The science of biological timing

Today, the Nobel Prize Committee awarded the 2017 Prize in Physiology or Medicine to three American scientists - Jeffrey C. Hall, Michael Rosbash and Michael W. Young, for their discoveries of molecular mechanisms controlling the circadian rhythm.
From the press release:

Off course, there's no "clock" in the body. Biological organisms use protein accumulation cycle to adapt to the rotation of the Earth. It took nature billions of years to develop this amazing adaptation. Now, we are figuring out ways to understand and and adapt to innovation timing, i.e. cycles of new ideas, including science and technology.

Invention of the Day: Hypodermic Syringe

I'm reading a wonderful book by Roger Bridman - 1,000 Inventions and Discoveries. It documents an incredible range of human ingenuity from thousands years ago to our days. For example, here's an invention that we take for granted today: hypodermic syringe.

Remarkably, it was invented by two people in different countries. As the book says, "[in 1853] In Scotland, physician Alexander Wood invented the hollow needle and adapted Pravaz’s device to go with it, forming the first hypodermic syringe." That is, the invention cannot be attributed to each of them separately because a new system — the syringe — provides functionality beyond the sum of its parts. A well-defined interface between the parts, the cylinder and the needle respectively, enabled rapid innovation in manufacturing technologies and use. For example, here's how hollow needles are produced today.

From an innovation timing perspective, we need to be aware that the business success of the new injection technology was determined by a major invention that came about much later.

By the late 1800s hypodermic syringes were widely available, though there were few injectable drugs (less than 2% of drugs in 1905). Insulin was discovered in 1921. This drug had to be injected into the bloodstream, so it created a new market for manufacturers of hypodermic needles and drugs.

Overall, the invention of the hypodermic syringe illustrates a number of important principles for pragmatic creativity:
- a new combination of parts has to produce a new system effect;
- no new science is necessary for making a technology breakthrough;
- a well-defined interface between parts enables rapid innovation on both sides, e.g. the cylinder and the needle;
- the success of the invention comes from a new use, which may require a new science, e.g. liquid penicillin;
- the combination of new parts (cylinder + needle) and use (liquid drug) form Dominant Design and Use patterns that remain stable for decades, if not centuries.

Psychology of Creativity: Art, Science and Technology

Until the middle of the 20th century, creativity was generally considered as a psychological attribute of an artist and, sometimes, of a scientist. Then in the late 1950s, J.P. Gulliford applied the idea of creative thinking to technological inventions.

Nowadays, engineers and scientists are expected to be creative. A recent paper shows how creativity in science/tech and art relate to personality traits, the so-called Big Five:

The Big Five personality dimension Openness/Intellect is the trait most closely associated with creativity and creative achievement.

We confirmed the hypothesis that whereas Openness predicts creative achievement in the arts, Intellect predicts creative achievement in the sciences. Inclusion of performance measures of general cognitive ability and divergent thinking indicated that the relation of Intellect to scientific creativity may be due at least in part to these abilities. Lastly, we found that Extraversion additionally predicted creative achievement in the arts, independently of Openness. Results are discussed in the context of dual-process theory.

A related paper outlined the overall relationship between the Big Five, by grouping them into two complementary categories - Stability and Plasticity.

Remarkably, the brain uses a broad range of cognitive strategies to pursue goals within a social context. Given a chance, we can exercise our creative options through technological innovation.

As a side remark, from an innovation theory perspective, the brain and society solve the stability-plasticity dilemma by using both traits, e.g. through the separation in space and time.

Apple needs a new product

Steve Jobs used iPod's success to launch the iPhone. If Apple doesn't create a breakthrough product within the next two years, the company could be in trouble.

So far, the iWatch doesn't even register on the trendline.

Lunch Talk: Artificial Intelligence 65 years ago

Claude Shannon demonstrate an electro-mechanical mouse that navigates a labyrinth, computes and remembers the optimal path. (Bell Labs, 1950s)

tags: innovation, science, technology, lunchtalk, BUS239

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

Background

In a 2017 Hype Cycle-related article, Gartner, an American Research and Advisory firm, put Deep Learning and Machine Learning at the top of the Hype Cycle.

In a follow-up article about Artificial Intelligence, Gartner mentioned 5 AI myths, including #1 "Buy an AI to solve your problems." The article says, "Enterprises don’t need an “AI.” They need business results in which AI technologies may play a role."

