The Mindfulness Meme

Mindfulness is increasingly arriving as an au courant meme to denote a deliberate, relaxed, and enlightened understanding when interacting with the self and others.

Despite occasional blips to the contrary, Steven Pinker (in The Better Angels of Our Nature) seems to be right in citing the overall decline in violence over the centuries of human existence. Even in the shorter term, this is visible in a Google Trends analysis of the keywords 'mindfulness' and 'assault weapons' appearing in news headlines (Figure 1).

 

Figure 1. Keywords in News Headlines 2005-2012: 

Mindfulness (blue) and Assault Weapons (red) Source: Google Trends

What is your SQ?

There was IQ, then EQ, and now, SQ! SQ – spiritual intelligence quotient – is now a criterion for successful leadership.

In the wake of scientific support for meditation and other mindfulness practices, and as businesses in the social capital movement transitioned to triple bottom lines (adding social and environmental outcomes to the profit motive), so too now the paradigm for successful leadership is changing. Empathy-devoid environments are no longer acceptable.

There is a claim that the successful contemporary leader in any field has the triumvirate of intellectual intelligence, emotional intelligence, and spiritual intelligence. Part of 'Spirituality 2.0' is the act of transferring quality-of-life attributes from spiritual practice to mainstream application.

The high-SQ leader has self-mastery and behaves with wisdom and compassion while maintaining inner and outer peace, being present in an embodied way, and connecting with others both intellectually and emotionally.

Top 10 traits of high-SQ leaders:

1. Calm and centered 
2. Compassionate 
3. Courageous
4. Passionately committed 
5. Forgiving 
6. Authentic, walks-the-talk 
7. Humble 
8. Wise 
9. Peaceful, nonviolent 
10. Service-oriented

Application of Complexity Theory: Away from Reductionist Phase Transitions

Reductionism persists as a useful node in the possibility space of understanding and managing the world around us. However the possibility space is now expanding to higher levels of resolution such as a focus on complex systems. Learning and tools are ratcheting in lock-step.

Some of the key complexity-related concepts in understanding collective behavior in real-life physical systems like the burning of a forest fire include:

• Organization and Self-Organization: Self-orchestration into order in both living and non-living systems, for example: salt crystals, graphene, protein molecules, schools of fish, flocks of birds, bee hives, intelligence and the brain, social structures 
• Order and Stability of Systems: Measurements of order, stability, and dynamical break-down in systems such as entropy, symmetry (and symmetry-breaking), critical point, phase transition, boundaries, and fractals (101 primer)
• Tunable Parameters: An element or parameter which doesn’t control the system, but can be tuned to influence the performance of the system (for example, temperature is a tunable parameter in the complex system of water becoming ice) 
• Perturbation and Reset: How and how quickly systems reset after being perturbed is another interesting aspect of complex systems 

 

Complexity science is not new as a field. What is new is first, a more congruous conceptual application of complexity thought in the sense of appreciating overall continuum of systems phenomena, not trying to grasp for the specific moment of a phase transition. Exemplar of this more comprehensive systems level thinking is Marcelo Gleiser’s reframe of the Grand Unified Theory problem and Sara Walker’s reframe of the Origins of Life problem. The other aspect that is new is the idea of working in an applied manner with complex systems, particularly with tools that are straightforward to implement like the math tools of non-linear dynamics, networks, chaos, fractals, and power laws (many inspired by the work of Stan Strogatz), and Software Tools like NetLogo, a multi-agent programmable modeling environment and ChucK, a digital audio programming language.

 

Broadcasting Preference in the Intention Economy

One key dimension of the future is the presence of multiple currencies. A multicurrency society is already starting to develop where traditional monetary-related currencies are being supplemented with other currencies like reputation, attention, intention, ideas, affinity, preference, health, and resource access.

A book published in May 2012, Intention Economy: When Customers Take Charge, suggests mechanisms to make intent as a currency more explicit, monetized, and implementable. The book extends the author’s previous ideas about vendor relationship management (VRM), which is how consumers might more effectively manage their relationship with vendors.

The issue is that corporations and other entities spend $1.5 trillion per year on marketing to create ‘a bad model of you’ and your purchasing intent (‘50% of marketing dollars are wasted but we don’t know which 50%’). On the other hand, you as a consumer may have trouble defining your demand, and finding and tailoring products and services in the midst of fending off unwanted publicity and inaccurate personalized advertising.

