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Thursday, March 22, 2018


Useful Informatica white paper on GDPR, brought to my attention.  Which happens come May 25.   Implications for Assistants?

In the WP: " ... The General Data Protection Regulation (GDPR) (EU) 2016/679 is a regulation in EU law on data protection and privacy for all individuals within the European Union. It addresses the export of personal data outside the EU. The GDPR aims primarily to give control back to citizens and residents over their personal data and to simplify the regulatory environment for international business by unifying the regulation within the EU.[1] When the GDPR takes effect, it will replace the 1995 Data Protection Directive (Directive 95/46/EC).[2] .... "

IBM Watson Assistant: Business Skills as Intelligence Architecture

Have now had a few month look at the Watson Assistant in Beta.   Also have had three years learning with the Amazon Echo and a year plus with the Google Home.    So the comparison is quite interesting.  Watson Assistant is very much a 'white label', a system designed  to be installed in other, more complex things like cars or hotel night stands or Hospital rooms.   Or even a tiny part of your IOT.   Not to say that the Echo and Home's have not also crept into other devices.  And both now have a considerable lead in implementation.

What Watson Assistant does now have is the ability to link to Watson meta skills that have already been built for Watson.   Conversation,  Discovery and  Personality detection are just a few of dozens.  In the future also Blockchain.  Some are arranged in industry functional groups:  Say Financial, Supply chain or Retail.   So you should be able to look up just the  intelligence 'skills' you need and apply it to your need, in API fashion.  Mix and match them like parts of a business brain.  And then you get the skill functions to augment business needs.

And these needs .... like understanding speech, speaking to you, linking to information on the Internet and communicating with the IOT, and performing typical business transactional interactions are all there. But how to attach them is still not clear.   For example the Discovery Watson Skill, which lets you ingest private information and then interact with it intelligently,  is still to be connected.  Similarly business capabilities, like Business process modeling , are also possible future available methods.

IBM has gotten closer to making useful business oriented capabilities useful as skills.  Better than Home or Echo.   Closer to having a true assistant.   So if developers and startups line up to produce meta-skills that will deliver business value, we may see great things.  It remains to be seen if IBM Watson has the architecture to make it the place to do that.   Or should the developers just write a business value from the ground up?   Looking for new examples.

 IBM’s Watson Assistant lets any company build Alexa-like voice interfaces

You get a voice assistant, and you get a voice assistant, and you  By James Vincent   @jjvincent  in TheVerge.

IBM is today launching Watson Assistant, a new service aimed at companies looking to build voice-activated virtual assistants for their own products. Want your hotel’s rooms to remember a guest’s preferences for air-con? Or your car’s dashboard to be controllable via voice interface? IBM’s message to companies is: we can help you build that.

It’s an interesting pitch, especially as voice assistants like Amazon’s Alexa are being integrated into new arenas. (See, for example, the Wynn Las Vegas’s decision to install Echoes in every room.) IBM says this shows the popularity of conversational interfaces, and believes companies should choose Watson Assistant over Alexa or Siri for a number of reasons — namely: branding, personalization, and privacy.

First, Watson Assistant is a white label product. There’s no Watson animated globe, or “OK Watson” wake-word — companies can add their own flair rather than ceding territory to Amazon or Apple. Second, clients can train their assistants using their own datasets, and IBM says it’s easier to add relevant actions and commands than with other assistant tech. And third, each integration of Watson Assistant keep its data to itself, meaning big tech companies aren’t pooling information on users’ activities across multiple domains. .... "

Machine Learning with Limited Data

Despite all the claims for all the data we have, this is often the case.  And the term 'mixed scale' is important,  you often have many different quantities of data by context.

