Category Archives: Retail

Building AI Is Hard—So Facebook Is Building AI That Builds AI

“…companies like Google and Facebook pay top dollar for some really smart people. Only a few hundred souls on Earth have the talent and the training needed to really push the state-of-the-art [AI] forward, and paying for these top minds is a lot like paying for an NFL quarterback. That’s a bottleneck in the continued progress of artificial intelligence. And it’s not the only one. Even the top researchers can’t build these services without trial and error on an enormous scale. To build a deep neural network that cracks the next big AI problem, researchers must first try countless options that don’t work, running each one across dozens and potentially hundreds of machines.”


This article represents a true picture of where we are today for the average consumer and producer of information, and the companies that repurpose information, e.g. in the form of advertisements.  
The advancement and current progress of Artificial Intelligence, Machine Learning, analogously paints a picture akin to the 1970s with computers that fill rooms, and accept punch cards as input.
Today’s consumers have mobile computing power that is on par to the whole rooms of the 1970s; however, “more compute power” in a tinier package may not be the path to AI sentience.  How AI algorithm models are computed might need to take an alternate approach.  
In a classical computation system, a bit would have to be in one state or the other. However quantum mechanics allows the qubit to be in a superposition of both states at the same time, a property which is fundamental to quantum computing.
The construction, and validation of Artificial Intelligence, Machine Learning, algorithm models should be engineered on a Quantum Computing framework.

AI Personal Assistants are “Life Partners”

Artificial Intelligent (AI)  “Assistants”, or “Bots” are taken to the ‘next level’ when the assistant becomes a proactive entity based on the input from human intelligent experts that grows with machine learning.

Even the implication of an ‘Assistant’ v.  ‘Life Partner’ implies a greater degree of dynamic, and proactive interaction.   The cross over to becoming ‘Life Partner’ is when we go ‘above and beyond’ to help our partners succeed, or even survive the day to day.

Once we experience our current [digital, mobile] ‘assistants’ positively influencing our lives in a more intelligent, proactive manner, an emotional bond ‘grows’, and the investment in this technology will also expand.

Practical Applications Range:

  • Alcoholics Anonymous Coach , Mentor – enabling the human partner to overcome temporary weakness. Knowledge,  and “triggers” need to be incorporated into the AI ‘Partner’;  “Location / Proximity” reminder if person enters a shopping area that has a liquor store.  [AI] “Partner” help “talk down”
  • Understanding ‘data points’ from multiple sources, such as alarms,  and calendar events,  to derive ‘knowledge’, and create an actionable trigger.
    • e.g. “Did you remember to take your medicine?” unprompted; “There is a new article in N periodical, that pertains to your medicine.  Would you like to read it?”
    • e.g. 2 unprompted, “Weather calls for N inches of Snow.  Did you remember to service your Snow Blower this season?”
  • FinTech – while in department store XYZ looking to purchase Y over a certain amount, unprompted “Your credit score indicates you are ‘most likely’ eligible to ‘sign up’ for a store credit card, and get N percentage off your first purchase”  Multiple input sources used to achieve a potential sales opportunity.

IBM has a cognitive cloud of AI solutions leveraging IBM’s Watson.  Most/All of the 18 web applications they have hosted (with source) are driven by human interactive triggers, as with the “Natural Language Classifier”, which helps build a question-and-answer repository.

There are four bits that need to occur to accelerate adoption of the ‘AI Life Partner’:

  1. Knowledge Experts, or Subject Matter Experts (SME) need to be able to “pass on” their knowledge to build repositories.   IBM Watson Natural Language Classifier may be used.
  2. The integration of this knowledge into an AI medium, such as a ‘Digital Assistant’ needs to occur with corresponding ‘triggers’ 
  3. Our current AI ‘Assistants’ need to become [more] proactive as they integrate into our ‘digital’ lives, such as going beyond the setting of an alarm clock, hands free calling, or checking the sports score.   Our [AI] “Life Partner” needs to ‘act’ like buddy and fan of ‘our’ sports team.  Without prompting, proactively serve up knowledge [based on correlated, multiple sources], and/or take [acceptable] actions.
    1. E.g. FinTech – “Our schedule is open tonight, and there are great seats available, Section N, Seat A for ABC dollars on Stubhub.  Shall I make the purchase?”
      1. Partner with vendors to drive FinTech business rules.
  4. Take ‘advantage’ of more knowledge sources, such as the applications we use that collect our data.  Use multiple knowledge sources in concert, enabling the AI to correlate data and propose ‘complex’ rules of interaction.

Our AI ‘Life Partners’ may grow in knowledge, and mature the relationship between man and machine.   Incorporating derived rules leveraging machine learning, without input of a human expert, will come with risk and reward.

