or TV shows work and why others fail.

Last year, the Entertainment Technology Center presented analysis showing correlations between a movie's story structure and how well it performed worldwide at the box office.

For example, films that led with action sequences did more than 13 times better at the box office on average than films that started with memory sequences.

Machine learning can also identify which stories are resonating online, pinpointing specific scenes or characters about which viewers are most passionate. .... " 

Accoustical Watermarking and the Second Screen

And yet more on context switching for the voice assistant.    Here work by Amazon, to be presented at an upcoming conference.   Originating from work to ignore 'wake words' in 'second screens' from other media.  Which seems to work quite well now.   But immediately made me think of:  Why not include more data in the watermark to identify it further, transmit information it learns about a context.  Nice direction.

Audio Watermarking Algorithm Is First to Solve "Second-Screen Problem" in Real Time   By Yuan-yen Tai

Audio watermarking is the process of adding a distinctive sound pattern — undetectable to the human ear — to an audio signal to make it identifiable to a computer. It’s one of the ways that video sites recognize copyrighted recordings that have been posted illegally.

To identify a watermark, a computer usually converts a digital file into an audio signal, which it processes internally. If the watermark were embedded in the digital file, rather than in the signal itself, then re-encoding the audio in a different file format would eliminate the watermark.

Watermarking schemes designed for on-device processing tend to break down, however, when a signal is broadcast over a loudspeaker, captured by a microphone, and only then inspected for watermarks. In what is referred to as the second-screen problem, noise and interference distort the watermark, and delays from acoustic transmission make it difficult to synchronize the detector with the signal. 

At this year’s International Conference on Acoustics, Speech, and Signal Processing, in May, Amazon senior research scientist Mohamed Mansour and I will present a new audio-watermarking algorithm that effectively solves the second-screen problem in real time for the first time in the watermarking literature.   .... "

From Web to Blockchain

Fascinating historical view of the Web, is the blockchain a natural architectural extension?

Moving Towards web3.0 Using Blockchain as Core Tech  By Shahid Shaikh

The invention of Bitcoin and blockchain technology sets the foundations for the next generations of web applications. The applications which will run on peer to peer network model with existing networking and routing protocols. The applications where centralized Servers would be obsolete and data will be controlled by the entity whom it belongs, i.e., the User.

From Web 1.0 to Web 2.0
As we all know, Web 1.0 was static web, and the majority of the information was static and flat.  The major shift happened when user-generated content becomes mainstream. Projects such as WordPress, Facebook, Twitter, YouTube, and others are nominated as Web 2.0 sites where we produce and consume verity of contents such as Video, Audio, Images, etc.

The problem, however, was not the content; it was the architecture. The Centralized nature of Web opens up tons of security threats, data gathering of malicious purpose, privacy intrusion and cost as well.

The invention of Bitcoin and successful use of decentralized, peer to peer, secure network opens up the opportunity to take a step back and redesign the way our web works. The blockchain is becoming the backbone of the new Web, i.e., Web 3.0.  .... "

Another Amazon Go Store

Why is Amazon building brick-and-mortar locations?   In Supermarketnews:

Amazon adds to physical retail footprint with latest Go store
Jeff Bezos highlights importance of brick-and-mortar locations to shareholders  By Russell Redman

Moving ahead with its brick-and-mortar expansion, Amazon.com Inc. this week opened a new Amazon Go cashierless store in San Francisco, its 11th overall.

Located at 575 Market St., the 1,750-square-foot store marks the third Amazon Go in the city. Customers can choose from an array of ready-to-eat breakfast, lunch, dinner and snack options made by the store’s kitchen or brought in from favorite local kitchens and bakeries.  .... " 

Wake Words for Assistance Context

Been experiencing the strange concept of a 'wake word' for a few years now.   Its means of switching context ... saying that after I say this special word or phrase, you can interpret everything I said afterwards as special, like a command.  My Echos and Google Homes and Siri do that.  Sometimes well, some times not.  And if there are multiple devices, what if several 'wake'?

  It seems that some devices, in certain places, can do it better or worse, leading to misinterpretation. Sometimes this is annoying, even dangerous.   I have set timers, and when I didn't carefully wait for a confirmation, discovered they were not set.   Its about the acoustics and expectations, I understand,  like when you are talking to people.  This technical article shows there is lots going on with the wake word now:

Using Wake Word Acoustics to Filter Out Background Speech Improves Speech Recognition by 15%   By Xing Fan  Amazon Alexa.

One of the ways that we’re always trying to improve Alexa’s performance is by teaching her to ignore speech that isn’t intended for her. 

At this year’s International Conference on Acoustics, Speech, and Signal Processing, my colleagues and I will present a new technique for doing this, which could complement the techniques that Alexa already uses.

We assume that the speaker who activates an Alexa-enabled device by uttering its “wake word” — usually “Alexa” — is the one Alexa should be listening to. Essentially, our technique takes an acoustic snapshot of the wake word and compares subsequent speech to it. Speech whose acoustics match those of the wake word is judged to be intended for Alexa, and all other speech is treated as background noise.

Rather than training a separate neural network to make this discrimination, we integrate our wake-word-matching mechanism into a standard automatic-speech-recognition system. We then train the system as a whole to recognize only the speech of the wake word utterer. In tests, this approach reduced speech recognition errors by 15%.

We implemented our technique using two different neural-network architectures. Both were variations of a sequence-to-sequence encoder-decoder network with an attention mechanism. A sequence-to-sequence network is one that processes an input sequence — here, a series of “frames”, or millisecond-scale snapshots of an audio signal — in order and produces a corresponding output sequence — here, phonetic renderings of speech sounds.  ... "

Decreasing Drilling Costs

Subsurface data is voluminous and complex.   So why not look at it to determine patterns of value?  AI today can be defined as looking for patterns of data that can be used to improve value in process.  Here is an excellent example.  Its not JUST about finding valuable things in patterns, its about finding better ways to make better use of them.   Less costly and more efficiently.   And putting in place a data collection and analysis method for future improvement.

Total Plans to Use Artificial Intelligence to Cut Drilling Costs in SupplychainBrain
Total SA plans to start a digital factory in the coming weeks to tap artificial intelligence in a bid to save hundreds of millions of dollars on exploration and production projects, according to an executive.

The use of artificial intelligence to screen geological data will help identify new prospects, and shorten the time to acquire licenses, drill and make discoveries, Arnaud Breuillac, head of E&P, said at a conference organized by IFP Energies Nouvelles in Paris on Friday. It will also help optimize the use of equipment and reduce maintenance costs, he said.

The digital factory will employ between 200 and 300 engineers and build on successful North Sea pilot projects, Chief Executive Officer Patrick Pouyanne said at the same event. It will also be a way to attract “young talent” to the industry.  .... "

Data Science Mistakes with the IOT

Good, short and non-technical article.  Obvious and useful.   And I as I often add, carefully map the business process,  get decision makers involved early and often.

Don’t Make These Data Science Mistakes in IoT  in Datanami by Alex Woodie

Data science is tough enough already. Whether you’re looking to act upon data collected from IoT sensors or human generators, don’t make it harder than it has to be by making these three common data science mistakes.

Failure, unfortunately, is not unusual when it comes to big data and data science — and it’s even more troublesome when dealing with large amounts of sensor data from the Internet of Things. When you consider the number of organizations with data science practices versus those that are getting a positive return on investment, it’s clear that many (if not most) organizations struggle to bring it all together before finding repeatable recipes for monetizing data. .... "

Self Driving Expectations

Was recently interviewed on exactly this question.   When?   And what will the phrase include?    Good piece.

