Lunch Talk: Quantum Computing

a discussion of why now is the right time to be thinking about this new technology and some of the recent developments that have been made, laying the groundwork for the future of this computing model.

Stanford CSP. BUS 152 - Innovation Timing. Session 2, Quiz 1

Background

The public's interest in Bitcoin rose sharply in 2013-14.

For example, on January 21, 2014, in a NYT article titled "Why Bitcoin Matters", Marc Andressen wrote:

Bitcoin gives us, for the first time, a way for one Internet user to transfer a unique piece of digital property to another Internet user, such that the transfer is guaranteed to be safe and secure, everyone knows that the transfer has taken place, and nobody can challenge the legitimacy of the transfer. The consequences of this breakthrough are hard to overstate.

Despite its great promise, this major breakthrough has not materialized yet. Nevertheless, the Google Trends chart above shows a noticeable uptick in Bitcoin-related interest in 2017. For example. a recent post on CloudTech by James Bourne titled "Blockchain beyond Bitcoin: Assessing the enterprise use cases" states that the technology "has serious potential to disrupt a multitude of industries." Also, Cade Metz in a January 6, 2017, Wired article titled "Bitcoin Will Never Be a Currency—It’s Something Way Weirder" reports on the general sentiment about Bitcoin, "Bitcoin is not something the average person will ever use to buy and sell stuff... It’s not something that will improve what the world has, such as money or stock. It’s something that will give the world stuff it has never had."

Quiz:
1. In your opinion, does Bitcoin follow the process generally described as Hype Cycle? Explain briefly.
1a. If yes, what is the current stage of the technology relative to the cycle?
1b. If no, how do you explain the 2014 peak and the significant investments VC funds put into Bitcoin-related startups?

2. Is the 2017 Bitcoin (and related technology) comeback for real? Where would you place the technology on the S-curve and Adopter Distribution chart as of today? Explain briefly.

How marketing affects the brain

I'm taking Dr. Hunt's History of Wine course at Stanford University CSP - a great learning experience. Wine fascinates me not only because (in moderate amounts) it stimulates creative thinking. From an inventor perspective, wine is interesting because it defies the common wisdom "Necessity is the mother of invention." We, humans, invented and perfected an incredible variety of wines and spirits just to make our lives more enjoyable. Arguably, the invention of wine turned enjoyment into a necessity in the modern society. Since enjoyment is a highly subjective matter, wine can serve as our entry point into the world of studying how attitudes affect human perceptions and thinking.

In 2007, a group of scientists from CalTech used wine tasting to study the impact of marketing on people's brains.

It's been widely reported that when subjects know the price of wine they consistently give high ratings to expensive wines. It's also known that in blind trials subjects don't find much difference between expensive and cheap wines. The important questions are, "How does the price information skew our brainwork? Does expensive wine taste better because we anticipate a better tasting experience from an implicit marketing message that a higher price means a higher product quality?" Here's an excerpt from the published paper:

Because perceptions of quality are known to be positively correlated with price (9), the individual is likely to believe that a more expensive wine will probably taste better. Our hypothesis goes beyond this by stipulating that higher taste expectations would lead to higher activity in the medial orbitofrontal cortex (mOFC), an area of the brain that is widely thought to encode for actual experienced pleasantness (6, 10–16). The results described below are consistent with this hypothesis. We found that the reported price of wines markedly affected reported EP and, more importantly, also modulated the blood-oxygen-level-dependent (BOLD) signal in mOFC.

In short, a $90 price tag activated the brain's pleasure center more than a $10 one - an almost 10X impact! Since in both cases researchers used the same wine, areas of the brain responsible for the more basic perceptions, including smell and taste, did not make any difference. The findings of the study was consistent with the placebo effect. External marketing information dominates internal perceptions.

As an exercise in creative thinking, we can try to use these results beyond the realm of wine tasting. For example, how does a perceived value of a startup or its founders affect the valuation in the early stages of financing when no objective data can be found yet? Are hype cycles are endemic in the high-tech industry because there's an inevitable time gap between the real and imaginary results of proposed innovations? Is the Mathew Effect hardwired into human brains?

tags: effect, brain, entrepreneurship, biology, research, science, perception, hype

Amazon's "anticipatory" patent: Let's cut through the BS!