Machine Learning With Limited Data
Government Computer News  By Matt Leonard

Researchers at Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a Mixed-Scale Dense Convolution Neural Network, a system that requires fewer parameters and training images when working toward image-recognition technology. A typical neural network is comprised of layers, each of which performs a specific analysis--one layer informs the next layer, so relevant information must be copied and passed along. Standard practice involves looking at fine-scale information in the early layers and large-scale information in the later layers. However, the new system mixes different scales within each layer, says Berkeley Lab's Daniel Pelt. This means large-scale information is analyzed earlier along with fine-scale information, enabling the algorithm to focus on the relevant fine-grain details. In addition, the layers in the new system are densely connected, meaning information does not have to be copied repeatedly throughout the network, and earlier layers can communicate relevant information directly to layers later in the series.
 .... "

Wednesday, March 21, 2018

Defining Normal

Useful idea.  The example shows a very specific context  at what space or times scales?

Researchers at Bethel University are studying how to teach computers to define "normal" data and then detect anomalies.

The team used mathematical models and real-world data to determine ways to detect needle-in-the-haystack anomalies and report them in real time, using far less computational power than conventional systems.

Their algorithm is based on recognizing a sudden increase of distance between vectors in a high-dimensional vector space.

The researchers tested the algorithm by installing a webcam in an office window to pick up a feed of outdoor foot traffic. Each quadrant in the field has its own anomaly detector attached to it, and if something enters into that box previously unseen by the system, an alert is sent, says Bethel's Brian Turnquist.  ... " 

Is the BlockChain Needed?

A critically contentious look at Blockchain.  Do we need it?  How is it different from a number of existing technical capabilities?  Worth thinking about it.

AI and Process Productivity

Nicely done, considerable case study.   Agree.   And suggest that a good way to ensure this is to make sure you know exactly where and how the AI is inserted in current or proposed process.  Then the needed training and skills of the employees involved should be apparent.

Why Artificial Intelligence Isn't a Sure Thing to Increase Productivity  in HBS Working Knowledge by Michael Blanding

As companies adopt artificial intelligence to increase efficiency, are their employees skilled enough to use those technologies effectively? Prithwiraj Choudhury looks to the US Patent and Trademark Office for a case study.  ... 

Will Amazon Own Your Customer?

Amazon Will Own Your Customer And What To Do About It
By James L. McQuivey   Vice President, Principal Analyst

 From twenty years of trying, I know this about covering Amazon: It’s tricky. Our report process can take months during which we comb through our extensive Technographics data to find patterns or we interview executives. Not to mention the time it takes to write, edit, and produce our reports. During which time, the moving target we call Amazon announces dozens of new things that you can’t go back and add to your report. So while I’m pleased to announce that my latest comprehensive review of Amazon’s long-term strategy is now ready for clients to read (see Amazon Will Own Your Customer In The Future), it will appear I have left a few things out. Except that I haven’t, because our read of Amazon’s strategy is so on-point that every one of these significant moves announced by the orange smile is accounted for in our model. For example, Amazon:   (See the full article at link) .... 

2018 Amazon Shopper Behavior Study

Looks to be most interesting, download it at the link:

CPC Strategy
The 2018  Amazon Shopper Behavior Study
How Shoppers Will Browse and Buy on Amazon in 2018

Get the Guide PDF

The Story: 2018 will be a pivotal year for retailers, and as usual, Amazon’s at the steering wheel. The only question is–where are they heading next, and more importantly, how will consumers react?

In our 2018 Amazon Shopper Behavior Study, we’ll reveal eye-opening statistical findings that drive Amazon shoppers to make a purchase and why consumers may not be as loyal to your brand as you thought.

The Study: In this year’s Amazon Shopper Study, we asked 1500 U.S. Amazon shoppers big questions including:

How far are Amazon shoppers willing to search beyond page one?
How often do you use Amazon to discover new products or brands?
Are you concerned about counterfeit products on Amazon?
What’s the biggest factor in your decision to buy a product?
And plenty more!   .... " 

Tuesday, March 20, 2018

Tiny, Disposable CPUs for the IOT

I like the idea that these CPUs will be embedded, even disposable.   In packaging for example.  Something we suggested in retail.    Bringing computing power closer to the edge.   Still not powerful by modern standards.

IBM’s latest computer is a blockchain-ready CPU smaller than a grain of salt  in DigitalTrends.

IBM kicked off its Think 2018 conference today with a bombshell announcement: It has made the world’s smallest computer, and it’s designed from the ground up to work with the blockchain. The computer itself is smaller than a single grain of salt, coming in at 1 millimeter by 1 millimeter and reportedly has about the same computing power as a 1990s era CPU.