Are we There Yet?  A Reality Check on Self-Driving Cars in Wired by Alex Davies

READ THE BREATHLESS articles and bold tweets and you could be forgiven for thinking that the fully autonomous vehicle is around the corner, with a collision- and congestion-free future riding shotgun.

Prepare for disappointment. A decade of massive investment in robocar tech has spawned impressive progress, but the arrival of a truly driverless car—the car that can go anywhere anytime, without human help—remains delayed indefinitely. Despite Elon Musk's self-assured claim that Teslas will have “full self-driving” capability by the end of 2020, the world is too diverse and unpredictable, the robots too expensive and temperamental, for cars to navigate all the things human drivers navigate now. Even John Krafcik, CEO of Waymo (the grown-up company that was Google's self-driving car project), agrees, saying last year, “Autonomy always will have some constraints.” .... '

AI Powered Home Tours

Something similar was suggested and tested to get data for plant maintenance by providing remote tours of key parts of facilities, then extracting data for simulations.  Or to document assets and inventory of facilities.

Virtually walk through dream homes with Zillow’s new A.I.-powered 3D home tours  in Digital Trends by Bruce Brown 

Home sellers and real estate agents listing properties on Zillow’s real estate marketplace now can add 3D tours for no charge to their listings. Zillow 3D Home uses artificial intelligence (A.I.) on an iOS mobile device app to create the tours with 360-degree panoramic photos taken in and around a home.

Zillow began testing the app in 2018. The impetus behind the project came from a survey report from Zillow’s research group that found 45% of Gen Z and 41% of Millennial home buyers stated 3D home tours and videos were very important or extremely important in their home buying decision process ... "

Sunday, April 21, 2019

5G and IoT Security

Will 5G play a role in IoT security? in 7wdata?

The Internet of Things (IoT) continues to grow as more and more devices, sensors, assets, and other "things" are connected and share data. Still, many remain concerned about the security threats and vulnerabilities of this environment -- whether it involves IoT networks, data, or the connected devices themselves.

Can 5G, the upcoming fifth generation of wireless mobile communications, help enhance the security of IoT?

IoT ecosystems can be especially appealing as the targets of attacks such as distributed denial of services (DDoS), in part because there are so many different components involved..... "

TensorFlow

Was asked this question recently.  Here a quick, non technical answer.  But does also include code, which is by its nature technical.

What is Tensorflow?

ODSC    https://opendatascience.com/  

It would be a challenge nowadays to find a machine learning engineer who has heard nothing about TensorFlow. Initially created by Google Brain team for some internal purposes, such as spam filtering on Gmail, it was open-sourced in 2015 and became the most popular deep learning framework in the next few years.

Tensorflow is often used for solving deep learning problems and for training and evaluating processes up to the model deployment. Apart from machine learning purposes, TensorFlow can be also used for building simulations, based on partial derivative equations. That’s why it is considered to be an all-purpose tool for machine learning engineers.  ... " 

Don't Panic about the Digital Revolution

I like to think about the future as having a history, that way we can connect it to other (past) history.  Will we be able to find patterns in each to prepare?

Don’t Panic: The Digital Revolution Isn’t as Unusual as You Think  in Knowledge@wharton
Apr 17, 2019 Books Business Radio Podcasts  North America

Former FCC chair Tom Wheeler discusses his new book, which places the current digital revolution into context with other periods of game-changing innovations.

The digital revolution has dramatically changed life on Earth, making it easy to think we’re living in the greatest time of innovation. But a new book by Tom Wheeler, former chairman of the Federal Communications Commission, is a reminder that remarkable change has happened many times before. The invention of the printing press in the 15th century created upheaval and reorganized everything in society, as did the subsequent inventions of the telegraph, telephone and railroad. From Gutenberg to Google: The History of Our Future is an insightful look at the development of networks, the physical links that bind people together. Wheeler, a visiting fellow at the Brookings Institution, recently joined the Knowledge@Wharton radio show on SiriusXM to talk about why history often repeats itself. (Listen to the podcast at the top of this page).

An edited transcript of the conversation follows.  .... "

Military Aviation Automation Operations

Though we are still working with pilots interacting with systems, as apparently happened in the recent 737 systems.   We will soon have to consider many such collaborative systems.

Aviation Automation Climbs New Heights With ALIAS 
Federal Computer Week   By Lauren C. Williams

The U.S. Defense Advanced Research Projects Agency (DARPA)'s Aircrew Labor In-Cockpit Automation System (ALIAS) project aims to develop autonomous artificial intelligences (AIs) to improve flight safety and performance in battlefield operations. ALIAS' goals include producing a customizable, drop-in, removable kit so fewer onboard crew members will be needed on military aircraft. With its initial fly-by-wire experiment led by Sikorsky scheduled for completion in May or June, ALIAS would enable advanced automation to be added to existing aircraft. DARPA in 2016 proved the effectiveness of the effort's sensory and avoidance capabilities with a Cessna 172G aircraft, approaching an unmanned aerial system from multiple angles. DARPA's Lt. Col. Philip Root said once a fly-by-wire AI has been successfully demonstrated, "we can begin adding the autonomy flight controls—operating in the background like a lane assist [feature in cars that helps] the human operator avoid a tree."

Saturday, April 20, 2019

AI Impact on Demand Forecasting

Good short piece,  makes good points about what is needed, and should be expected.  I have taught forecasting in the enterprise, and its more about how the forecast is used than what it is.   You would love to have it perfect, but it will not be.   AI provides another useful component.

Is AI’s impact on demand forecasting more hype than reality?   by Nikki Baird in Retailwire

Through a special arrangement, presented here for discussion is a summary of a current article from the blog of Nikki Baird, VP of retail innovation at Aptos. The article first appeared on Forbes.com.

The forecast error in retail is as high as 32 percent, according to some estimates. Will artificial intelligence (AI) technology do any better?

AI promises to change the way demand forecasting works in retail in six key ways, but those promises include a bit of hype:  .... " 

Wing Delivers from Drones in Australia

Have not seen it in the US except for specialty examples, but Alphabet is doing it in Australia.

Wing Officially Launches Australian Drone Delivery Service in IEEE Spectrum

After years of testing, Wing is now offering consumer drone delivery to select Australian suburbs   By Evan Ackerman

This drone can deliver your morning coffee directly to your house. But is that something people really want?

Alphabet’s subsidiary Wing announced this week that it has officially launched a commercial drone delivery service “to a limited set of eligible homes in the suburbs of Crace, Palmerston and Franklin,” which are just north of Canberra, in Australia. Wing’s drones are able to drop a variety of small products, including coffee, food, and pharmacy items, shuttling them from local stores to customers’ backyards within minutes.    ..... "

Overpromise of AI for Healthcare?