One potential solution for decreasing friction in the narrowband way that vendors and consumers currently interact is having consumers directly communicate their interests and intent. Intent communication could be accomplished through fourth party exchanges, websites like EmanciPay, where consumers may escrow their intention to buy with a down payment of funds to the site (fourth parties are truly independent intermediaries and advocates for the consumer as opposed to current third parties which are more of an accessory to second parties (e.g.; vendors)). Short of making a financial pledge, many other fourth party sites could accommodate less-defined customer specifications for desired products and services.

The Intention Economy then, is where consumers intentcast (e.g.; broadcast their intent) for products and services, even and especially at inchoate and automated levels, so that vendors can be responsive and continue their expertise in constructing solutions that anticipate consumer demand. Some companies are getting onto this bandwagon, like IBM with their "Chief Executive Customer" program, but like any important change and successful implementation, mindset shifts may be required, and tools must be extremely easy to use – where is Twitter for VRM?!

Crowd Models Become Pervasive Across Society

Crowd-based models are becoming so pervasive that almost no major segment of modern life is left untouched by them. The concept of digital crowd models refers to the coordination of large numbers of individuals (the crowd) through an open call on the Internet in the conduct of some sort of activity.

Not only are crowd models an efficient at-scale alternative to former methods that the Internet now affords, but at another level, crowd models are also a node of progress for humanity, both individually and en masse. An inherent property of crowd models is greater autonomy, decision-making, and action-taking by the individual. This means greater individual agency whilst simultaneously enabling group collaboration projects at previously unimaginable scales, for example, possibly ultimately coordinating and employing the cognitive power of millions of human agents.  

Crowd Models by Sector

• In economics, there are crowdsourced labor marketplaces where simple tasks and professional services requests can be posted and fulfilled, crowdfunding websites for financing projects, and group purchasing mechanisms. 
• In politics, crowd models mean the use of big data and social media to organize opinion and action, conduct direct marketing, and affect change. 
• In the social venue, blogs, social networks, and online dating sites are examples of crowd models. 
• In entertainment, there are massively multiplayer online games and virtual worlds. In education, vast eLearning networks are populating the landscape. 
• In health, there are health social networks, digital health collaboration and experimentation communities, crowdscience competitions, and new movements such as the quantified self. 
• In the legal venue, digital public goods have arisen through crowd contributions such as the Wikipedia, online health databanks, and other data commons resources.

Supercomputing Increments Towards the Exaflop Era

The November 2012 biannual list of the world’s fastest supercomputers shows the winner incrementally improving over the last measure. The Titan (a Cray XK7, Opteron 6274 16C 2.200GHz, Cray Gemini interconnect, NVIDIA K20x) is leading with 17.6 petaflops per second of maximum processing power. This was only an 8% increase in maximum processing speed as compared to other recent increases of 30-60%, but a continued step forward in computing power.

Supercomputers are used for a variety of complicated modeling problems where simultaneous processing is helpful such as weather modeling, quantum physics, and predicting degradation in nuclear weapons arsenals.

Figure 1. World's Fastest Supercomputers. (Source)

Increasingly, supercomputing is being seen as just one category of big data computing along with cloud-based server farms running simple algorithms over large data corpuses (for example Google’s cat image recognition project), crowd-based distributed computing networks (e.g.; protein Folding@home with 5 petaflops of computing power, and crowdsourced labor networks (e.g.; Mechanical Turk, oDesk, CrowdFlower - theoretically comprising 7 billion Turing test-passing online agents).
 

IOT Appliances Blur the Distinction between Matter and Man

The growing wireless Internet of Things (Sensor Mania!) could bring a ‘Cambrian explosion’ in wearable computing and the number and types of Internet-connected sensors, devices, hardware platforms, software programs, and end-user applications.

There could be an adjustment period as humans adapt to an Internet of Things (IOT) landscape with more kinds of data and different mindsets, activities, behaviors, and perspectives when interacting with these data.

Whole fields of study previously limited to self-reported information such as psychology could be radically supplemented and transformed with objective metrics obtained from the IOT.

The IOT is in the early stages of modulating data onto the world of existing artifacts.

Increasingly objects may be able to collect their own data and act on it autonomously with pre-set limits and degrees-of-freedom algorithms.