“The world’s smallest computer is an IBM-designed edge device architecture and computing platform that is smaller than a grain of salt will cost less than ten cents to manufacture, and can monitor, analyze, communicate, and even act on data,” IBM claims. “It packs several hundred thousand transistors into a footprint barely visible to the human eye and can help verify that a product has been handled properly throughout its long journey. ... 

.... Essentially, these CPUs will be embedded in tags or product packaging, and they’ll log every movement the product makes, from shipment to delivery. They could also be used to ensure the authenticity of luxury goods. .... 

“ ... These technologies pave the way for new solutions that tackle food safety, authenticity of manufactured components, genetically modified products, identification of counterfeit objects, and provenance of luxury goods,” Krishna continues. .... " 

On Algorithms and Reading

How to Think for Yourself When Algorithms Control What You Read   By Marc Zao-Sanders in HBR

With the flick of a switch, a handful of tech giants can change the nature and extent of mankind’s ingestion of information. In 2013, Google took a step towards understanding the intent of their users with the Hummingbird algorithm. Twitter replaced most-recent with most-important tweets when they introduced their algorithmic timeline in 2016. Facebook claimed they’ll be replacing clickbait with more meaningful interactions on their feeds earlier this year.  These changes are almost always met with public uproar for a few weeks, soon after which humanity acquiesces. The ability for an elite to instantly alter the thoughts and behavior of billions of people is unprecedented.

This is all possible because of algorithms. The personalized, curated news, information and learning feeds we consume several times a day have all been through a process of collaborative filtering. This is the principle that if I like X, and you and I are similar in some algorithmically determined sense, then you’ll probably like X too. Everyone gets their own, mass-personalized feed, rationed by the machines. ... "

IBM Delivers a Watson Voice-Powered Assistant

Been looking at this in Beta for some time.  More detail to follow.

IBM delivers Watson-powered voice assistant for consumer brands
Alexa and Google Assistant have taken residence in people's homes. IBM aims to give companies a way to deliver their own branded AI voice assistants

IBM has launched Watson Assistant, an artificial intelligence (AI) powered voice assistant for businesses.

Organisations showcasing the Watson Assistant include speaker maker Harman, retail bank Royal Bank of Scotland, Autodesk, Munich Airport and Motel One.  ... "

Behavioral Implications of Grab and Go Retailing

Some interesting behavioral observations of early use of the lack of checkouts in Amazon's Grab and Go tests.   We interviewed and watched consumers in our laboratory stores to learn how they felt and reacted to similar approaches.  Will this cause fewer visits, change the nature of visits and purchases?  How will it interact with online visits?    Will this be an ultimate expectation of physical stores?   Amazon is in position to learn much here.

Amazon Go customers are still adjusting to the grab-and-go model in DigitalTrends

Apparently, our parents have taught us well. While Amazon’s new cashless grocery store, Amazon Go, has encouraged folks to just walk out the door without paying, it would seem that folks aren’t quite on board with that model yet. According to Gianna Puerini, vice president of Amazon Go, it has taken shoppers a bit of time to get used to the fact that walking out of a store without stopping by a cash register is not, in fact, immoral or illegal.

At Shoptalk, a retail industry event in Las Vegas, Puerini noted that she has been struck by the number of customers who have second-guessed their ability to take advantage of the cashless convenience offered by Amazon Go. ‘‘What we didn’t necessarily expect was how many people would stop at the end on their first trip or two and ask, ‘Is it really OK if I just leave?’’’ Puerini said of the new-age store that opened in January in Amazon’s hometown of Seattle. .... " 

Monday, March 19, 2018

Optimizing Health Policies with Bayesian Networks

 Another excellent, mostly nontechnical presentation on the topic.   Interesting is the decision model itself, and the topic of health decisions.  Unlike most modeling methods, this approach embeds the details of the model into the decision process being modeled.  So you can visually see the details of what is being modeled and discuss it with decision makers.  Also, it directly models uncertainty involved, based on real known data.   We used these methods actively,  I but find them rarely applied in business.   Consider it.  ....