IBM has created lots of interesting pieces of the solution, but not the harder solution of the broader process involved.   Can these be connected into big value?  And Hype has an element as well.   Not too dissimilar from what happened in the previous AI solutions in the 80s,  healthcare solutions emerged quickly to ultimately retract.  Good article:

How IBM Watson Overpromised and Underdelivered on AI Health Care
After its triumph on Jeopardy!, IBM’s AI seemed poised to revolutionize medicine. Doctors are still waiting   By Eliza Strickland in IEEE Spectrum

In 2014, IBM opened swanky new headquarters for its artificial intelligence division, known as IBM Watson. Inside the glassy tower in lower Manhattan, IBMers can bring prospective clients and visiting journalists into the “immersion room,” which resembles a miniature planetarium. There, in the darkened space, visitors sit on swiveling stools while fancy graphics flash around the curved screens covering the walls. It’s the closest you can get, IBMers sometimes say, to being inside Watson’s electronic brain.  ... " 

Automating Need Processes with RPA

An outline of the use of RPA in Contact centers.   A natural place because the customer establishes themselves as needing help.    But its use goes far beyond, to most any process.  Also clearly useful in an attentive assistant system, once its established the customer needs something.  See previous piece on Google moving in this direction.   Inserting need solution within need statement.

How is Robotic Process Automation in Contact Centers improving Customer Experience and Driving Profitability?   By Mitul Makadia - in CustomerThink

With the emergence and advent of RPA, enterprises are starting to see major growth in terms of savings and scaling of overall operations, however, when it comes to contact centers or call centers, robotic process automation offers invaluable advantages by providing solutions to challenges based around service, process & technology.

Customer satisfaction is a huge KPI for any business and call centers play a key role in shaping the success of that KPI. CSRs face immense demand to grow overall revenue by upselling & cross-selling, delivering fast, personalized and effective service – all while meeting high first call resolution and low average handling time goals. Yet, they happen to work with technology that slows them down and requires them to work with a myriad of slow & complicated applications while they speak with customers.

Although Business Process Management plays its part, the high levels of repetitive tasks within contact centers can only be circumvented through call center automation for better employee efficiency, customer satisfaction, and profitability.

Take a look at how Robotic Process Automation in Contact Centers is improving customer engagement and streamlining processes –  .... "

Google Focusing Context of Need Curation with Assistants

Is everything in Google turning into an ad-oriented assistant?    Into product curation?   Yes,  see how their fundamental service, search, has already turned that way.  I ask for help,  it gives me good results and then sets my information context to need what I searched for.   Having an assistant App, or an assistant device listening for my requested needs, is just another way to focus and set context for product curation.  Its always listening to get and set the context of our needs.

The massive Google shift you probably haven't noticed
 Android Intelligence   By JR Raphael, Contributing Editor, Computerworld 

Google is quietly repositioning the very foundation of its business — and if you aren't watching closely, this monumental move might be easy to miss.

The trend, in short, revolves around getting down to business — specifically, the business of making money off of you and me and everyone else who uses Google services. For a while now, y'see, Google has been focusing on new areas that don't directly fit in with the company's long-standing main business model. Google, as we all know, makes its money primarily from selling and showing ads that are custom-tailored to your interests at any given moment. But many of Google's newer services have remained mostly ad-free since their starts.

Sure, these services still collect data about us, which can then be used to better target ads in traditional web search and other such places — but more and more, we tech-loving Homo sapiens aren't using traditional web search to get all of our information, especially when we're on mobile devices or other modern-tech gizmos. In the longer-term future, if Google wants to keep its cash cow mooing, it's gotta find a way to replicate its ad system in other areas and keep its business model relevant to our evolving tech habits.  .... 

The bigger Assistant ad picture

The injection of ads directly into Assistant feels like a culminating step in a process we've been watching unfold for years. It's become increasingly clear over time that Assistant is turning into the central focus for almost everything Google does — and for good reason: As we all spend less time surfing the open web and more time using apps and connected devices, the future of the online ad industry is being threatened by irrelevance. The future, as the thinking goes, isn't in traditional box-on-a-page web search but rather in interacting with all the stuff around us. And if Google Assistant is the genie inside all that stuff, at the end of the day, we're all still Google customers. .... " 

Friday, April 19, 2019

Device Discovery in Smart Home Skills

Turned out this problem occurred recently in related applications.   Not fixing this kind of problem can lead to large scale problems.  Ultimately its all about seamless integration of knowledge and skills.  When you talk to someone you want to know what they  know and can they provide it in useful context.

4 Tips for Implementing Device Discovery in Your Smart Home Skills   By Roy Kincaid

Building an Alexa smart home skill enables you to link Alexa with your existing smart home device cloud. This gives your customers the ability to control and query their compatible devices through Alexa. When creating a smart home skill, one of the first steps is to implement the Alexa.Discovery interface.The Device Discovery process allows you to send Alexa a list of your customer’s devices and capabilities, so that they can interact with them through voice or the Alexa app.

When testing your implementation of the Alexa.Discovery interface, you first need to check that you've enabled the skill on your Alexa account and successfully performed account linking. The next step is to run device discovery from your Alexa account. If no endpoints are found from your skill, then you may have encountered a device discovery error. Here are four common culprits you can look into to resolve these errors.   ....  " 

Is AI Saving SAP

Had worked with them in the enterprise, and itt had come to mind that some of what SAP did could be done with clouds and automated efficient pattern analysis.    But the article does not really make the case that SAP is in trouble, but I might be worried.

Can artificial intelligence save SAP?  By Jason Bloomberg

There are persistent signs that all is not well in the land of SAP.

The German enterprise applications leader is in the midst of laying off thousands of people. Its cloud efforts have sputtered. Its product line confuses customers. HANA, the in-memory columnar database that was supposed to save the company, has been eclipsed by newer, more cloud-friendly players.

With the throng of cloud native enterprise resource planning providers nipping at SAP’s heels, it has found itself in need of game-changing innovation – and it looks like the company has moved its chips all-in on artificial intelligence.

Whether Leonardo, SAP’s core AI offering, will save the company is still an open question. Is it one more item on a too-long list of SKUs? Can it compete with the likes of IBM’s Watson or Salesforce’s Einstein, or any other AI product named after some smart dead white guy?  .... " 

Qubic for Process Anyone?

Am looking to do an application that will insert 'smart contract' type specifications to observed business process, focused by business process models. Anyone used IOTA's Qubic?   Qubic is still in development I know, but any early impressions or tests would be interesting.   Connect with me via my Linkedin contact.

" .... What is Qubic?
In short: Qubic began life as as an initialism-turned-acronym, QBC, which stands for quorum-based computation.

Quorum (distributed_computing) on wikipedia

Specifically, Qubic is a protocol that specifies IOTA's solution for quorum-based computations, including such constructs as oracle machines, outsourced computations, and smart contracts. Qubic provides general-purpose, cloud- or fog-based, permissionless, multiprocessing capabilities on the Tangle. In the long term, Qubic will allow people to leverage world-wide unused computing capacity for a myriad of computational needs, all while helping to secure the IOTA Tangle: an IOTA-based world supercomputer.

More generally, a qubic is what we call a packaged quorum-based computation that occurs according to the Qubic protocol. Below are some examples of different types of qubics - while they are distinguished here for clarity, they are all nevertheless variations on a single, general-purpose concept: the quorum-based computation, or qubic.  .... " 

Grief Examination via Interactive VR

Might we use gaming, or interactive storytelling to interact with our history?

Afterlife Is A Hard Hitting VR Experience Examining Grief, Coming In May
It'll support a range of VR headsets.
Peter Graham   

Award-winning multimedia studio Signal Space Lab announced work on a new interactive live-action experience called  Afterlife last year, aiming to create a deeply meaningful film looking at grief. The studio has just announced that it plans on releasing the film across several formats next month..... "

Clash of the Digital Platforms

Not a bad look at what exists,perhaps not enough usage to contextual use details.