Eventually, the IOT label could become a redundant demarcation as all human-manufactured matter in the future could have integrated sensors and microprocessors.

A next generation of sensors and microprocessors is already being developmentally fashioned from organic, inorganic, and hybridized material, using cutting-edge technologies for manipulating organic and inorganic matter such as synthetic biology and molecular nanoelectronics.

Distinctions between man and machine, and subject and object could blur further as IOT appliances eventually create a layer of exosenses to greatly extend current human capabilities and the ability to integrate with the outside world.

More information: "Sensor Mania! The Internet of Things, Wearable Computing, Objective Metrics, and the Quantified Self 2.0"

Crowdsourced Labor, Digital Marketplaces, and the Future of Self-Actualized eWork

The third annual CrowdConf on changing the future of work through Internet-based crowdsourcing labor models was held in San Francisco on October 23, 2012. The field is much larger compared to prior years (2011 and 2010), both practically and intellectually, as a range of industry vendors and other ecosystem members (e.g.; research organizations, foundations, financial community) attended the conference. Participation in crowd-based models has been increasing this year. Crowdfunding (raising money to back projects through an open call on the Internet) platforms like Kickstarter and indiegogo have been used to raise millions of dollars for projects (although both of these sites have announced that they will not be launching a new development, equity crowdfunding). Crowdsourced labor marketplaces too have been growing significantly.

What is Crowdsourced Labor? 
Crowdsourced labor is sourcing human workers via the Internet for any variety of tasks or work product, with or without remuneration, usually including an online system for bidding, quality tracking, and reputation feedback. There are digital labor marketplaces for general tasks, both short activities (e.g.; to recognize images, validate information, create electronic forms, read handwriting, classify data, tag images, transcribe audio, translate languages, and verify business listings) and professional services engagements at sites like CrowdFlower, CrowdSource, oDesk, ClickWorker, Mechanical Turk (from Amazon)) mobileworks (including real-time task-routing to the best candidate online right now), and vocational specialties such as software programming (TopCoder, Elance, vWorker (was Rent a Coder) and Guru), graphic design (99designs, crowdSPRING), writing, editing and proofreading (CloudCrowd, Soylent), document processing (microtask), and customer relationship management (LiveOps). Mobile phone-based task completion is an important category of crowdsourced labor with projects making use of time-cycles while on the go, and sites like Gigwalk ('hire your smartphone army') offering location-specific tasks.

Figure 1. Real-Time Barometer of CrowdFlower's Digital Labor Market (source: CrowdFlower)

Crowdsourced labor also includes uncompensated work in the volunteer, gift, and reputation economies in examples like Twitter’s localization service, the Wendy Schmidt Oil Cleanup X Challenge (a $1.4 m X Prize for solutions to accelerate oil spill cleanup), and crowdscience games and competitions for protein folding prediction, and genetic and other science data analysis at sites like foldit, EteRNA, Phylo, and Kaggle.

The digital marketplace concept extends more generally to that of resource allocation, allowing supply and demand to meet in real-time on the Internet in other models such as a labor markets for physical-world tasks (e.g.; TaskRabbit and Zaarly), and resource allocation (e.g.; AirBNB (apartment rental) and Uber (private driver ride service on-demand)).

Microtask Design 
Crowdsourced labor is starting to be seen as a general resource that any individual or business can tap on demand. To do so, it is helpful to know how to design a microtasking project, which can be done either independently or through third-party vendors like CrowdFlower and CrowdSource. At the conference, YP (Yellow Pages) shared best practices from a photo moderation project: they used Mechanical Turk’s Master’s Pool of photo reviewers (96% accuracy vs. 80% for unqualified task-completers), had a batch size of 40 photos (more produced worse quality), 8 buckets of keep-suppress gradations for evaluation, and a price of $0.04 per batch (1/6 the price quoted by a third-party vendor).

The Future of Work 
The conference considered more broadly the future directions of work, labor, and organizations. One analogy is that similar to the cash register being a decisive node that allowed business to explode from small family-owned, trust-based activity to large-scale enterprise, crowdsourced labor could be a similarly explosive node. Productive enterprise is no longer confined to physically-based organization-internal corporate structures. Management has been a technology, and crowdsourcing and algorithms are disrupting it. The new challenge becomes how to build and structure work for large-scale crowdsourcing, for many kinds of productive enterprise. There are new capital streams (e.g.; social, political, intellectual, and affective) available to be directed for productive construction on a global, flexible, fungible, and accountable basis. Workers and more generally humans can be put together in new ways, likely in increasingly automated ways to direct individuals to projects in areas of personal interest, for example rated on a self-actualization and contribution scale.