FinTech: End to End Framework for Client, Intermediary, and Institutional Services

Is it all about being the most convenient,  payment processing partner, with an affinity to the payment processing brand?  It’s a good place to start; the Amazon Payments partner program.

FinTech noun : an economic industry composed of companies that use technology to make financial systems more efficient

Throughout my career, I’ve worked with several financial services  teams to engineer, test, and deploy solutions.  Here is a brief list of the FinTech solutions I helped construct, test,  and deploy:

  1. 3K Global Investment Bankers – proprietary CRM platform, including Business Analytics, Business Objects Universe.
  2. Equity Research platform, crafted based on business expertise.
    • Custom UI for research analysts, enabled the analysts to create their research, and push into the workflow.
    • Based on a set of rules,  ‘locked down’ part of the report would  “Build Discloses” , e.g. analyst holds 10% of co.
    • Custom Documentum workflow would route research to the distribution channels; or direct research to legal review.
  3. (Multiple Financial Org.) Data Warehouse middleware solutions to assist organizations in managing,  and monitoring usage of their DW.
  4. Global Derivatives firm, migration of mainframe system to C# client / Server platform
  5. Investment Bankers and Equity Capital Markets (ECMG)  build trading platform so teams may collaborate on Deals/Trades.
  6. Global Asset Management Firm: On boarding and Fund management solutions, custom UI and workflows in SharePoint

*****

A “Transaction Management Solution” targets a mixture of FinTech services, primarily “Payments” Processing.

Target State Capabilities of a Transaction Management Solution:

  1. Fraud Detection:  The ability to identify and prevent fraud exists within many levels of the transaction from facilitators of EFT to credit monitoring and scoring agencies.  Every touch point of a transaction has its own perspective of possible fraud, and must be evaluated to the extent it can be.
    • Business experts (SMEs)  and technologists continue to expand the practical applications of Artificial Intelligence (AI) every day.  Although extensive AI fraud detection applications  exists today incorporating human populated Rules Engines,  and AI Machine learning (independent rule creation).
  2. Consumer “Financial Insurance” Products
    • Observing a business, end to end transaction may provide visibility into areas of transaction risk.   Process  and/or technology may be adopted / augmented to minimize the risk.
      • E.g. eBay auction process has a risk regarding the changing hands of currency and merchandise.  A “delayed payment”, holding funds until the merchandise has been exchanged minimized the risk, implemented using PayPal.
    • In product lifecycle of Discovery, Development, and Delivery phases, converting concept to product.
  3. Transaction Data Usage for Analytics
    • Client initiating transaction,  intermediary parties, and destination of funds may all tell ‘a story’ about the transaction.
    • Every party within a transaction, beginning to end, may benefit from the use of the transaction data using analytics.
      • e.g. Quicken – personal finance management tool; collects, parses, and augments transaction data to provide client  analytics in the form of charts / graphs, and reports.
    • Clear, consistent, and comprehensive data set available at every point in the transaction lifecycle regardless of platform .
      • e.g. funds transferred between financial institutions may  have a descriptions that are not user friendly, or may not be actionable, e.g. cryptic name, and no contact details.
      • Normalizing data may occur at an abstracted layer
    • Abstracted, and aggregated data used for analytics
      • e.g. average car price given specs XYZ;
      • e.g. 2. avg. credit score in a particular zip code.
    • Continued growth opportunities, and challenges
      • e.g. data privacy v. allowable aggregated data
  4. Affinity Brand Opportunities Transaction Management Solution
    • eWallet affinity brand promotions,
      • e.g. based on transaction items’ rules; no shipping
      • e.g.2. “Cash Back” Rewards, and/or Market Points
      • e.g.3. Optional, “Fundraiser” options at time of purchase.
  5. Credit Umbrella: Monitoring Use Case
    • Transparency into newly, activated accounts enables the Transaction Management Solution (TMS) to trigger a rule to email the card holder, if eligible, to add card to eWallet

Is Intuit an acquisition target because of Quicken’s capabilities to provide users consistent reporting of transactions across all sources?  I just found this note in Wiki while writing this post:

Quicken is a personal finance management tool developed by Intuit, Inc. On March 3, 2016, Intuit announced plans to sell Quicken to H.I.G. Capital. Terms of the sale were not disclosed.[1]

For quite some time companies have attempted to tread in this space with mixed results, either through acquisition or build out of their existing platforms.  There seems to be significant opportunities within the services, software and infrastructure areas.  It will be interesting to see how it all plays out.