Many news outlets, including the Wall Street Journal, wrote recently about Amazon's US Patent 8,615,473, issued on December 24, 2013, titled "Method and system for anticipatory package shipping." For example, Tyler Cowen, of the marginalrevolution.com fame, quoted a catchy 2-liner to describe the invention:

The Seattle retailer in December gained a patent for what it calls “anticipatory shipping,” a method to start delivering packages even before customers click “buy.”

The title of Cowen's blog entry "Back to the Amazon future" tells more about people's hyped-up perception of Amazon's delivery prowess than the actual invention.

That is, the patent is a lot more mundane than journalists and bloggers imagine. It covers a scenario where a particular item can be re-routed to a specific address while it is still being shipped to a general geographical area.

The pre-emptive part of the invention is not new at all. Retailers routinely ship products before people buy the stuff. When you go to a grocery store you buy a watermelon that was pre-emptively shipped to this location for your buying convenience. The same goes for TVs, cameras, flowers, etc. It's obvious that the retailer takes into account what Amazon calls "business variables," e.g. that people buy more flowers before the Valentine's Day, than the Father's Day.

Let's de-glamourize the patent by thinking that we deal with low-tech railroad coal shipments, instead of high-tech Amazon robotic drones. Imagine that the year is 1914 and you are in the coal business. You know seasonal patterns and you anticipate customer orders based, e.g. on the weather. If it's going to be cold in Michigan you know that people will burn more coal to heat their houses. They've done it year after year after year. Being smart, you start shipping coal to Michigan by railroad before you receive specific orders. Then, when you receive the actual orders you send a telegram to the railroad company and ask them to re-route some of the coal cars to Detroit an Ann Arbor, which happen to be close to one of your Michigan coal warehouses. That's it. Only instead of coal cars in 1914, Amazon ships socks and shoes in 2014. Nothing magically pre-emptive here.

Amazon's US Patent 8,615,473 is one of the three the company received so far on various aspects of the same invention.

The patents cover the same basic scenario: ship a package to a general geographic area, then notify the shipping company of a specific address in the area before the final delivery. Most likely, the patents will never be used because Amazon is already a dominant force in the industry.

To me, this particular media event illustrates multiple layers of "aboutness" that people pile up on top of each other when describing a hypothetical object or process. First, Amazon writes a patent application about a proposed modification to a shipping process. Then, the US Patent Office issues office actions that finalize patent claims about the invention and grants a patent. Then, a blogger reads the patent and writes a blog post about it. Then, an economist twits about the blog post. Etc. etc. Once an error creeps into the aboutness process, the entire information trail ends up leading nowhere.

tags: invention, innovation, patent, hype, amazon, media, aboutness

Google + Nest GSV = the Web is Dead

Google announced that they are buying Nest GSV, the smart thermostat company, for $3.2B. The acquisition extends Google's push into the Internet of Things (IoT), including robotics, automatic cars, etc. Gartner's 2013 Hype Cycle report puts IoT firmly at the top of the hype chart.

Recently, Cisco added to the hype with an estimate for the IoT market of $19T by 2020. Since Google missed badly on Social Networking, the company is eager not to miss on the next big thing. With the web going away (Scalable Innovation, Chapter 20), Google needs new massive sources of data streams to process; otherwise, all their data-crunching technology could become worthless. The Internet of Things seems to fit the requirements. Although the valuations are of hype-size proportions, today's web advertisement (search) produces enough cash to finance the future S-curve.

When I worked in research on IoT concepts in the early 2000s, it was too early. We did get a number of good patents, e.g. US7,620,703, US7,257,839, US7,092,861, US7,069,345, US6,838,986, out of that work, but the inventions didn't become mass-market innovations back then. Even today, it's still too early for the mass market. Interesting questions to consider would be, What does it mean to be too early? What problems do we need to solve, so that an innovation in this particular technology market becomes real?


tags: invention, innovation, hype, google, system, synthesis, web

Nobel Prize in Economics: Using models to make sense of models.