Sensor Mania! The Explosive Growth of the Wireless Internet of Things

The Internet of Things (IOT) is the idea of everyday objects being interconnected network devices by having embedded sensors and communicating wirelessly with the Internet. An increasing trend is for real-world objects like buildings, roads, household appliances, and human bodies to become connected to each other and the Internet via sensors, tiny microprocessor chips that record and transmit data such as sound waves, temperature, movement, and other variables. Vernor Vinge has estimated that 5% of human-constructed objects have embedded microprocessors.

Some of the most familiar Internet-connected devices are computers such as laptops, servers, smartphones, and tablets (e.g.; iPads, etc.) but the IOT concept is much broader. One way of organizing the IOT is by market segment where there are three main categories: 

1. Monitoring and controlling the performance of homes and buildings - Some of the basic IOT applications underway in the connected home and buildings include temperature monitoring, security, building automation, remote HVAC activation, off-peak electricity use for non-time critical activities, and smart power meters. The worldwide use of smart power meters is expected to grow from 130 million in 2011 to 1.5 billion in 2020. 
2. Automotive and transportation applications -  Some of the many automotive and transportation IOT uses include the Internet-connected car (syncing productivity, information, and entertainment applications), traffic management, direction to open parking spots, and electric vehicle charging. It is estimated that 90% of new vehicles sold in 2020 will have on-board connectivity platforms, as compared with 10% today. In industrial transportation, train operators like Union Pacific use IOT infrared sensors, ultrasound, and microphones to monitor the temperature and quality of train wheels. 
3. Health self-tracking and personal environment monitoring - One of the biggest IOT growth areas is measuring individual health metrics through self-tracking gadgets, clinical remote monitoring, wearable sensor patches, WiFi scales, and a myriad of other biosensing applications.

Singularity Summit 2012: Image Recognition, Analogy, Big Health Data, and Bias Reduction

The seventh Singularity Summit was held in San Francisco, California on October 13-14, 2012. As in other years, there were about 600 attendees, although this year’s conference program included both general-interest science and singularity-related topics. Singularity in this sense denotes a technological singularity - a potential future moment when smarter-than-human intelligence may arise. The conference was organized by the Singularity Institute, who focuses on researching safe artificial intelligence architectures. The key themes of the conference are summarized below. Overall the conference material could be characterized as incrementalism within the space of traditional singularity-related work and faster-moving advances coming in other fields such as image recognition, big health data, synthetic biology, crowdsourcing, and biosensors.

Key Themes:

• Singularity Thought Leadership
• Big Data Artificial Intelligence: Image Recognition
• Era of Big Health Data
• Improving Cognition: Bias Reduction and Analogies
• Singularity Predictions

Singularity Thought Leadership
Singularity thought leader Vernor Vinge, who coined the term technological singularity, provided an interesting perspective. Already since at least 2000, he has been referring to the idea of computing-enabled matter and the wireless Internet-of-things as Digital Gaia. He noted that 5% of objects worldwide are already embedded with microprocessors, and it could be scary as reality ‘wakes up’ further, especially as we are unable to control other phenomena we have created such as financial markets. He was pessimistic regarding privacy, suggesting that Brin’s traditional counterproposal to surveillance, sousveillance, is not necessarily better. More positively, he discussed the framing of computers as a neo-neocortex for the brain, extreme UIs to provide convenient and unobtrusive cognitive support, other intelligence amplification techniques, and how we have been unconsciously prepping many of our environments for robotic operations. There has also been the rise of an important resource in crowdsourcing as the network (the Internet plus potentially 7 billion Turing-test passing agents) filters optimal resources to specific cognitive tasks (like protein folding analysis).