Inhibitors to enclosing a transaction within an end to end Transaction Management Solutions (TMS):

  • Higher level of risk (e.g. business, regulatory) expanding out service offerings
  • Stretching too thin, beyond core vision, and lose sight of vision.
  • Transforming tech  company to hybrid financial services
  • Automation, streamlining of processes, may derive efficiencies may lead to reduction in staff / workforce
  • Multiple platforms performing functions provides redundant capabilities, reduced risk, and more consumer choices

 Those inhibitors haven’t stopped these firms:

Payments Ecosystem
Payments Ecosystem

 

The Race Is On to Control Artificial Intelligence, and Tech’s Future

Amazon, Google, IBM and Microsoft are using high salaries and games pitting humans against computers to try to claim the standard on which all companies will build their A.I. technology.

In this fight — no doubt in its early stages — the big tech companies are engaged in tit-for-tat publicity stunts, circling the same start-ups that could provide the technology pieces they are missing and, perhaps most important, trying to hire the same brains.

For years, tech companies have used man-versus-machine competitions to show they are making progress on A.I. In 1997, an IBM computer beat the chess champion Garry Kasparov. Five years ago, IBM went even further when its Watson system won a three-day match on the television trivia show “Jeopardy!” Today, Watson is the centerpiece of IBM’s A.I. efforts.

Today, only about 1 percent of all software apps have A.I. features, IDC estimates. By 2018, IDC predicts, at least 50 percent of developers will include A.I. features in what they create.

Source: The Race Is On to Control Artificial Intelligence, and Tech’s Future – The New York Times

The next “tit-for-tat” publicity stunt should most definitely be a battle with robots, exactly like BattleBots, except…

  1. Use A.I. to consume vast amounts of video footage from previous bot battles, while identifying key elements of bot design that gave a bot the ‘upper hand’.  From a human cognition perspective, this exercise may be subjective. The BattleBot scoring process can play a factor in 1) conceiving designs, and 2) defining ‘rules’ of engagement.
  2. Use A.I. to produce BattleBot designs for humans to assemble.
  3. Autonomous battles, bot on bot, based on Artificial Intelligence battle ‘rules’ acquired from the input and analysis of video footage.

QR Code Customer Surveys on Customer Printed Receipts

A new type of customer survey might come to a retail store near you.  If you’ve ever received a receipt with a customer survey, they tell you to go home on line, and take the survey and you may receive thousands of dollars. You probably threw out the survey.

Now, to have a higher rate of return on these receipt surveys, there will be a mini QR code under each letter answer, and the user just scans in QR code answer 2.B. The result is then uploaded to the retail chains site, and registers the answer so you can easily perform the customer survey with your smartphone, or they may even provide an extra scanning tool in the store, as you leave.  Thank goodness I won’t miss out on all those opportunities to win 5 thousand dollars!

Increasing RAM on an Android OS to Limitless Computing Capacity

As I was implying in other posts, it is possible, with a potential infinite capacity to expand the computing power of a Google Android device exponentially without potential limitations.  As I explored why all the devices produced by Android seemed to grow in CPU, but not in RAM it seemed to be implied that the Android model was progressing toward a cloud model, the computations on the device would occur using an Elastic Compute Cloud, Amazon, EC2, and now Google is expanding into that arena. 

The other spectrum, Apple’s iPhone, has a business model, where it was clear that storage was their cloud model, no indications of cloud computations.  In fact, initially, there was no road map for cloud computing, philosophically, as the initial pricing model was indicating, although that might have had to change to compete, but wouldn’t admit it.

There have been several posts which specify how one would be able to hack the Android Operating System, and add RAM using the extendable, on board microSD.  The initial strategy to partition on board memory, such as leveraging the Secure Digital memory is the first step to increase your devices computing capacity.  The secondary evolving step is to use cloud elastic computing, especially in HotSpots, or home WiFi, when accessible, to utilize and expand your devices capacity to run applications at a high performing capacity.

There are opportunities to increase HotSpots through public access points, which will be hard, maybe impossible, for retail to compete with the free expansion of public accessible HotSpots.  Municipalities may decide to allow tax payers of a particular community to enter in a code, and as a result of residency of a local community, have access to the municipalities’ HotSpots.  It justifies the expansion, expenditure, and increase in revenues and local taxes for the municipalities.   Municipalities may even allow the local taxpayer to have a certain number of guest accounts.  Additional accounts may be charged a discounted fee for transient visitors to the towns, such as local shoppers that patronage local shops.  The question is, would expansion of municipality public access WiFi  offset the retail WiFi income potential for shops?  It seems that many shops are offering Free WiFi, or partnering with external national or regional providers of WiFi.  Municipality WiFi may use these 3rd party vendors to build up their infrastructure, and offer this plan.

The ability to scale up your device for both performance and storage is the sweet spot, which may entice retail shoppers to shop in a community, bring in additional revenues to a municipality.  In addition, local municipalities may offer tax breaks to registered WiFi secure HotSpots, which enable local shoppers to go through a municipality portal, and utilize the WiFi access.  The common proxy portal will enable users to register a code, or pay for the local access, just as hotels today perform the same service.  Revenue for the municipality would come both from the WiFi access, and retail revenue, i.e. taxes.