The Clash Of The Digital Platforms: The 5-year Update
By James L. McQuivey, Vice President, Principal Analyst  Forrester

On March 7, 2014 I wrote a report called The Clash of the Digital Platforms in which I identified 5 companies that had a unique status in the world of technology, innovation, and overall business. The five companies were (alphabetically) Amazon, Apple, Facebook, Google, and Microsoft. In a byline piece I wrote for AdAge’s DigitalNext column later that month, I wrote:

Marketers Need to Pay Attention to the Battle of the Digital Titans

We’re barely into 2014 and already the biggest digital disruptors are either flexing their muscles anew or apparently getting ready. Google acquired Nest for $3.2 billion, Apple said it has nearly $160 billion in the bank, Amazon is reportedly close to shipping a set-top box for your TV, Microsoft has sold millions of its Xbox One game consoles and Facebook followed its announcement of a record quarter by spending billions to acquire WhatsApp.

It’s an intensifying battle of mythical proportions, and to faraway marketers and product managers in non-digital industries like banking, pharmaceutical or consumer packaged goods, it may seem not worth much thought — because there’s little they can do about it. (AdAge DigitalNext, March 20, 2014) .... "

Thursday, April 18, 2019

Free Graph Algorithms Book


My favorite analytics methods.

Hidden Data Patterns Only Relationships Can Find - Free O’Reilly Book

Graph analytics use relationships to reveal structural and predictive insights hiding in your data. Whether you are building dynamic network models, mitigating risk and fraud or forecasting real-world behavior.

Check out this great resource – just published today: The O'Reilly book, Graph Algorithms: Practical Examples in Apache Spark and Neo4j. Get your free copy now.

Pass this offer along to anyone on your team who would like to explore graph algorithm examples with working code and sample datasets for both Spark and Neo4j. Also included is a chapter on how graph algorithms enhance machine learning accuracy and precision.

Best,  Amy Hodler & Mark Needham, co-authors
@amyhodler & @markhneedham

Get your free copy now

Is it still about Paper Coupons?

Worked with paper coupon redemption analytics from the very beginning at very big CPG.   Is it about their physical nature?     Will there always be room for the  paper coupon?  Would not have guessed it, but the statistics still show it.

Will America’s love for paper coupons ever die?
by Guest contributor   MarketingCharts staff in Retailwire 

Through a special arrangement, presented here for discussion is a summary of articles from MarketingCharts, which provides up-to-the-minute data and research to marketers.

Despite a slight rise in the preference for paperless discounts, more adults still prefer paper coupons, according to the latest annual survey of coupon use from Valassis.

Fully half of adults in the U.S. prefer to get coupons in the mail, a figure that has continued to rise over the past three years. The proportion of respondents who prefer to get coupons from a coupon book found in a newspaper continues to rise as well, from 42 percent last year to 44 percent this year.

Some 42 percent agree that they prefer to get paperless discounts from the internet that they can download onto their store shopper/loyalty card. And even though a smartphone offers the convenience of carrying coupons anywhere, just 38 percent say they prefer paperless discounts on their smartphone/mobile device.  .... " 

WiFi as Hospitality, Retail Value

Now having experienced Wifi in Hospitality since its inception, I recall having a conversation with a Hotel Chain innovation group.  At the time they were unconvinced that Wifi had value, and there too many dangers.    Things have changed and continue to evolve.  Incentivizing repeat business.  Now a days I mostly wander through retailers checking stocking and possible product use, and the Wifi experience could be much better.  They need to make it very clean, and incentivize repeat business and value with the right data.  You are an edge of the retail IOT.  And how about making the edge more intelligent as an assistant?

Wi-Fi Without Reservations   By McCall Bunn in Cisco Blog

Partner Success Story

Providing high-quality Wi-Fi is an IT investment most businesses incur. Customers expect Wi-Fi at every destination. It is crucial to post pictures of appetizers, split checks, and look up the difference between ‘bucatini’ and ‘fettuccini’. It has become a necessity when dining out.

And a large hospitality group, previously known as Batali and Bastianich (B&B), with locations around the world, already knew this. Yet they had a problem offering quality connection in several of their Las Vegas restaurants. And, they were struggling to identify their customers. So, they came to a Cisco Solution Partner iValu8 for help.

B&B agreed to a one-month trial with iValu8 to pilot VivaSpotTM, a marketing campaign platform that runs over Wi-Fi, which then implements Cisco Meraki as the reliable and scalable way to power the solution.

Not only were their customers now able enjoy high-quality Wi-Fi during the trial, but they began to collect customer data to incentivize repeat business, gather feedback, and amplify the hospitality group’s social media presence. They could track the results in real-time and launch campaigns on any device from any location. And, free Wi-Fi became a key marketing assets.

With multiple locations around Las Vegas, VivaSpot also cross-promoted other properties of the hospitality group when customers logged-on to their current Wi-Fi. And the results? An overall increase in spend from customers’ during their stay at all of the properties.

The hospitality group found so much success with the pilot, they’re ordering more. They are bringing Cisco Meraki and iValu8’s VivaSpot to eleven different locations from NYC to LA. Taking the group from a one-month trial to over $100,000 in revenue.  ... "

DJ's Spin Code

I changed the title,  they will likely not write code in the future, they will create algorithms by some interface other than 'writing code'.   Coding, as it has developed, is far too inefficient and error prone.

DJs of the Future Don't Spin Records—They Write Code
in Wired  By Michael Calore

Artists in the underground electronic music culture are performing live-coding shows or "algoraves," in which they program software algorithms to create new forms of music. Musicians synthesize individual sounds on their computers, then direct the software to string those sounds together based on a set of predefined rules; the end product has the artist's signature, but is algorithmically sculpted. When the same routine is run again, the song will sound familiar and contain the same elements, but the composition will be structured differently. Performances often are enhanced with screens displaying the running code as trippy visuals. A popular venue for this emergent art form is the Algorithmic Art Assembly, a two-day festival in San Francisco ..... "

Spying on Your Smart Home

Have now had a smart home lab for a long time.  Could have used this for some time, in particular to understand how the home interacts with external contexts, like the car, the store, the Internet.  Like the idea.  So many things in the lab are IOT members.   Has to be marketing insight here.

Spy on Your Smart Home With This Open Source Research Tool 
In TechCrunch     By Natasha Lomas

Princeton University researchers have built an open source Web app that allows homeowners to monitor their smart home devices. The IoT Inspector is designed to help consumers analyze the network traffic of their Internet-connected appliances, mainly to determine whether those devices are sharing their information with third parties. The researchers said the IoT Inspector requires no special hardware or a complex setup, making it easy for consumers to deploy smart home monitoring. The team acknowledged it hopes to use data collected by the app to advance Internet of Things (IoT) research, including insights into privacy, security, and network performance risks of IoT devices. The researchers said the app can track the Internet activities of as many as 50 devices on a network. .... " 

Employee Surveillance is Data

Not an unexpected thing.  Its another form of data and is naturally part of efficiency considerations.  Even its 'architecture',  like those mentioned in recent silo readings, can be important to the accuracy of decisions being made.  Data exists in work contexts, decisions use data, which includes how people (and AIs) use that data.