Lars Peter Hansen shared 2013 "Nobel Prize" in Economics for his work on models. Below are several slides from his Nobel Prize Lecture. Since I study innovation-related hype, the second slide, which shows how to model distorted beliefs, is quite interesting. Maybe we can use this approach to understand why Gartner Hype Cycle keeps showing up in innovation processes.

tags: science, economics, hype, model

Disruption: everything everywhere all the time.

Disruption has become a meaningless buzzword applied to any new technology to make it sound more solid than the good old "cool."

(November 13, 2011. NYT. Disruptions: The 3-D Printing Free-for-All.) - A recent research paper published by the Institute for the Future in Palo Alto, Calif., titled “The Future of Open Fabrication,” says 3-D printing will be “manufacturing’s Big Bang.” as jobs in manufacturing, many overseas, and jobs shipping products around the globe are replaced by companies setting up 3-D fabrication labs in stores to print objects rather than ship them.

 Let's do a quick reality check. What is the problem the technology is going to solve? Assuming the technology works, is there a large-scale need for making more physical things?

I don't think so. The overwhelming trend is toward creating and consuming virtual rather than physical stuff. Electronic books are killing paper books. Electronic toys are killing physical toys. For example, here's what today's kids want for Christmas:

One generation from now, when the presumed 3D revolution is supposed to take over the world, these kids will be into manipulating 3D virtual objects, rather than printing and throwing them out after they turn out ugly.

Further, there's a lot of research that show people prefer experiences to objects in( see for example, Carter & Gilovich, 2010. The Relative Relativity of Material and Experiential Purchases. DOI: 10.1037/a0017145)

Unlike material possessions, which are typically made to fill a specific, concrete purpose, experiences are often purchased for a variety of different reasons, both abstract and concrete.

 

Transportation cost savings will also be negligent because you'll have to transport raw materials for making the stuff in your home/garage/office. Most likely, 3D printers are going to make a difference in rapid prototyping of new devices or making lawn furniture on demand. Is it going to be a disruption? Maybe for the current prototyping methodologies, but far from a revolution in consumer goods.

Local electric power production and storage is needed

Two cases when adding new consumption or production capacity (Tool) leads to unintended consequences for the existing infrastructure (Distribution).

The first example relates to the predicted increase in the number of electric cars in California:

Oct. 23 (Bloomberg) -- California’s push to lead U.S. sales of electric cars may result in higher power rates for consumers in the state, as a growing number of rechargeable vehicles forces utilities to pay for grid upgrades.

A typical Santa Monica circuit, which serves about 10 households, may be overloaded should two or three of those customers charge vehicles simultaneously, even if they do so overnight during off-peak hours, Ted Craver, Edison’s chief executive officer, said in a phone interview on Oct. 20.

While surplus power is available at night at cheaper rates, the grid needs adjustments to handle such charging, Craver said. For example, additional or larger transformers may be needed in neighborhoods with numerous plug-in car owners.

In the second example, Science magazine describes the potential impact of biofuel production on the water distribution infrastructure:

Biofuels promise energy and climate gains, but in some cases, those improvements wouldn't be dramatic. And they come with some significant downsides, such as the potential for increasing the price of corn and other food staples. Now, a series of recent studies is underscoring another risk: A widespread shift toward biofuels could pinch water supplies and worsen water pollution. In short, an increased reliance on biofuel trades an oil problem for a water problem.

Making matters worse, other U.S. energy sectors are growing and increasing their demand for water. Another recent report from Argonne by Deborah Elcock, an energy and environmental policy analyst, for example, found that water consumption for energy production in the United States will jump two-thirds between 2005 and 2030—from about 6 billion gallons of water per day to roughly 10 bgd—driven primarily by population growth. About half of that increase will go toward growing biofuels.

tags: five element analysis, tool, distribution, system, greatest, maturity, hype, energy

Growing beyond hype

During the next four years, the cloud is predicted to grow very rapidly:

Another good news is that we seem to have passed the peak of the hype cycle some time earlier this year.

tags: cloud,  hype, growth, niche construction, artefact,storage