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

In a recent article, MIT Technology Review described exciting new developments in AI-enabled robotics:

This robot, controlled by software from a San Francisco–based company called Osaro, is smarter than any you’ve seen before. The software has taught it to pick and place chicken in about five seconds. Within the year, Osaro expects its robots to find work in a Japanese food factory.

Industrial robots have been largely untouched by the latest advances in artificial intelligence. Over the last five or so years, AI software has become adept at identifying images, winning board games, and responding to a person’s voice with virtually no human intervention. It can even teach itself new abilities, given enough time to practice. All this while AI’s hardware cousins, robots, struggle to open a door or pick up an apple.

That is about to change. The AI software that controls Osaro’s robot lets it identify the objects in front of it, study how they behave when poked, pushed, and grasped, and then decide how to handle them. Like other AI algorithms, it learns from experience. Using an off-the-shelf camera combined with machine-learning software on a powerful computer nearby, it figures out how to grasp things effectively. With enough trial and error, the arm can learn how to grasp just about anything it might come across.

Moreover, investors show strong interest in the field as well. For example, this week's Bloomberg article noted creation of new ETFs dedicated to Robotics and Artificial Intelligence.

Quiz:
1. In your opinion, does the field of new AI-enabled robots 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 major disadvantages of using the technology relative to more traditional robots?
1c. How many years would it take for AI-enabled robots to become mainstream?

2. Where would you place the technology on the S-curve and Adopter Distribution chart as of today? Explain briefly.

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.

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.

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 152 - Session 5, Quiz 1

Background: A major shift in business and technology strategy (aka pivot) seems to be inevitable during the life time of both startups and large companies. The change requires the team to make critical decisions under conditions of uncertainty.



Please listen to the podcast above and answer the following Questions:

1. Why LoudCloud was too early to the market? What were the key decisions for LoudCloud/Opsware in executing a pivot?

2. Did Lytro develop a new technology? Please describe briefly its pivot in terms of the 4Q diagram covered during our Session 4 (Feb 13, 2017). Using the same terms, describe the team's original mistake.

3. (Optional). Imagine that you are the CEO of Twitter. Your user base and revenues are not growing fast enough to compete with Facebook and Snapchat. You have $1B and 2 years to execute a pivot. Describe your key decisions and reasoning behind them.

tags: bus152, quiz, 4q diagram,

Stanford CSP, BUS 152 - Innovation Timing. Session 4, Quiz 1

Background:

Recently, a number of technology companies introduced Augmented Reality headsets that enable users to overlay images from the real world with information generated by a computer, including text, video, graphics, etc. Microsoft HoloLens  is one of the most advanced projects in the field, backed by a major industry player. For example, in a 2016 TED Talk, Alex Kipman demonstrated a head-mounted 3D hologram computer that lets users interact with "magical objects" directly, which eliminates, among other things, the need for displays, keyboards, joysticks, and other typical computer accessories.

Please read the wikipedia article referenced above, watch the TED video, and answer the following questions:

1. Is HoloLens a new technology? Explain.

2. Imagine that it is year 2040. Do you see HoloLens-like devices dominating specific fields of human-computer interaction, e.g.

a) Education (certainly, highly likely, maybe, absolutely not). Explain.
b) Gaming (certainly, highly likely, maybe, absolutely not). Explain.
c) Construction and Industrial Services (certainly, highly likely, maybe, absolutely not). Explain.
d) Healthcare (certainly, highly likely, maybe, absolutely not). Explain.

3. (Optional) In your opinion, what are the top three bottlenecks that may prevent Augmented Reality devices, like HoloLens, from becoming widely popular among consumers during the next 3-5 years? Explain.

Stanford CSP, BUS 152 - Innovation Timing. Session 3, Quiz 1

Background: Over the last decade, AI-based technologies succeeded in solving various problems that before were considered impossible to solve using computational methods. In one recent example, Stanford researchers "have trained an algorithm to diagnose skin cancer." In another example, AI bot easily outplayed humans in poker.

The significance of the latter development is that the algorithm successfully handled a problem with imperfect information:

Poker requires reasoning and intelligence that has proven difficult for machines to imitate. It is fundamentally different from checkers, chess, or Go, because an opponent’s hand remains hidden from view during play. In games of “imperfect information,” it is enormously complicated to figure out the ideal strategy given every possible approach your opponent may be taking.

Given that innovation fundamentally involves decision-making with imperfect information, we may want to consider how AI will impact broader innovation processes in our society.

Questions:
1. Assume that AI decision-making services are widely available. In your opinion, which segments of the society will start using such services first: consumer or enterprise? Explain your reasoning and give approximate calendar time estimates for each segment.

2. Consider Kahneman's System 1 vs System 2 approach to human decision-making (e.g. as discussed during our Session 2). Will a wide adoption of AI services improve or worsen people's ability to use "System 2 thinking"? Explain.

3. In your opinion, will AI-based decision-making services affect the overall timing of innovation diffusion in social systems (see Session 1 lecture notes), e.g. by making S-curves more gradual, more steep, or leave them unchanged? Explain.

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 1.

Background:

Timing is critical for innovation success. Sometimes, companies introduce new products and services when it’s too late. For example, neither Google+ nor Microsoft smartphone succeeded, despite their respective companies putting major resources behind them, both in money and development efforts.

On the other extreme, some innovations fail because they seem to appear too early. Social networks Friendster and Livejournal started gaining traction in the early 2000s, but never got to the scale of Facebook. Similarly, WebTV started in 1995, with the intent to provide users with a broad range of content over the Internet. In almost two decades that followed, the company burned through hundreds of millions of dollars, went through a major acquisition, but failed in the very same marketplace where NetFlix and other video streaming services managed to succeed a few years later.

Finally, certain products and services had perfect timing. For example, Gmail and Youtube spread like a California wildfire. The Apple iPhone succeeded where Apple Newton failed.

In preparation for the course, please answer the following questions:

1. List 2-3 novel products or services in each of the timing categories:
a) too late;
b) too early;
c) just perfect.

2. (Optional). Pick one example from the list and explain your reasoning with regard to innovation timing. Mention at least 3 factors that played a role in the success or failure of the innovation.