An independent investigation by Stats.com seems to confirm the conclusion. The publication considered the track record of IBM's Watson for Cancer, an AI system deployed in many hospitals around the world, and found that "the supercomputer isn’t living up to the lofty expectations IBM created for it." Furthermore,

Perhaps the most stunning overreach is in the company’s claim that Watson for Oncology, through artificial intelligence, can sift through reams of data to generate new insights and identify, as an IBM sales rep put it, “even new approaches” to cancer care. STAT found that the system doesn’t create new knowledge and is artificially intelligent only in the most rudimentary sense of the term.

IBM denies the assertions and says that the technology is on track "to offer guidance about treatment for 12 cancers that account for 80 percent of the world’s cases" by the end of the year.

Questions

1) Do you agree with the Gartner's assessment that AI in general, and Deep Learning and Machine Learning in particular are overhyped? Explain your opinion and provide supporting evidence.

2) In your opinion, which technology and business areas will benefit the most from rapid adoption of various forms of AI? Which forms of AI will play the most significant role? Explain briefly.

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 74. Session 3 Quiz 1.

Background:

MIT Technology Review lists face-detecting systems as one of the top 10 innovations for 2017.

The technology figures to take off in China first because of the country’s attitudes toward surveillance and privacy. Unlike, say, the United States, China has a large centralized database of ID card photos. During my time at Face++, I saw how local governments are using its software to identify suspected criminals in video from surveillance cameras, which are omnipresent in the country. This is especially impressive—albeit somewhat dystopian—because the footage analyzed is far from perfect, and because mug shots or other images on file may be several years old.

Facial recognition has existed for decades, but only now is it accurate enough to be used in secure financial transactions. The new versions use deep learning, an artificial-intelligence technique that is especially effective for image recognition because it makes a computer zero in on the facial features that will most reliably identify a person.

Quiz:

Read the entire article and answer the following questions:
1. Does facial recognition covered in the article represent a new technology? Explain briefly.
2. Will the technology become important outside of China? Explain briefly:
2.1. If the answer is yes, what markets/applications will benefit from it?
2.2. If the answer is no, what barriers will prevent its diffusion?

The Services Revolution: Why Social Networks Turned Into an Instituion

Last month I gave a talk (pdf) on innovation timing at OpenWay Club. The presentation covered, among other topics, the unfolding technology revolution in services. The talk drew on several key sources, including the work of Oliver E. Williamson, a Nobel Prize winner in economics from UC Berkeley, Cesar Hidalgo's book "Why Information Grows", and our book with Max Shtein "Scalable Innovation."

My goal was to show that new technologies have fundamentally changed the nature of services because they commoditized "specificity" and "recurrence." (see figures below). That is, in a networked digital world knowing your customers and interacting with them on a regular basis is dramatically less expensive than in a "stand alone brick-and-mortar" world. To illustrate the main points, here's a screen shot of a relevant page from Hidalgo's book (with my annotations) and several slides from the talk.

(The recent purchase of Whole Foods by Amazon is another example of the shift to Groceries-As-Service model, where Amazon leverages its customer insights into recurring retail sales.)

Even more importantly, the new service models have become a major global institution because they addressed the fundamental issue that plagued service businesses since ancient times. Douglas C North (Nobel Prize in Economics, 1993), described the problem in game theory terms:

In the world of personal exchange (recurring-specific - ES), it pays for parties to an exchange to cooperate, because the parties have personal knowledge of the other players and there is the possibility for repeat dealings between the parties. But in a world of impersonal exchange, it pays for the parties to defect, ceteris paribus. With impersonal exchange, the world is one in which there is not an iterated game.... One does not know anything about the other players, and indeed there are a large number of players.

That is, in traditional transactions players on both sides have incentives to cheat because they don't know each other personally or through a personal network. Therefore, in 1999 North suggested that to make the global marketplace efficient and scalable a new model had to be invented:

...we are going to have to devise institutions de novo that attempt to confront and deal with worlds of impersonal exchange.

Remarkably, new service models, such as Airbnb, Uber, Amazon, Alibaba, Instaply and others provide a glimpse of the institutions to come. Since identities of sellers, buyers and recommenders are known, parties are less likely to cheat; therefore, the number and quality of transactions shows rapid growth.  Although the solution is not perfect, it is a lot more efficient than all attempts to introduce global regulations. It's exciting to see how social networking technologies are redefining the rules of commerce and provide a working alternative to law.