Presentation link and slides below: 

By Stefan Conrady

Managing Partner at Bayesia USA & Singapore: Bayesian Networks for Research, Analytics, and Reasoning

Optimizing Health Policies with Bayesian Networks

In case you missed today's webinar, here is the recording. Today's program was about developing a reasoning framework for health policies in developing nations with Bayesian networks. The specific study question was whether to implement a "test & treat" policy versus a presumptive treatment approach for malaria and bacterial pneumonia. https://bayesia.wistia.com/medias/16vb2vljlt

HBR: Getting Value from Machine Learning

Makes a very obvious case.    That has existed since the beginning of computing.  Yet still a good one to repeat.  Systems must be easy enough to use.  And then actually used, to make them valuable.  Of course when you add in some level of autonomy, with a clearly measurable value, that helps.   One way to do that is to plug them into a known and measurable business process.   You can show the value of it being better, faster, or cheaper, directly.  Augmentation of people and processes is best.  Making the method automatically considered and even applied.  We did it many times.  Good example of project management below. 

Getting Value from Machine Learning Isn’t About Fancier Algorithms — It’s About Making It Easier to Use    By Ben Schreck, Max Kanter, Kalyan Veeramachaneni, Sanjeev Vohra, Rajendra Prasad  in the HBR

Machine learning can drive tangible business value for a wide range of industries — but only if it is actually put to use. Despite the many machine learning discoveries being made by academics, new research papers showing what is possible, and an increasing amount of data available, companies are struggling to deploy machine learning to solve real business problems. In short, the gap for most companies isn’t that machine learning doesn’t work, but that they struggle to actually use it.

How can companies close this execution gap? In a recent project we illustrated the principles of how to do it. We used machine learning to augment the power of seasoned professionals — in this case, project managers — by allowing them to make data-driven business decisions well in advance. And in doing so, we demonstrated that getting value from machine learning is less about cutting-edge models, and more about making deployment easier.  .... " 

Inferring Emotion and Cognitive Changes

The OBAIS department at the Lindner College of Business, University of Cincinnati, invites you to attend a research seminar:

Date and time: Wednesday, March 28th, 2018, 11:00AM-12:00PM

Location: Lindner Hall 608
Speaker: Prof. Joe Valacich, Eller Professor in MIS, University of Arizona

Title: Inferring Emotion and Cognitive Changes through Human-Computer Interaction Devices: From Basic Research to Communalization

Best wishes,

Yichen Qin, Assistant Professor
Department of Operations, Business Analytics, and Information Systems
Lindner College of Business, University of Cincinnati
Website: http://business.uc.edu/academics/departments/obais/faculty/qinyn.html
Email: qinyn@ucmail.uc.edu

Measuring Results

How Accurate Is Your AI? 
from Kyoto University

A researcher at Kyoto University in Japan has developed a new technique that evaluates artificial intelligence's (AI) performance based solely on the input data. In typical AI development, a performance evaluation is trusted if there is an equal number of positive and negative results, and data biased toward either value means the current system of evaluation will distort the system's ability. "The novelty of this technique is that it doesn't depend on any one type of AI technology, such as deep learning," says Kyoto's J.B. Brown. "It can help develop new evaluation metrics by looking at how a metric interplays with the balance in predicted data. We can then tell if the resulting metrics could be biased." Brown's work breaks down the AI utilization and analyzes the nature of the statistics used for reporting an AI's ability, while also producing a probability of the performance level, given evaluation data. .... " 

Testing and Automation of Assistant Skills

Like paying attention to the process of creating and delivering skills: 

Building Engaging Alexa Skills: Why Testing and Automation Matter

By Paul Cutsinger  In Amazon Developer

By Editor’s Note: Skill testing is one of the most important things you can do to build high-quality voice experiences. Today we welcome a community expert in testing tools for voice—John Kelvie, founder and CEO of Bespoken—to share some best practices.

Developing for Alexa can be a lot of fun. There are so many opportunities to create innovative user experiences. The cutting edge is constantly evolving. And the reachable audience is immense, and always expanding.