Big Data Artificial Intelligence: Image Recognition
Peter Norvig continued in his usual vein of discussing what has been important in resolving contemporary problems in artificial intelligence. In machine translation (interestingly a Searlean Chinese room), the key was using large online data corpuses and straightforward machine learning algorithms (The Unreasonable Effectiveness of Data). In more recent work, his lab at Google has been able to recognize pictures of cats. In this digital vision processing advance (announced in June 2012 (article, paper)), the key was creating neural networks for machine learning that used hierarchical representation and problem solving, and again large online data corpuses (10 million images scanned by 16,000 computers) and straightforward learning algorithms.

Era of Big Health Data 
Three speakers presented innovations in the era of big health data, a sector which is generating data faster than any other and starting to use more sophisticated artificial intelligence techniques. Carl Zimmer pointed out that new viruses are continuing to develop and spread, and that this is expected to persist. Encouragingly, new viruses are genetically sequenced increasingly rapidly, but it still takes time breed up vaccines. A faster means of vaccine production could possibly come from newer techniques in synthetic biology and nanotechnology such as those from Angela Belcher’s lab.  Linda Avey discussed Curious, Inc, a personal data discovery platform in beta launch that looks for correlations across big health data streams (more information). John Wilbanks discussed the pyrrhic notion of privacy provided by traditional models as we move to a cloud-based big health data era (for example, only a few data points are needed to identify an individual and medical records may have ~500,000). Some health regulatory innovations include an updated version of HIPAA privacy policies, a portable consent for granting the use of personalized genomic data, and a network where patients may connect directly with researchers.

Improving Cognition: Bias Reduction and Analogies (QS’ing Your Thinking) 
A perennial theme in the singularity community is improving thinking and cognition, for example through bias reduction. Nobel Prize winner Daniel Kahneman spoke remotely on his work regarding fast and slow thinking. We have two thinking modes, fast (blink intuitions) and slow (more deliberative logical) thinking, both of which are indispensable and potentially problematic. Across all thinking is a strong inherent loss aversion, and this helps to generate a bias towards optimism. Steven Pinker also spoke about the theme of bias, indirectly. In recent work, he found that there has been a persistent decline in violence over the multi-century history of time, possibly mostly due to increases in affluence and literacy/knowledge. This may seem counter to popular media accounts which, guided by short-term interests, help to create an area of societal cognitive bias. Other research regarding cognitive enhancement and the processes of intelligence was Melanie Mitchell’s claim that analogies are a key attribute of intelligence. The practice of using analogies in new and appropriate ways could be a means of identifying intelligence, perhaps superior to other mechanisms such as general-purpose problem solving, question-answering, or Turing test-passing as the traditional proxies for intelligence.

Singularity Predictions 
Another persistent theme in the singularity community is sharpening analysis, predictions, and context around the moment when there might be greater-than-human intelligence. Singularity movement leader Ray Kurzweil made his usual optimistic remarks accompanied by slides with exponentiating curves of technology cost/functionality improvements, but did not confirm or update his long-standing prediction of a technological singularity circa 2045 [1]. Stuart Armstrong pointed out how predictions are usually 15-25 years out, and that this is true every year. In an analysis of the Singularity Institute’s database of 257 singularity predictions from 1950 forward, there is no convergence of time in estimates ranging from 2020-2080. Vernor Vinge encourages the consideration of a wide range of scenarios and methods including ‘What if the Singularity Doesn’t Happen.’ The singularity prediction problem might be improved by widening the possibility space, for example perhaps it less useful to focus on intelligence as the exclusive element for the moment of innovation, speciation, or progress beyond human-level; other dimensions such as emotional intelligence, empathy, creativity, or a composite thereof could be considered.

Reference
1. Kurzweil, R. The Singularity is Near; Penguin Group: New York, NY, USA, 2006; pp. 299-367.

The Evolution of the Quantified Self into the Qualified Self and the Extended Exoself

The Quantified Self is a fast-growing movement of individuals who are interested in personalized knowledge through self-tracking. So far, 5,000 QS’ers have come together at 70 worldwide meetup groups to share the details of their projects, discussing what they did, how they did it, and what they learned. Three areas were thematized at the group’s third conference held at Stanford University, September 15-16, 2012:

• The need for a data commons where participants may contribute personalized self-tracking data streams 
• Improving quality of life by tracking impact rather than actions in areas such as mood, happiness, productivity, well-being, and goal-achievement 
• The notion of current QS activities being an intermediary step towards the development of an extended self with exosenses like augmented reality vision overlays and haptic data that can be perceived as a sensation

Neural Data Privacy Rights

One result of the massive explosion in the wireless internet-of-things is that a wide range of new personalized data streams are being created.