Employee Privacy in the U.S. at Stake as Corporate Surveillance Technology Monitors Workers' Every Move     CNBC   By Ellen Sheng

The advent of technologies that let businesses track, overhear, and monitor employees on company time is raising issues about corporate surveillance. Gartner estimated last year that 22% of organizations worldwide in various sectors use employee-movement data, 17% track work-computer-usage data, and 16% access Microsoft Outlook or other calendar-usage data. Products of interest include Amazon's recently patented ultrasonic bracelet, which can localize warehouse employees and monitor their interaction with inventory bins via sound pulses. Meanwhile, last year Walmart patented a system for eavesdropping on workers and customers, which tracks employee "performance metrics" to ensure employees are on the job by listening for certain noises. Some makers of monitoring technologies are developing deployment guidelines to allay employer and employee privacy concerns, but advocates fear worker privacy could be compromised without appropriate regulation.  ... " 

Silo Syndrome

Its really always about silos.  The silos are formed in part by the data that exists within them.  But also more fundamentally by the trust that exists within decision making.    I have trust within a silo that makes decisions that influences agreed-to goals.   How might further automation change this?

Five-Fifty  in Mckinsey:
A quick briefing in five—or a fifty-minute deeper dive

In this edition:The silo syndrome  Working in silos can cause tunnel vision, tribalism, and weak corporate performance. What’s a silo-buster to do?  ... "

Wednesday, April 17, 2019

Automating Machine Learning with Azure

This example was sent to me, a straight forward example of using Azure.   Always looking for useful examples of better automating at least initial tests of a machine learning example.  Big proponent of quick, early,  cheap tests of even complex modeling efforts.      Look for ways to get the idea in front of other analysts, decision makers, data providers.   Even a sketch on a board is worthwhile, but showing something interactive gives a clear taste of the potential value.

How to forecast energy demand with Azure Machine Learning | Azure Makers Series
Use Azure Machine Learning to create a model and apply it to a real-world scenario: predicting energy demand and expected load on energy grids - a critical business operation for energy companies. The same principles apply across use cases, so you can adjust for your organization’s critical operations and needs.  

GitHub Repo: https://github.com/FrancescaLazzeri/A... 

Create your Azure free account: https://aka.ms/J1PxFdcK2tY

Follow Francesca on Twitter: https://twitter.com/frlazzeri

Faster and Smaller Neural Nets

Fascinating development.   Smaller usually means faster with training nets.   Smaller can also mean easier implementation at the IOT edge.  Now will they be as accurate?   It is all about more efficient perception.  Closer to human.   Technical piece in Google AI.  Intro below, more at the link:


MorphNet: Towards Faster and Smaller Neural Networks  in Google AI.   Wednesday, April 17, 2019

Posted by Andrew Poon, Senior Software Engineer and Dhyanesh Narayanan, Product Manager, Google AI Perception 

Deep neural networks (DNNs) have demonstrated remarkable effectiveness in solving hard problems of practical relevance such as image classification, text recognition and speech transcription. However, designing a suitable DNN architecture for a given problem continues to be a challenging task. Given the large search space of possible architectures, designing a network from scratch for your specific application can be prohibitively expensive in terms of computational resources and time. Approaches such as Neural Architecture Search and AdaNet use machine learning to search the design space in order to find improved architectures. An alternative is to take an existing architecture for a similar problem and, in one shot, optimize it for the task at hand.  .... " 

Distributed Ledger as new Enabler

Bold claim here in Supplychain Brain.

Why Supply Chain Technology Needs Blockchain
 Jon Kirkegaard, SCB Contributor

Blockchain: A New Enabler

" ... What’s encouraging is a growing wave of awareness of blockchain and distributed ledger technology (DLT). Interest in blockchain appears to be providing an avenue for the true scaling of real-world collaboration, by embracing decentralized technology, encrypted security and peer-to-peer networking technology.

Blockchain is increasingly being discussed in the context of supply chain, but the focus is often on the replacement of existing applications such as tracking. In my view, this is not where blockchain can be of the most value to the supply chain. The greatest need, and highest return on investment, lies with processes that can’t be automated using centralized technology.

As an example of this disconnect, despite decades of new supply-chain technology, as much as 90 percent of all real planning and coordination is still done via spreadsheet and e-mail. In particular, the coordination of S&OP build plans outside of one department or company is almost always carried out in that manner.

Perhaps you have witnessed in your organization attempts to deploy connected planning technology and kill the spreadsheet, in favor of one real-time instance of advanced planning and scheduling. Has that worked, or has it just created more underground use of spreadsheets, e-mails, whiteboards and conference calls?... "

Futurithmic

New, brought to my attention, short non-tech articles on advancing tech.  With some interesting embedded links.

How AI will change your shopping habits   By Christine Persaud

Artificial intelligence (AI) is influencing everything from photography to gaming, home entertainment, education and autonomous vehicles. AI is also reinventing the way we shop.

AI has the potential to impact many industries, from healthcare to manufacturing. The University of Waterloo is just one of many companies and institutions that has opened an AI institute dedicated solely to complex and detailed research on the technology’s applications.  ... " 

About Futurithmic

Our editorial mission is to explore the implications of emerging technologies on society, business, politics and the environment of tomorrow. We aim to inform and inspire through thoughtful research, responsible reporting, and clear, unbiased writing, and to create a platform for a diverse group of innovators to bring multiple perspectives.  ... " 

Machine Teaching

Nice thoughts here.   If we can learn we should be able to teach.


Deep Teaching: The Sexiest Job of the Future 
Carlos E. Perez   in Medium

Microsoft Research has a recent paper (Machine Teaching: A New Paradigm for Building Machine Learning Systems) that explores the eventual evolution of Machine Learning. The paper makes a clear distinction between Machine Learning and Machine Teaching. The authors explain that Machine Learning is what is practiced in research organizations and Machine Teaching is what will eventually be practiced by engineering organizations. The teaching perspective is not only different from the learning perspective, but there are obvious advantages in that concept disentanglement is known a priori ... "

See the Microsoft Paper mentioned.


Tuesday, April 16, 2019

Simulation is Very Useful for Analytics Validation

I am a long time proponent and practitioner of simulation methods.   We simulated plant design and process, warehouse operations,  woodland growth and management, consumer in aisle behavior, coffee roasting,  advertising selection and delivery ... and much more.   Always a good approach to validate prescribed analytics and AI.    It needs be better linked directly to analytical solutions.

Advance Your Process Improvements with Simulation Technology  in the APQC Blog  By Lochlyn Morgan  Posted in Process and Performance Management

I recently spoke with Luis Lopez, manager of process improvement at the Port of Vancouver, to discuss the role that simulation technology has in process improvement, advice on piloting simulation software, and a few lessons learned from his hands-on experience with simulation technology.

What role can simulation technology play in process improvement work?

Simulation technology plays an important role in the improvement of complex processes as it provides a non-invasive, risk-free, and cost-efficient method to identify and analyze the underlying factors that may contribute to poor process performance and evaluate potential improvements. Simulation technology is key when testing improvements in the real process can be very costly, risky or lengthy.

Simulation models also provide a great way to engage project teams in the design and development of process improvements. Advances in 3D graphics have made it relatively simple to make detailed 3D simulation models of an operational process. These 3D renderings allow project teams to quickly visualize their ideas and identify potential benefits and implementation barriers. This is why I like to say that “if one picture is worth a thousand words, an animated 3D simulation model in a process improvement project is worth a thousand pictures.”  .... " 

Google has an AI Cloud Platform. Lets link it with BPM

Quite some detail for making AI applications work with the cloud in this new production factory for AI in the Cloud.  I like the idea of standardizing such learning projects and installed solutions. I would also like to see this kind of work linked with business process models like BPM.

AI Platform

Create your AI applications once, then run them easily on both GCP and on-premises.