When building skills, it is incredibly important to build high-quality experiences for users. These users will not come back if a skill does not open or fails quietly halfway through. And we may not be aware of any problems until a user writes a one-star review. This is not the ideal way to identify and fix bugs; there must be a better one.

And there is. Testing and automation are the solution. They help us deliver reliable skills for customers and a great user experience. Through testing and automation, we can offer consistently great experiences to our users. This blog will outline how to do this at a high level and also offer some practical steps to implement it. .... " 

Online Grocery to Reach $100 Billion

Online grocery sales could reach $100 billion by 2022, researchers say    By Andrea Miller   ABC

Walmart plans on expanding grocery delivery to 100 metropolitan areas

Instead of taking a trip to a local grocery store, more and more consumers are opting to order essentials such as cereal, toothpaste or even apples from online retail giants.

Walmart, for one, announced Wednesday that it is bolstering its grocery-delivery service to reach even more cities. .... " 

Macy's Using Virtual Reality for Furniture Sales

Really a pretty old idea, was one of the first ideas we examined for demonstration and sales.    I encountered IKEAs approach in-store  just a few days ago, well done, but not enough AR to understand how your choices would fit in.   Also drove home the point that for store and online experiences the consumer needs to be able to use the system quickly.  Its different in research.   We experimented with it to understand how product would exist on shelves with other products.   See also approaches that mix VR, AR and physical digital displays, such as John Milby's Full Scale Virtual Research (FSVR).

Macy’s will use VR to sell furniture in 50 stores by summer
 By Jeremy Horowitz  @Horowitz  in Venturebeat

VR and online shopping are often portrayed as enemies of brick-and-mortar retail, but shopping mall anchor Macy’s plans to embrace both technologies in a bid to improve its sales, reports FurnitureToday. Speaking at the ShopTalk retail conference in Las Vegas, Macy’s CEO Jeff Gennette announced that he will bring VR furniture-selling tools to 50 stores by this summer and plans to offer the immersive shopping technology in “as many stores as possible.”

According to Gennette, the virtue of virtual reality is its ability to “sell more furniture with less, or even no, square footage devoted to displaying it.” Macy’s piloted a VR system that let customers use a tablet to add furniture to a room, move the pieces around until they seemed optimal, then experience the fully furnished room using VR. The system enabled customers to feel more comfortable about furniture fit and “significantly increased” both total transaction sizes and sales of items that Macy’s carries but didn’t keep on site.  .... " 

AI for Competitive Value

Everyone is still asking,  how much of this is hype?  There is an element of that, but clearly value as well.  How much should the enterprise invest?

How machine learning is changing the game for app marketers  in Thinking with Google    ... Jason Spero Nov 2017 Apps, Emerging Technology, Mobile, Data & Measurement

Artificial intelligence and machine learning technology have the potential to revolutionize marketing as much as mobile, the internet, and television did in the past.

Forward-thinking companies are using machine learning tools to supercharge their marketing. These early adopters take advantage of the technology’s ability to streamline data, unlock user insights, and engage users in highly relevant ways. In fact, 85% of executives believe AI will allow their companies to obtain or sustain a competitive advantage, according to the The Boston Consulting Group.  ... "

Smart Speakers Addictive?

In what sense?  Because they are frequently always on, perhaps, but because they use voice as assistants I find  myself using them less than smartphone in public or semi-public situations.

How addictive are smart speakers?  by Tom Ryan  in Retailwire.

According to the latest Smart Audio Report from NPR and Edison Research, 65 percent of voice-activated smart speaker owners “wouldn’t want to go back to life without” their Amazon Echo or Google Home.

That finding exceeded the 46 percent of Americans who told Pew Research Center in 2014 they “couldn’t live without” their smartphones.

One caveat from NPR’s survey last November of 1,800 consumers is the finding that only 16 percent of Americans own a smart speaker. But the survey still demonstrated how smart speakers are changing behaviors and causing owners to form new habits.