Biometric data (e.g.; heart rate variability, respiration, galvanic skin response, temperature, daily steps taken, etc.) is sensitive enough but neurometric data is even more so. The immediate reaction would be fear of discovery and unwillingness to share neural data streams, real-time thought feeds (e.g.; Twitter, only more direct, even less filtered!), eye-tracking data, and EEG streams. But is this even realistic with the pace of advancing technology? Will a personal Faraday cage be bundled with Google's Project Glass?

As individuals and societies, we need to problematize issues related to the continuous streaming health information climate in ways that support and facilitate humanity's future directions in mature, comfortable, and empowering ways, with an eye to the future as opposed to the immediate knee-jerk privacy-at-all-costs reaction of the present.

The Quantified Self becomes the Qualified Self and the Exoself

Quotable quotes from the third Quantified Self conference held at Stanford University September 15-16, 2012. 

• Can I query my shirt or am I limited to consuming the querying that comes packaged in my shirt?
• Quantified Self enables the constant creation of this thing called the self
• We think more about our cats/dogs than we do our real pets, our microbiome
• Information conveyance, not dataviz
• Quantified emotion and data sensation (haptics)
• Display of numerical data and graphs are the interface
• Quantifying is the intermediary step...exosenses (haptics, wearable electronic senses) is really what we want
• Perpetual data explosion
• Our mission as Quantified Selves is to discover our mission

Figure 1. Word Cloud Visualization of Agenda Topics at the third Quantified Self Conference.

Sensor Mania! TechCrunch Disrupt Hardware Day!

Taking advantage of Sensor Mania! – the exploding wireless internet of things – TechCrunch Disrupt featured a special Hardware day on September 12, 2012 at its annual conference held in San Francisco, CA. 29 companies in a wide range of areas presented their hardware products, as 26 had at a similarly successful event in New York in May 2012. If underwhelming in ‘new new thing’ innovation, the startups at least appeared commercializable for the most part. Perhaps the biggest similarity in the eclectic mix was the high number of Kickstarter projects (the new alpha customer sales and financing platform).

The biggest interesting category of startups was biosensors, including a consumer EEG company (InteraXon), a sports sensor training program (GolfSense), an integrated biosensor platform for personalized pain management delivering the equivalent of white noise stimulus to nerve endings (Thimble Bioelectronics (integrating the Somaxis muscle sensor)), and a pedometer watch and social gaming fitness app for kids (Sqord).

Another interesting category of startups was internet-of-things companies. Ninja Blocks (‘the API for atoms’) was providing a standard offering of an internet-enabled console block plus five home sensor units (with distance, temperature, motion, camera, etc. sensor capabilities) for $200. Similarly, knut was providing a small, battery powered, Wi-Fi enabled sensor hub for real-time monitoring in the home environment for $80.

Figure 1: Electric Skateboard from Boosted Boards

The other companies were a mix including electric skateboards (Boosted Boards as shown in Figure 1), kitchen products (sous vide cooking (Nomiku) and high-end coffee brewing (Blossom Coffee)), standing desks, flashlights 2.0 (HexBright), rear-view cycling camera unit (Cerevellum), iPad kiosks (Lilitab), and the expected photo, audio (Vers), and gaming-related apps.

Consumer Products go Social: from Shelf-Buy to Ongoing Dialogue

With the modern expectation of a social layer for everything, together with real-time feedback, data infographics, personalized recommendations, and gamification fun and reward, all received ambiently on the Pebble watch (the smartwatch is the new platform), consumer product delivery is being revolutionized.

Just as new media crippled juggernaut industry business models in computing, email, newspapers, TV, and music distribution, an even more fundamental shift is coming to consumer products. The successful game is transitioning from a one-off shelf-buy to an ongoing dialogue with consumers, providing a consumer product service.

One way this could be facilitated is by delivering preventive wellness/peak health enhancement services (“condition-as-a-service”) at the growing number of in-store clinics (à la WalMart Vison Centers) at drugstores (CVS, Walgreens) and high-end food stores (e.g.; Whole Food’s Wellness Club). How soon is the Whole Body and Whole Mind’s Neurofeedback Demo and Service Purchase coming along with Whole Food’s in-store destination edutainment sommelier training?