Category Archives: Innovation

Ray Kurzweil has mostly wrong predictions

As often, Marc Voinchet had a remarkable broadcast this morning on France Culture. First a great guest, Cécile Lafontaine for her book The body market, the commodification of human life in the era of bioeconomy (in French only – my translation of the title) which goes beyond the adressed topic by asking questions about the tensions between the individual and society. It provides excellent answers to the debates opened by Thiel. But here I stop and let you discover the interview if the subject interests you.

FranceCulture-Matins

In addtion Xavier de la Porte wrote an excellent chronicle that I copied directly from the website of France Culture on the French part of my blog (in order to be able to translate it here): The brain is not one million lines of code.

When we look at what the digital world has to say about the body and life, there is a high likeliness to find quickly intimidating predictions: “Soon we will all be cyborgs” and “In 2045, we will have completely merged with the machines.” A specialist in this kind of statements is a guy named Ray Kurzweil – which I mentioned here already. Pretty awesome inventor, wise businessman, Kurweil became in the last twenty years the promoter of a movement called transhumanism – which considers that humankind will soon merge with machines, thus giving rise to post-humanity – ideas that Kurzweil sold worldwide with books and conferences, ideas that he also sells to super-powerful companies: Google has hired him to run a program on teaching language to machines. The problem with Kurzweil – and many transhumanists – it is their strength of conviction that passes through a scientific-techno-philosophical discourse which we feel is not right, but without knowing exactly where. But recently , I came across evidence that Kurzweil says non-sense. I enjoyed my discovery and I want to share this joy with you.

It has to do with an important aspect of transhumanism: the belief always repeated that very soon we can duplicate our brains into computers. Kurzweil believes that this will be possible in 2020, and moreover, he has stored the brain of his deceased father in that perspective. And in order to support his thesis, here is the type of speech that Kurzweil gives: “The code of the brain is in the genome. The human genome is 3 billion base pairs, six billion bits, which is about 800 million bits after compression. After eliminating redundancies […] this information can be compressed into approximately 50 million bits. But the brain is about half of that, about 25 million bits, or one million lines of code.” And here, in a ruthless and intimidating demonstration, Kurzweil shows us a million lines of code suffice to duplicate the function of the human. (I say “sufficient” because it is just one million lines of code; for comparison, Microsoft Office 2013 is 45 million lines of code).

Except that for once, someone came forward to explain that Kurzweil told non-sense. This person is called Paul Zachary Myers. He is a recognized biologist at the University of Minnesota, specializing in developmental genetics and writes a blog called Pharyngula. And it is on his blog that Myers explains very calmly why what Kurzweil says is wrong. Here is his demonstration. The premise of the reasoning of Kurzweil is “The code of the brain is in the genome.” Totally wrong, says the researcher. The code of the brain is not encoded in the genome. What is in the genome is a collection of molecular tools which is the regulating portion of the genome, which makes cells sensitive to interactions with a complex environment. During its development, the brain unfolds through interactions between cells, interactions which we understand today a small part only. The final result is a brain that is much more complex than the sum of nucleotides that encode a few thousand proteins. One can not deduce a brain from the protein sequences of its genome. How will these sequences express is dependent on the environment and the history of hundreds of billions of cells, interdependent on each other. We have no way to calculate in principle all possible interactions and functions of a single protein with tens of thousands of others who are in the cell, which is the essential first step in the execution of the unlikely algorithm of Kurzweil. In support of his argument, the researcher takes a few examples of some proteins and shows how the interactions are numerous, complex and mostly still unknown.

What is very interesting is that Myers states that he is not hostile to the idea that the brain is a kind of computer, and we will be able to artificially reproduce one day its functions. But he says that he does not need to say stupide nonsense, as does Kurzweil and build hisreasoning on false premises. And here is for you, Kurzweil. If only more researchers could take more time to bring their expertise to question the transhumanist speech, it may save us to hear many absurdities and attend another commodification of human life, which is about seeling biotechnology dream.

When Peter Thiel talks about Start-ups – Final Thoughts: Human After All

As you noticed if you read my previous posts, I’ve been quite impressed by Peter Thiel’s notes about start-ups. I’ve written 7 long parts. I had been similarly impressed by Mariana Mazzucato’s The Entrepreneurial State even if with only 5 posts!

Thiel-Mazzucato

I said it already, I would have loved to attend their debate in a few days at the conference Human After All, Toronto 2014. But apparently they do not participate to the same roundtable anymore… (After reading what follows, I see that Taleb would have been a great addition).