The important part of cloud computing, regardless of storage or real-time computations, must be able to encrypt the storage so the storage company doesn’t have the encryption access to the contents, but also the processing of information (CPU/RAM) in real time, or, Just In Time (JIT) encryption in the cloud.  People need to be able to trust the containment and the processing of their information within the cloud, and this is one way to be able to do so.  If each device has a mechanism, just like the one already in place by Google, and other firms,  they define and pass a Client ID,  and Client Secret to exercise there API for applications.  The one challenge to this is providing the company, which contains your information, the keys to your kingdom, a trusted party.

An alternate approach might be to allow an independent authority to control the keys, just like the original structure of the internet, where a single source controls the maintenance and control of domain (e.g. name.com) allocation.  The authority which manages domain names under a hierarchy is headed by the Internet Assigned Numbers Authority (IANA). They manage the top of the tree by administrating the data in the root nameservers.   Many time governments administrate the authority, others delegate the authority, so please read, the Domain Name Registration article.

Memory wall

The “memory wall” is the growing disparity of speed between CPU and memory outside the CPU chip. An important reason for this disparity is the limited communication bandwidth beyond chip boundaries. From 1986 to 2000, CPU speed improved at an annual rate of 55% while memory speed only improved at 10%. Given these trends, it was expected that memory latency would become an overwhelming bottleneck in computer performance.[5]

Currently, CPU speed improvements have slowed significantly partly due to major physical barriers and partly because current CPU designs have already hit the memory wall in some sense. Intel summarized these causes in their Platform 2015 documentation (PDF)

“First of all, as chip geometries shrink and clock frequencies rise, the transistor leakage current increases, leading to excess power consumption and heat… Secondly, the advantages of higher clock speeds are in part negated by memory latency, since memory access times have not been able to keep pace with increasing clock frequencies. Third, for certain applications, traditional serial architectures are becoming less efficient as processors get faster (due to the so-calledVon Neumann bottleneck), further undercutting any gains that frequency increases might otherwise buy. In addition, partly due to limitations in the means of producing inductance within solid state devices, resistance-capacitance (RC) delays in signal transmission are growing as feature sizes shrink, imposing an additional bottleneck that frequency increases don’t address.”

 

Amazon Content Rich Advertising with Streaming Video & Audio

The Amazon advertising program should include a plugin for personal web sites and blogs that instead of getting a static image with a link to a movie, or song (with Album cover), the plug in, provided by Amazon, should have an option to have a static image, as per today, or:

  • Any movies, where trailers are available, especially for Amazon Instant Movies, have two formats for an associate plug-in.  The first plugin for low bandwidth sites, the user still continues to see a flattened image of the DVD case or CD album, but in addition, have two links, play trailer, or play music. 
  • The second, more content rich plugin, would have either one, or a rotating collection of playing trailers and/or music, with album image.  The trailer can play the standard or an abridge trailer, as defined in the settings. The music would play at the normal sample length, or an curtailed length, based on the settings.  Finally, there are two image overlays, one in the bottom left, the other in the right, but the user may click, the left has a More Info, the right says Buy @ Amazon.

The user would select a collection of songs as well as movie trailers, or the user may make multiple collections, that have movies, songs, or both.

This same Amazon Associates plugin for web sites or blogs, may be applied to other products, such as Audible.com and audio books with samples.  In the Amazon Associates Product Advertising API WSDL, I did not notice references to ‘sample’ or ‘Trailer’, so I do not think a third party can build this plugin or widget as of yet.

Wal-Mart to compete with Amazon Locker Concept

Wal-Mart steps up its online game with help from stores | Reuters.

This is a very interesting perspective.  From the corporate side, they are mazimizing the logistics of their order workflow, gaining more control, and perhaps cost savings.  We MAY see fewer options with free shipping on items, e.g. over N dollar value orders, across retail if this process workflow catches on in the industry.

The consumer, for lower cost items, where they shop on line, and already pick up their orders, we will see a positive result in the customer service experience, e.g. the consumer does not have to wait on lines to pick up their order.  However, if the consumer would have, under the old program, had free shipping, this may alter the perspective of the customer, that they are getting less service, i.e. before they did not have to leave their homes.

All and all, if these stores balance their models, and continue to offer the free shipping option for high price items, whatever the watermark, e.g. $50 USD, and this option is available for all items which can fit in the locker, many consumers may be pleased.  If Amazon was smart, they might take advantage of as many partners as possible, as well as leveraging many of the small ‘long standing’ for rent shops, with one employee, if their logistics workflow includes not just leveraging partner’s shipping workflow.

In addition, this option, if progressed or evolved for retail, B&M, we may see fewer shortages.  That is for another article.