For instance, when smart speaker owners were asked what other devices they are spending less time with as they use they increase their smart speaker usage, the top answer was traditional radio, at 39 percent. That was followed in the top-five by smartphones, 34 percent; television, 30 percent; tablets, 27 percent; and computers, 26 percent.  .... "

Sunday, March 18, 2018

Driverless Pizzas to be Delivered before People

Inclined to generally agree, general driver less delivery should precede driver-less vehicles with passengers.   If only for the liability and legal issues involved.    Yet driver-less vehicles will come.  But agree less with the article that we will soon see many customers meeting the driver-less delivery vehicles out by the curb to eliminate the last 100 yards.   It is still extreme convenience that is leading this transition.   Thoughtful piece on business process profitability issues:

Why Self-Driving Vehicles Are Going to Deliver Pizzas Before People     By Bloomberg in Forbes

In the wait for self-driving technology, cell-phone toting tech bros may have to cede their spot in line to pizzas, Craigslist couches and the mounting ephemera of e-commerce.

The future—at least in the near-term—will not only be driverless, but sans passenger as well.

The early conversations around driverless cars have focused on robot taxis because taking the human driver out of a cab seemed like the quickest path to profitability. But an increasing number of companies—automakers, tech giants, startups, parcel services—are seeing autonomous delivery as the more lucrative venture.

“The revolution in commercial vehicles will come first, then the passenger cars” will follow, said Ashwani Gupta, senior vice president of Renault-Nissan’s light commercial vehicle business. “The moment business people start believing this is going to generate additional revenue and that this is going to be more efficient, then I think they’ll start working on it.”  ... ' 

Fujitsu Human Centric AI

Was impressed with Fujitsu's work in retail when we visited.

Fujitsu drives a human centric model

AI is a core technology which enables many complex processes to be conducted independently of human judgment. Now, deep learning is often featured in the media. But it is not the whole story of AI, just an important piece of the puzzle. Our human cognition is continuously generated from complex interactions between our sensory organs, nervous system, brain and external environments.

To achieve an AI, we have to replicate and bring together a range of cognitive capabilities: perceiving, reasoning, making choices, learning, communicating, and moving and manipulating.

Fujitsu is developing key technologies under a comprehensive framework (see diagram). We call it Human Centric AI, Zinrai. Fujitsu is incorporating component technology such as machine learning, deep learning and visual recognition, into its digital solutions and services. .... " 

Baidu's AI Mimicing Voice

Baidu’s new A.I. can mimic your voice after listening to it for just one minute
By Luke Dormehl in Digital Trends

" ... “From a technical perspective, this is an important breakthrough showing that a complicated generative modeling problem, namely speech synthesis, can be adapted to new cases by efficiently learning only from a few examples,” Leo Zou, a member of Baidu’s communications team, told Digital Trends. “Previously, it would take numerous examples for a model to learn. Now, it takes a fraction of what it used to.” .... " 

Samsung TVs Controlled with Bixby Assistant

Rumor out there that perhaps Samsung would tap Alexa and/or Google for voice control.  But it seems they are sticking with their own Bixby voice assistant for controls.  Up to now only on phones, that will likely soon change.  Looking to test.

Samsung TVs tap Bixby for voice, SmartThings for home control

The company improves its already excellent Smart TV system with an app for easy setup and smart home control, as well as the Bixby voice assistant.     By David Katzmaier ...  

Misinformation and the Wikipedia

Been a longterm Wikipedia fan.   And have also been directed to many, many examples of misinformation there.  But still use it daily.  So whats the solution?  Apparently Youtube planning to resource credibility with WP articles, among others.    Further curated?   Only as good as the curators.  Bias is all over the place.

Don't ask Wikipedia to Cure the Internet   by Louise Matsakis in Wired.