Lunchtalk: TED - Why humans run the world

A TED talk by Yuval Harari, the author of The Sapiens. From the talk description:

Seventy thousand years ago, our human ancestors were insignificant animals, just minding their own business in a corner of Africa with all the other animals. But now, few would disagree that humans dominate planet Earth; we've spread to every continent, and our actions determine the fate of other animals (and possibly Earth itself). How did we get from there to here? Historian Yuval Noah Harari suggests a surprising reason for the rise of humanity.

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.

Stanford CSP. Business 152. Innovation Timing. Session 1, Quiz 3

Background: Sequoia Capital, one of the leading Silicon Valley venture capital firms, typically asks its prospective portfolio startups "Why Now?"

Quiz:
1. List at least 10 major innovations that are either happening now or about to happen within the next 3-5 years.
2. Assume that you are going to participate in one or two of those innovations.
3. Pick your role, e.g. startup founder, employee, corporate CEO/CTO, investor, scientist, student, journalist, president, non-profit, etc.
4. Given your role, select two innovation opportunities that you want to start working on now.
5. Explain "Why now?"

tags: stanford, quiz, innovation

The Structure of Technology Revolutions

Since last summer, I've been working on a book project tentatively (and modestly!) titled "The Structure of Technology Revolutions." The purpose of the book is to show how technology enables completely new possibilities, by breaking trade-offs that are considered unbreakable.

To demonstrate the underlying structure of the innovation process, I'm using Category Theory tools (OLOGs) originally created by D.I. Spivak from MIT.

Here's a series of draft figures with an example of how the logic of innovation had worked in the technology revolution initiated by the automobile with the internal combustion engine (see below).

 Note, that the same logic can be applied to the modern autonomous vehicle. The technology is going to be successful because it creates incredible maneuverability at the "traffic" level of abstraction.

Now, back to the horses example:

Fig. 1 introduces the trade-off between Power and Maneuverability. An eight-horse carriage has a lot of power, but it's difficult to maneuver. Adding more horses will create a huge maneuverability problem. On the other hand, a horse rider is highly maneuverable but he lacks the carrying capacity of the horse carriage.

Fig. 2 introduces a logical representation of a horse carriage and maps it onto a "Conflicting Desires Diagram." That is, we show that any "designer" of a horse carriage faces a trade-off between Power and Maneuverability.

Fig. 3 sheds horse pictures and shows a logical generalization: a horse carriage is a kind of power-driven vehicle. 

Fig. 4 indicates the desired situation (the green dot on the right): We want a vehicle that has the best of both worlds, it's highly powerful and highly maneuverable.

Fig. 5 shows that the Automobile breaks the trade-off and creates a vehicle with the potential to hit the green dot. That is, we create a technology that disentangles human ability to control horses from the power. Thus, we achieve a new state that was considered impossible before.

To model the Autonomous Vehicle technology revolution we need to abstract from "a vehicle" to "traffic" and show how the new technology breaks the traffic congestion trade-off. In general, congestion trade-offs are ubiquitous in economic systems and technology revolutions break through them quite often.

Fig. 6 is a generalized diagram of how technological innovations make the impossible possible.

tags: innovation, trade-off, logic, technology, revolution

Stanford CSP. Business 152. Innovation Timing. Session 1, Quiz 2.

On November 14, 2016, the New York Times wrote a story about a Spark Capital, a 11-year old technology venture firm.

The article opened with a description of one of Spark's recent deals:

Betting on an automated driving start-up in 2015 may not have been the most intuitive gamble at a time when Google and Uber had already declared that self-driving vehicles were among their top research priorities. 

But in the fall of 2015, Spark Capital was one of a few established venture capital firms to wade into the industry, helping lead a $12.5 million investment in Cruise Automation, a start-up based in San Francisco whose software helps cars pilot themselves. One of Spark’s partners became the only outside board member of the firm. 

It was a bet that paid off quickly: Within six months, Cruise sold itself to General Motors for about $1 billion.

Questions:
1. In your opinion, why the timing of the deal turned out to be so good? Was it pure luck? If you were the analyst who "discovered" Cruise Automation back in 2015, how would you justify the $12.5M investment to your VC partners?
2. (optional) Consider the generic innovation diffusion S-curve, as described in Everett Rogers' "Diffusion of Innovations." What stage of the curve the self-driving car technology is now? Why?

tags: course, stanford, innovation, s-curve

Lunch Talk: Counterintuitive approach to building startups (Stanford University)

This is Lecture 3 from a Stanford University course "How to start a startup". The speaker is Paul Graham; his transcript is here: http://tech.genius.com/Paul-graham-lecture-3-counterintuitive-parts-of-startups-and-how-to-have-ideas-annotated

tags: startup, stanford, entrepreneurship, innovation, lunchtalk,

Stanford CSP BUS 74 [Principles of Invention and Innovation], Session 4 Quiz 1

On July 19, 2016, Bloomberg Technology News reported that Google used its DeepMind AI technology to reduce power consumption in the company's data centers:

In recent months, the Alphabet Inc. unit put a DeepMind AI system to reduce power consumption by manipulating computer servers and related equipment like cooling systems. It uses a similar technique to DeepMind software that taught itself to play Atari video games, Hassabis said in an interview at a recent AI conference in New York.