Take your machine learning projects to production

AI Platform makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively. From data engineering to “no lock-in” flexibility, AI Platform’s integrated tool chain helps you build and run your own machine learning applications.

AI Platform supports Kubeflow, Google’s open-source platform, which lets you build portable ML pipelines that you can run on-premises or on Google Cloud without significant code changes. And you’ll have access to cutting-edge Google AI technology like TensorFlow, TPUs, and TFX tools as you deploy your AI applications to production.  ... "

A testimonial they provide:

" ... In retail, it’s important to provide customers with easy access to alternative products or recommended add-ons. We train our own machine learning models with TensorFlow on Google Cloud ML, and we automate the periodic retraining of these models with Kubeflow Pipelines. Together with AI Hub, useful for sharing models between data scientists, we can now iterate faster on our models, and automatically deploy them to staging and production. ... '    Lucas Ngoo, co-founder, CTO, Carousell

See also: https://techcrunch.com/2019/04/10/google-expands-its-ai-services/

Mathematica Expands

Been a long time since I worked with Wolfram's Mathematica.  Was always impressed with what the package provided.  Especially useful for people that already have a math background.    Also good to let people/students with a strong interest in Math expand their mathematical powers.

They are coming up with a considerable update I have started to scan.  Lots of new descriptive documentation that looks good.  Now includes examples about how to do DeepLearning and blockchains with Mathematica.  The article below has a long description of the capabilities.

Version 12 Launches Today! (And It’s a Big Jump for Wolfram Language and Mathematica)
April 16, 2019 — By Stephen Wolfram  ... '

Predicting Sales Behavor in Real Time

Sales Prediction in real time.

6sense raises $27 million for its marketing and sales predictive analytics tool  By Manish Singh @REFSRC

6sense, a San Francisco-based startup that uses big data to predict in real time when people are looking to buy products, has raised $27 million to grow its marketing analytics tool.

The funding round was led by Industry Ventures, with existing investors Bain Capital Ventures, Battery Ventures, Costanoa Ventures, Salesforce Ventures, and Venrock also participating. 6sense, which described the new round as “growth funding following series B,” has raised $63 million to date.  .... " 

AI for the Diagnosis and Management of Eye Disease

Another example of the use of AI for healthcare management.  Considerable detail at the link.

A major milestone for the treatment of eye disease  in DeepMind
We are delighted to announce the results of the first phase of our joint research partnership with Moorfields Eye Hospital, which could potentially transform the management of sight-threatening eye disease.

The results, published online in Nature Medicine (open access full text, see end of blog), show that our AI system can quickly interpret eye scans from routine clinical practice with unprecedented accuracy. It can correctly recommend how patients should be referred for treatment for over 50 sight-threatening eye diseases as accurately as world-leading expert doctors.

These are early results, but they show that our system could handle the wide variety of patients found in routine clinical practice. In the long term, we hope this will help doctors quickly prioritise patients who need urgent treatment – which could ultimately save sight.

A more streamlined process
Currently, eyecare professionals use optical coherence tomography (OCT) scans to help diagnose eye conditions. These 3D images provide a detailed map of the back of the eye, but they are hard to read and need expert analysis to interpret.

The time it takes to analyse these scans, combined with the sheer number of scans that healthcare professionals have to go through (over 1,000 a day at Moorfields alone), can lead to lengthy delays between scan and treatment – even when someone needs urgent care. If they develop a sudden problem, such as a bleed at the back of the eye, these delays could even cost patients their sight. .... " 

Monday, April 15, 2019

On Automated Help

Our own work in this space often touched on this:   A person does like to talk to a clear, knowledgeable person who can solve our problem quickly and directly.   But in what context would they live with less than that?   And how does that alter their later commercial behavior regarding the service?   Quite an important issue for any assistant role.

In HBS Working Knowledge.  An infographic style look at ongoing research. With some backup statistical results.

Infographic: Can I Please Speak to an Actual Person?
 by Katherine Vizcardo and Danielle Kost

Customers still want the option to access human help in automated service—even if they don't use it, says research by Michelle A. Shell and Ryan W. Buell.  .... ' 

AI Creates a Sport

Always been interested in creativity from AI.   Here an AI 'observes' sports  and creates a new one.   Is this creative, predictive, adaptive?  Is the idea useful for other kinds or contexts of human behavior?  Could this be redone for serious games?

Speedgate is based on data from hundreds of existing sports.

Jon Fingas, @jonfingas
12h ago in Personal Computing in Engadget

Many existing sports have their roots in hundreds (if not thousands) of years of human tradition. But what if you asked computers to create a sport? You now know how that can turn out. The design agency AKQA has introduced Speedgate, reportedly the first sport envisioned by an AI. The event has six-player teams competing on a field with three open-ended gates. Once you've kicked the ball through a center gate (which you can't step through), your team can score on one of the end gates -- complete with an extra point if you ricochet the ball through the gate. You can't stay still, either, as the ball has to move every three seconds.   .... " 

Converting Insight into Action for CPG

Useful description about the ability to integrate CPG and behavior.

Using AI to Translate Insight into Action
By Steven Hornyak, Symphony Retail AI, CPG Solutions - in ConsumerGoods

Today, consumer packaged goods brands are tasked with much more than conveniently connecting shoppers with their favorite items. Consumers want brands to anticipate their needs and make relevant products available to them wherever they shop.

But many CPGs have yet to crack the code. They’re spending countless hours and dollars investing in trade promotions even though 72% of those programs don’t break even. They also invest heavily in new product development even though 95% of new products fail. To be successful in today’s market, CPGs must acquire and learn from a deeper understanding of consumer behavior to make more strategic, more intelligent promotion decisions.

Channel blurring has led to more complexities than ever for both CPGs and retailers. Consumers have the option to shop in physical stores or online, a blend of the two with buy online and pick up in store, or to not even actively shop at all by using a subscription service. On top of this, the growth of today’s private label and regional-based players have led many product lines to hit a premature revenue ceiling. ... " 

Cases for AI in Advertising

We  used AI in the earliest days, but did not have the needed tools, there are many more now.

The Case for Investing in AI for Advertising in ChiefMarketer

Posted on April 15, 2019 by Sven Lubek

There are numerous examples of high profile brands experimenting with artificial intelligence (AI) in creative ways. For example, Lexus recently worked with IBM Watson to release the first AI scripted advertisement.

AI is ultimately here to improve people’s lives both at work and at home, yet many organizations are still timid about investing in the technology. Here are some strong cases for investing in AI for advertising today:

Achieving True Scale and Engagement

Marketers are investing in AI to deliver advertising that is relevant, contextual and hyper-personalized to individual consumer preferences. Automation is an important component of driving this capability.

Adam Powers, CEO at Tribal Worldwide, shared at Mobile World Congress 2019 how they use AI in advertising to create contextual experiences for users: “Offer an experience where the application of AI is an invisible factor—emotional engagement and conversion focus. Magic can happen in the details, the small things and looking at the practical application of AI. For example, a client in Indonesia uses machine learning to forecast fashion trends by feeding in various data points, and image uploading to forecast in which part of the region certain products will sell.”