" .... On stage at the South by Southwest conference on Tuesday, YouTube CEO Susan Wojcicki announced that her company would begin adding "information cues" to conspiracy theory videos, text-based links intended to provide users with better information about what they are watching. One of the sites YouTube plans to use is Wikipedia. "We’re just going to be releasing this for the first time in a couple weeks, and our goal is to start with the list of internet conspiracies listed where there is a lot of active discussion on YouTube," Wojcicki said on stage..... " 

Saturday, March 17, 2018

Tags in this Blog

This blog contains tags at the end of each post which lead to related posts.   I do go back selectively and update these tags, especially as they relate to my current research, interests or work. The tags can't be complete,  in some cases the tag topic may not exist until much later.     For example a company that is later formed to address some new technology.  This blog is for my own and client reference,  but if you have any suggestions pass then along in a comment or email.  I am on Linkedin and will respond there too.   - FAD

(Updated) Optimization using Genetic Methods

In our earliest days,  addressing supply chain and blending type manufacturing problems, we were an optimization shop.  Using the math structure of difficult combinatorial problems to find best solutions based on known goals and constraints.    But if you couldn't glean enough low level structure, we tested genetic methods, described here.   In this era of faster machines and more contextual information even more useful to try today.  Also for certain kinds of structure, also consider Dynamic Programming.  Happen to be examining that again today.

In KDNuggets  By Ahmed Gad, KDnuggets Contributor 

This article gives a brief introduction about evolutionary algorithms (EAs) and describes genetic algorithm (GA) which is one of the simplest random-based EAs.

Selection of the optimal parameters values for machine learning tasks is challenging. Some results may be bad not because the data is noisy or the used learning algorithm is weak, but due to the bad selection of the parameters values. This article gives a brief introduction about evolutionary algorithms (EAs) and describes genetic algorithm (GA) which is one of the simplest random-based EAs.


Suppose that a data scientist has an image dataset divided into a number of classes and an image classifier is to be created. After the data scientist investigated the dataset, the K-nearest neighbor (KNN) seems to be a good option. To use the KNN algorithm, there is an important parameter to use which is K. Suppose that an initial value of 3 is selected. The scientist starts the learning process of the KNN algorithm with the selected K=3. The trained model generated reached a classification accuracy of 85%. Is that percent acceptable? In another way, can we get a better classification accuracy than what we currently reached? We cannot say that 85% is the best accuracy to reach until conducting different experiments. But to do another experiment, we definitely must change something in the experiment such as changing the K value used in the KNN algorithm. We cannot definitely say 3 is the best value to use in this experiment unless trying to apply different values for K and noticing how the classification accuracy varies. The question is “how to find the best value for K that maximizes the classification performance?” This is what is called optimization.

In optimization, we start with some kind of initial values for the variables used in the experiment. Because these values may not be the best ones to use, we should change them until getting the best ones. In some cases, these values are generated by complex functions that we cannot solve manually easily. But it is very important to do optimization because a classifier may produce a bad classification accuracy not because, for example, the data is noisy or the used learning algorithm is weak but due to the bad selection of the learning parameters initial values. As a result, there are different optimization techniques suggested by operation research (OR) researchers to do such work of optimization. According to [1], optimization techniques are categorized into four main categories:  .... " 

  (Update) A comment I got made me add this.  'Optimization' in business practice implies you can get the provably, best possible solution to a problem.   But in reality it almost always means you only can get the best solution within some specific context.     A context can include structure, constraints and goals.    It may also vary over time.    It may be wrong because its too hard to completely understand the problem.  But its still often useful to get a better solution, even if not provably optimal, if its better than todays practice.     Further if you can calculate this 'theoretical' best solution, it can give you better understanding of a problem, and what to strive for.    - FAD 

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Friday, March 16, 2018

Augmented Beauty by Modiface at L'Oreal

An area we did lots of research and development on.  Now based on this piece, it seems that the tech has finally caught up to the needs.   But will it practically work as a marketing, sales and operational tool?  Remains to be seen.   See images at the link.

L’Oreal acquires Modiface, a major AR beauty company
By Ashley Carman @ashleyrcarman  in TheVerge

L’Oreal announced today that it has acquired Modiface, a company that’s had a hand in the creation of many custom augmented reality beauty apps, including those from Sephora and Estée Lauder. L’Oreal didn’t disclose the amount spent, but it did tell Reuters that it now owns Modiface’s numerous patents that help users visualize makeup and hairstyles on themselves. The partnership makes sense in that Modiface has already worked with L’Oreal multiple times, including on the launch of its Style My Hair mobile app, which lets users try on different hairstyles. For that app, Modiface manually annotated 22,000 facial images to create the experience.  ... "

Iterative Random Forests

New Learning Method:  Sees the Forest and the Trees

".... Researchers at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) and University of California, Berkeley have created a novel machine learning method that enables scientists to derive insights from highly complex systems in record time.