The system cut power usage in the data centers by several percentage points, "which is a huge saving in terms of cost but, also, great for the environment," he said.

The savings translate into a 15 percent improvement in power usage efficiency, or PUE, Google said in a statement. PUE measures how much electricity Google uses for its computers, versus the supporting infrastructure like cooling systems.

Question 1. Using the system model, name the functional element that DeepMind technology helps to improve directly.
Question 2. Based on what you know about the improved element, describe other functional elements within the same system.

A new way to map brains

Neuroscientists at Washington University Medical School created a method to build maps for individual brains:

(MIT Tech Review) Researcher Matthew Glasser says that unlike many previous studies, this map considers several features of the brain simultaneously to mark its boundaries. Some neuroscientists still define brain regions based on a historical map called Brodmann’s areas that was published in 1909. That map divided each half of the brain into 52 regions. Each hemisphere on the new map has 180 regions.

Glasser defined these regions by looking for places where multiple traits—such as the thickness of the cortex, its function, or its connectivity to other regions—were changing together. After drawing the map onto one set of brains, the researchers developed an algorithm to recognize the regions in a new set of brains where the size and boundaries vary from person to person. “It’s not just a map that people can make reference to,” Glasser says. “You can actually find the areas in the individuals that somebody is studying.”

From an innovation perspective, mapping methods create opportunities to systematically explore and coordinate knowledge about a broad class of objects. This particular approach enables scientists and engineers to move back and forth from generalized information about human brain to specific aspects in a particular brain. For example, we might be able to understand why 3D VR can replace painkillers in some medical applications.

Facebook patents recommendations from contact lists

The USPTO awarded Facebook US Patent 9,338,250, titled "Associating received contact information with user profiles stored by a social networking system" (inventors: Michael Hudack, Christopher Turitzin; Edward Baker; Hao Xu). The patent covers the now standard feature in many social networks, both consumer and professional, where the system finds potential connections in your imported contact list and recommends adding a person who is currently not in your network.

From an innovation methodology perspective, the invention solves a typical problem that arises when users need to be migrated from an old technology space into a new one. In the System model, an effective solution improves scalability, by dramatically reducing costs of adding Sources and Tools during the synthesis phase.

tags: facebook, innovation, invention, patent, social, networking, synthesis

Stanford CSP Scalable Innovation (BUS 134) Session 3, Quiz 1

Autonomous vehicles (formerly known as self-driving cars) can drive safely at fast speeds and maintain short distances between cars, reducing road congestion. Furthermore, electric autonomous vehicles can accelerate and maintain high speeds without dramatically increasing pollution.

On the other hand, human drivers are required to drive under the speed limit and maintain a certain, relatively large, distance between cars, e.g. the Two-Second Rule. Arguably, introduction of modern breaking technologies doesn't reduce the rate of accidents significantly.*

As a result, large-scale deployment of autonomous vehicles creates a situation that involves multiple trade-offs.

Questions:

1. List trade-offs relevant to the situation (use divergent thinking). Select one (use convergent thinking) that you anticipate to become the most important in the future. What selection criteria did you apply?
2. Propose solutions that can break the trade-off: realistic, futuristic, fantastic, etc.
3. (Bonus 1 - optional). What technology and business opportunities you can create by breaking the trade-off?
4. (Bonus 2 - optional) Using analogical thinking, what solutions from the history of the automobile can you re-use to solve the current situation?

* See, for example, Foolproof: How Safety Can Be Dangerous and How Danger Makes Us Safe, by Greg Ip, 2015.

Lunch Talk: In 2003 Elon Musk gave a talk at Stanford about PayPal and Space X

From the Youtube blurb:

"Elon Musk, co-founder, CEO, and chairman of PayPal, shares his background: He was accepted into Stanford but deferred his admission to start an internet company in 1995. His company was zip2 which helped the media industry convert their content to electronic medium. Then, he sold the company for over $300 million and never came back to Stanford."

tags: youtube, lunchtalk, innovation, media, space