“Brands need to try to keep up with changing consumer behavior,” added Neil Stubbings, CRO at IV.AI. “It’s the age of availability. A brand should be available on any platform that the customer is, and that’s the challenge and the opportunity for brands to transact with consumers…people are looking for things that feel more native.”  .... ' 

Forrester on Value of Blockchain for the Supply Chain

High level overview of value of blockchains and link to a video:

Blockchain and Supply Chain
George Lawrie, Vice President, Principal Analyst
Martha Bennett, Principal Analyst

Modern supply chains are faster, more dynamic, and more volatile than ever before. The digital economy thrives on scouring the globe for new markets and new sources of supply.  Furthermore, agile supply networks outpace rigid supply chains, anticipating demand from empowered customers. But in contrast with rigid legacy supply chains, binding known and trusted vendors,  an agile network of temporary suppliers,  might damage customer experience, by concealing the origin and characteristics of components or ingredients. Blockchain and distributed ledger technologies can help,  by increasing visibility of supply chain documentation. They can reduce inspections, boost trade credit,  and build trust even with new, or temporary, suppliers. .... " 

On the use of Microservices

Fascinating case study that I have passed the link on to several clients.  Below the intro:

How we moved from a giant monolithic system to microservices in Medium
By Arjun Dixit  @ Rebel Foods (Part 1/2)

Defeat them in detail: The Divide and Conquer Strategy. Look at the parts and determine how to control the individual parts, create dissension and leverage it. — Robert Greene

With this being said, we at Rebel Foods tech, strongly believe in the idea of breaking down a large monolith system into the small sets of microservices. Here I would be describing the purpose and the journey behind it.

Overview of the monolith giant system of Rebel Foods:

When we started in 2011 with one brand FAASOS the requirements were quite clear to us — “Build a system that can handle 15k transactions per day” and 15k was just the number of orders expected daily, behind this Rebel Foods manages the complete lifecycle of on-demand food right from the inventory to our supply chain to content management to user channels like our mobile apps, websites and our third-party partners to our cloud kitchens to finally making the last-mile fulfilment. Looking at the fast-paced market we had to deliver a system that can produce a flawless experience while being 99% fault tolerant. We came up with a central core system design that would interact with our main database and would expose the APIs to perform various operations required to satisfy the above needs. We called this system the V1 architecture of Rebel Foods.  ... "

Sunday, April 14, 2019

Cyber Agriculture

My own strong interest and background in botany makes me consider this closely, consider the implications.  In particular have been experimenting with basil flavors for years.   While the smells of basils can be considerable, they often do not perform as distinctly in dishes.   Can we program in robust flavors?  Following.

MIT’s ‘cyber-agriculture’ optimizes basil flavors   By Devin Coldewey @techcrunch

The days when you could simply grow a basil plant from a seed by placing it on your windowsill and watering it regularly are gone — there’s no point now that machine learning-optimized hydroponic “cyber-agriculture” has produced a superior plant with more robust flavors. The future of pesto is here.

This research didn’t come out of a desire to improve sauces, however. It’s a study from MIT’s Media Lab and the University of Texas at Austin aimed at understanding how to both improve and automate farming.

In the study, published today in PLOS ONE, the question being asked was whether a growing environment could find and execute a growing strategy that resulted in a given goal — in this case, basil with stronger flavors.

Such a task is one with numerous variables to modify — soil type, plant characteristics, watering frequency and volume, lighting and so on — and a measurable outcome: concentration of flavor-producing molecules. That means it’s a natural fit for a machine learning model, which from that variety of inputs can make a prediction as to which will produce the best output.

“We’re really interested in building networked tools that can take a plant’s experience, its phenotype, the set of stresses it encounters, and its genetics, and digitize that to allow us to understand the plant-environment interaction,” explained MIT’s Caleb Harper in a news release. The better you understand those interactions, the better you can design the plant’s lifecycle, perhaps increasing yield, improving flavor or reducing waste.  .... " 

Case Study for a Global AI

Considerable case study, contains lots of good things to consider,  but not enough about the goals involved.  Good details but not enough of them.   Its a global brand, so how much do we need to consider varying languages and cultures?   In our own example we found that the training data quality varied strongly because it was gathered based on those cultural differences.  In some cases there was insufficient data for a particular culture.  I like particularly the involvement of decision makers early seems to be carefully considered. 

Building an AI For A Global Brand  by Alexandre Gonfalonieri in Medium

Building an AI solution for a global brand is actually quite challenging. From figuring out the best business issue for AI to the release of the solution, many things can impact the project. Through this article, I wanted to share with everyone my own personal experience.

AI has become a buzzword in almost all industries and most decision-makers want to start or have already started implementing AI solutions.  ... "

A Better Way to Multiply

Useful for cryptography and methods that require fast hashing on IOT edge applications?

Mathematicians Discover the Perfect Way to Multiply  in Quanta Magazine

By chopping up large numbers into smaller ones, researchers have rewritten a fundamental mathematical speed limit.

On March 18, two researchers described the fastest method ever discovered for multiplying two very large numbers. The paper marks the culmination of a long-running search to find the most efficient procedure for performing one of the most basic operations in math.

“Everybody thinks basically that the method you learn in school is the best one, but in fact it’s an active area of research,” said Joris van der Hoeven, a mathematician at the French National Center for Scientific Research and one of the co-authors. ... " 

Consumers Breaking with Legacy Brands

Still nostalgia equity is a powerful thing for many brands.

Nostalgia Is Not Enough: Why Consumers Abandon Legacy Brands
Mar 25, 2019 Strategic Management  North America

Earlier this month, Sears ended a nine-decade presence in Lincoln, Nebraska, when it closed its store at the Gateway Mall. So it was, too, at Park City Center in Lancaster, Pennsylvania, where that town’s Sears store was one of dozens shuttered nationally in yet another wave of contraction by the once-mighty retailer.

The closings set off the expected misty-eyed recollections about the legacy brand and the cherished place it occupied in hearts across the country. In Colorado, where Sears closed two stores in Colorado Springs and one in Pueblo, a columnist for the Gazette mourned the loss. But she also admitted that her February visit to report on the closing was the first time she had been to Sears in a decade. “I left empty-handed, and a little heavier-hearted,” wrote Stephanie Earls.

Among legacy brands, Sears is in similar, troubled company. Payless ShoeSource is liquidating its 2,100 U.S. stores. Toys “R” Us — where many a young American parent remembers buying his or her first Transformer or Super Soaker – closed its 730 locations last year and is struggling to come back in some form post-bankruptcy.

You might have expected that the pull of nostalgia would have protected these brands from the retail re-sorting underway. Customers have emotional connections to certain stores — places where their parents brought them as children and where they did their first Christmas shopping, and developed certain buying habits and loyalties.

So what was the breaking point for customers? Price? Experience? Convenience? Why, in the end, are customers abandoning their shopping heritage and breaking up with brands? ... '

Saturday, April 13, 2019

Comparison of Analytic Methods

Becasue I often work with different kinds of practitioners, I often get questions like:  How is this different from statistical methods, from Operations Research .... ?  I was trained in earlier methods that often had the same goals, but with no claim of being a science.   Just math and data based techniques that embed some useful goals and constraints.    In prep for an upcoming presentation I reviewed the below to consider the differences.    There are lots of overlap here,  so you can't define them precisely.    Often the best approach can be the one that your clients best understand.    But its good to know and review the general direction of many of these.   Also,  hype does not mean right,  and can confuse the issue when over-emphasized.    Good piece.   Join DSC for more.

16 analytic disciplines compared to data science  in DSC

Posted by Vincent Granville on July 24, 2014 

What are the differences between data science, data mining, machine learning, statistics, operations research, and so on?