In a paper published recently in the Proceedings of the National Academy of Sciences, the researchers describe a technique called "iterative Random Forests," which they say could have a transformative effect on any area of science or engineering with complex systems, such as biology. ... "

Amazon Pickup Service in Whole Foods

Witnessed the set up of this in a nearby Whole Foods today.  No additional crowding as yet.   Can see it as a specialized service offering, volume involved unclear.  Other uses when the infrastructure is operating?

Amazon/Whole Foods planning store pickup service from third-party retailers  by George Anderson in Retailwire.  with further expert comments:

Amazon.com wants to negate one advantage that rivals such as Walmart, Target, Kroger and others have — store pickup. The e-tailing giant is looking to offer a pickup service at Whole Foods’ stores that will not only include orders from the organic grocery chain, but also from a host of other retailers.

According to the reports, Amazon is seeking a finance manager that will help build a pickup business from the ground up. The job posting, which was first reported on by the Puget Sound Business Journal, said the person hired would be behind “the Whole Foods delivery and pick-up service on the ultra-fast Prime Now app and enable our Prime customers to shop from a set of marquee third-party retailers.”

What potentially makes the described service different from those offered by Walmart and others is that it would appear to offer pickup from online orders placed with Whole Foods, Amazon and perhaps others, as well.  ... " 

Ring and Amazon

I am a user of the Ring Doorbell, have been since their beginning.   So intrigued by the implications. New kinds of image data collection?  Amazon Key service has been covered here.  Privacy of behavior in the home.

What does Ring mean for Amazon?   in Retailwire  by Chris Petersen with expert comments. 

Through a special arrangement, presented here for discussion is a summary of a current article from the IMS Results Count blog.

Amazon.com in late February acquired Ring, a maker of internet-connected doorbells and cameras, for about $1.1 billion.

Ring is best known for its Wi-Fi enabled doorbells that are equipped with cameras to detect when someone is at the door. Users receive an alert and then are able to view and talk to the individual outside their door through their smartphone.

On the surface, Ring is a powerful acquisition, which launches Amazon further into the home security space. Last year it began selling Amazon Cloud Cam, an indoor security camera of its own design. In December it acquired Blink, a maker of inexpensive internet security cameras and doorbells. Amazon also moves further into the IoT space with more popular products that can connect to Alexa. Google’s Nest also offers a home security system.

The apps and Ring subscriptions will create recurring revenue. All well and good in itself, but several reports on the acquisition focused on how Ring’s technology may build on Amazon Key, a service launched last October that allows Prime members to have orders delivered inside their homes to help deter theft and prevent fresh food from spoiling. .... " 

Google and Marketing Measurement

Always have been impressed by Google's aim at better measurement, it is foundational, and not  enough attention is paid to it.  Here some of their latest:

Measurement matters: Laying a foundation for better measurement, today and tomorrow  By Babak Pahlavan Mar 2018 Data & Measurement

When we talk to marketers about their challenges and needs in digital, measurement always finds its way to the center of the conversation. We've heard from advertisers large and small that measurement on digital can be difficult and often complex. But it’s also critical to address, because effective measurement is foundational to growth.

That might sound a bit lofty, but it’s true. Better measurement helps businesses uncover the best ways to invest their limited marketing resources. Which leads to better marketing, which leads to new customers and continued growth.  

But how do you define better measurement? We’ve invested a lot of time listening to our advertisers and industry partners, and we’ve consistently heard that, to be effective, measurement solutions must be:

Trustworthy: They must be transparent and easily verified by advertisers, publishers, and third parties, including technology providers and industry standards groups.

Intelligent: They must uncover the insights that really matter to a business—which often means using the latest advancements in areas like machine learning and going way beyond simple reporting.

Actionable: They must be easy to act on, so advertisers can quickly fine-tune or change their strategy, turning metrics and insights into real business impact. .... "