Here I compare several analytic disciplines that overlap, to explain the differences and common denominators. Sometimes differences exist for nothing else other than historical reasons. Sometimes the differences are real and subtle. I also provide typical job titles, types of analyses, and industries traditionally attached to each discipline. Underlined domains are main sub-domains. It would be great if someone can add an historical perspective to my article.  ... "

Robots Sorting Trash

An excellent example of robot use.  Its a classic example of solving a messy problem that can change the economics of a difficult problem.  How well would it work?

MIT’s bot sifts through trash to do your recycling for you in DigitalTrends

Engineers from the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new recycling robot that’s capable of automating the process of sifting through trash to distinguish between paper, plastic and metal items. In doing so, it could automate a dull — but entirely necessary — job that few people would want to carry out by hand if there was another option available.

“Although single-stream recycling is really convenient for people, it’s actually a time-consuming and expensive ordeal, requiring significant human labor,” Lillian Chin, a CSAIL Ph.D. student who worked on the project, told Digital Trends. “In developing countries, people have to pick out the recyclable materials from normal waste which can be quite hazardous. [But] even in the U.S., with more automated recycling centers, people are still needed to double-check the machine’s output and manually pick out unrecyclable objects like car engines and plastic bags.”  .... '

Best Data Science Youtube Channels

Good resources, did  quick scan and there are some useful things there,  somewhat varied in quality,  but there are gems.

4 of the Best Data Science YouTube Channels in Medium
Go to the profile of #ODSC - Open Data Science

There are a lot of ways that you can learn about data science and/or stay up to date with the latest trends, but the easiest by far is still Youtube. You could do a search for data science and come up with thousands and thousands of hits, but we’ve got our top four picks to help you get started. Let’s take a look:   ... '

Natural Language and Intent with Ambiguity

Good simple explanation from Tableau on Intent.   Have used the concept now in several projects, and of course there is ambiguity, beyond dictionary-definition,  in the use of many terms within a company.   The ambiguity in context is important to consider.

Machine learning, natural language meet to understand intent
 By Mark Jewett, VP of Marketing, Tableau

Machine learning and natural language processing promise to better translate human curiosity into pertinent answers. If true, these smart capabilities will broaden the use of analytics and reach people who are less comfortable dealing with data. It will all start with helping machines learn to interpret human intent. The key is semantics.

Sometimes intent is simple and explicit, like asking Siri or Alexa if a flight is delayed. This question has clear intention and a simple response—returning the flight status answers the question. Such simplicity is seldom the case when it comes to data analysis. Questions are usually more nuanced, making it hard to correctly assume what the user is really looking for. Natural language is even more tricky where ambiguous terms are common.

It’s also difficult for a machine to understand our intent within a limited context. The machine has the data itself but doesn’t grasp the bigger picture in the same way a person with domain expertise can. Asking “How are my sales doing in the Northeast?” is a lot more ambiguous than the flight status example above.

Ambiguity isn’t a new challenge in data analysis. Different groups within an organization may have different definitions or calculations for the same words: for example, the term “profitability”. Some organizations use central dictionaries (also called data catalogs) to reduce ambiguity and create consistency across the organization. These tools can help provide users with the context they need to understand more deeply. .... " 

Data vs Democracy?

Interesting view ...

Who needs democracy when you have data?

Here’s how China rules using data, AI, and internet surveillance.
by Christina Larson in Technology Review

"... In 1955, science fiction writer Isaac Asimov published a short story about an experiment in “electronic democracy,” in which a single citizen, selected to represent an entire population, responded to questions generated by a computer named Multivac. The machine took this data and calculated the results of an election that therefore never needed to happen. Asimov’s story was set in Bloomington, Indiana, but today an approximation of Multivac is being built in China. ... " 

Friday, April 12, 2019

The Value of Inefficiency

I like the general thought.     Pure efficiency can make us miss things.   Its why  had second thoughts about optimization methods,  they could rarely be implemented directly, and their methods where often   did not give you enough hints at creative alternatives in context.  Podcast and transcript in K@W:

Edward Tenner discusses his new book about how too much efficiency kills creativity, innovation and problem-solving.

Technology is the undisputed champion of efficiency. Tasks that were once complex and time-consuming are now completed in the blink of an eye. But there is a downside to an abundance of technology. In his new book, scholar Edward Tenner explains how too much efficiency can kill creativity, which can turn off avant-garde thinking, innovation and problem-solving. He believes there is a better way to improve our lives through a combination of technology and intuition, and by exploring the random and unexpected.

Tenner, a distinguished scholar at the Lemelson Center for the Study of Invention and Innovation at the Smithsonian, spoke about his book, The Efficiency Paradox: What Big Data Can’t Do, on the Knowledge@Wharton radio show on SiriusXM. (Listen to the podcast at the top of this page.)

 An edited transcript of the conversation follows. ... 

Knowlege@Wharton: What’s so terrible about efficiency?

Edward Tenner: The problem with efficiency is that algorithms let us really learn from experience, they let us codify experience, they let us benefit, they recognize patterns. They are really tremendous at that. For example, I use the Google navigation program Waze. I first started out as a critic of it, but then I got into it more and more. However, the problem with Waze is that every once in a while, it will make a terrific blunder. If somebody relies completely on a system like that, no matter how brilliantly engineered, sooner or later some glitch is going to bite back. However, if they keep their awareness of where they are, if they keep their common sense, and if they keep trust in their common sense, then they can get the most of the program while avoiding those little disasters.

Knowlege@Wharton: Because we are so reliant on technology, are we losing something as a society, as a culture?    .... " 

IOTA Zeus for Retail Payment

A somewhat unexpected application for the novel IOTA 'blockchain' approach.  Following.

Zeux App Enables Use of IOTA For Cryptocurrency Payments at Retail Stores
By Gabriel M

The crypto payments startup Zeux has recently affirmed that it would team up with IOTA (MIOTA) in order to list the token for crypto payments at retail stores. According to the reports, the service will be available with stores that accept Samsung Pay and Apple Pay.

Zeux has revealed the partnership via social media, affirming that IOTA payments will be added for the new token and that people will be able to use it with several different merchants. At the moment, Zeux has a FCA regulatory license and this is probably part of the changes due to its upcoming launch in the European Union next month.

The company is also planning to launch its services in the United States soon. According to the announcements, a big number of shops from grocery stores to coffee shops will be able to receive payments using Zeux.  .... " 

Augmenting Quantum D-Wave Annealing

Mentioned before we connected with D-Wave Quantum Computing early on.   Have posted many items about their work.    Their annealing approach still has great potential for some difficult kinds of combinatorial problems.  Note how this addresses partitioning of sub problems to make the D-Wave approach most useful.  Here a new example of work from Japan in the automotive manufacturing space.  Not enough detail here, but taking a closer look.

Algorithm Optimizes Quantum Computing Problem-Solving 
Tohoku University in ACM

Researchers at Tohoku University in Japan have developed an algorithm that augments the ability of a Canadian-designed quantum computer to more efficiently determine an optimized solution for complex problems. The D-Wave quantum annealer uses the concepts of quantum physics to solve "combinatorial optimization problems;” Tohoku's Shuntaro Okada and Masayuki Ohzeki designed the algorithm with global automotive components manufacturer Denso and other collaborators, to improve this capability. The algorithm partitions a large problem into a group of subproblems, then the annealer iteratively optimizes each subproblem to solve the overarching one. The program also enhances another algorithm via the same concept, permitting the use of larger subproblems, and more efficiently arriving at optimal solutions. Ohzeki said, "As the number of [quantum bits] mounted in the D-Wave quantum annealer increases, we will be able to obtain even better solutions."  ... '