– He will discuss “The Economics of Radical Uncertainty.”
How do human beings truly react when confronted with conditions of genuine “unknown unknowns”? According to Frank Knight, “Uncertainty must be taken in a sense radically distinct from the familiar notion of risk, from which it has never been properly separated…The essential fact is that ‘risk’ means in some cases a quantity susceptible of measurement, while at other times it is something distinctly not of this character; and there are far – reaching and crucial differences in the bearings of the phenomena depending on which of the two is really present and operating… It will appear that a measurable uncertainty, or ‘risk’ proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all.” The economics literature from Knight onward is very good at laying out the propensity of markets to greatly overshoot and undershoot the fundamentals. However, economics does not adequately address the implications of “Knightean” uncertainty, because the discipline finds it hard to model this phenomenon. To get a full measure of this, one has to enter into the realm of psychology and neuroscience. That’s where the definition lies. Radical uncertainty, like so much else, is too important to be left to the realm of economics alone.

– She will be part of “Innovation: Do Private Returns Produce the Social Returns We Need?”
The machines of the first age replaced and multiplied the physical labour of humans and animals. The machines of the second age will replace and multiply our intelligence. The driving force behind this revolution will, argue the “techno-positivists,” exponentially increase the power (or exponentially reduce the cost) of computing. The celebrated example is Moore’s Law, named after Gordon Moore, a founder of Intel. For half a century, the number of transistors on a semiconductor chip has doubled at least every two years. But the information age has coincided with – and must, to some extent, have caused – adverse economic trends: stagnation of median real incomes; rising inequality of labour income and of the distribution of income between labour and capital; and growing long – term unemployment. Are the great gains in
wealth and material prosperity created by our entrepreneurs in and of themselves sufficient to produce desired social returns demanded in today’s world?

Start-ups are a great area to study the tension between individuals and society. A kind of chicken and egg situation… Indeed they might explain the growing gap between the USA and Europe in many dimensions. Mazzucato would be on the social side, Thiel closer to the individual. But do not see any provocative statement here. The thoughts of Thiel and Mazzucato are profound. I agree with most of what they say, disagree with smaller pieces, though most people could think their thinking can not be reconciled. I really think that combining their point of views is an interesting approach to what innovtaion really is…

PS (May 8, 2014): I just found that video of Thiel at SXSW.

When Peter Thiel talks about Start-ups – part 7: luck & uncertainty

This is my last post about Thiel’s class notes at Stanford and it is about Class 13 – Luck. Now I need to wait for his book to be published…

zerotoone

I love accidents. I mentioned it in a post which has nothing to do with start-ups (related to Street Art). The accident here is funny: I totally forgot to copy-paste Thiel’s class 13 and it is only when I began to read class 14 that I noticed my mistake. Now let me quote Thiel: “Note that this is class 13. We are not going to be like the people who build buildings without a 13th floor and superstitiously jump from class 12 to 14. Luck isn’t something to circumvent or be afraid of. So we have class 13. We’ll dominate luck.” Strange, right? I had to call this final part, part 7…

So what does Thiel say about luck? Well it is a debated topic, as I experienced in my activity at EPFL. Thiel feels the same. He begins with: “The biggest philosophical question underlying startups is how much luck is involved when they succeed. As important as the luck vs. skill question is, however, it’s very hard to get a good handle on. Statistical tools are meaningless if you have a sample size of one. It would be great if you could run experiments. Start Facebook 1,000 times under identical conditions. If it works 1,000 out of 1,000 times, you’d conclude it was skill. If it worked just 1 time, you’d conclude it was just luck. But obviously these experiments are impossible.” adding the famous Thomas Jefferson’s line: “I’m a great believer in luck, and I find the harder I work the more I have of it.”

Thiel is not so much interested in luck as in determinism vs. indeterminism. “If you believe that the future is fundamentally indeterminate, you would stress diversification. […]. If the future is determinate, it makes much more sense to have firm convictions. […] Overlay this diversification/conviction dynamic over the optimism/pessimism question and you get further refinement. Whether you look forward to the future or are afraid of it ends up making a big difference. And here is his vision of the world:

Thiel-World1

With an even more surprising and quite convincing:

Thiel-World2

“But the indeterminate future is somehow one in which probability and statistics are the dominant modality for making sense of the world. Bell curves and random walks define what the future is going to look like. The standard pedagogical argument is that high schools should get rid of calculus and replace it with statistics, which is really important and actually useful. There has been a powerful shift toward the idea that statistical ways of thinking are going to drive the future.”

But here I’d love to ask Peter Thiel what he makes of Black Swans if he believes in 0 to 1 more than in 1 to n. 1 to n belongs to statistics, not 0 to 1… (read again my part 1 if this is cryptic)

Thiel-World-SFBA

Thiel likes crazy ideas, like Reber’s project for the Bay Area in the 1940s above. He also still believes in finance despite its excesses: “In a future of definite optimism, you get underwater cities and cities in space. In a world of indefinite optimism, you get finance. The contrast couldn’t be starker. The big idea in finance is that the stock market is fundamentally random. It’s all Brownian motion. All you can know is that you can’t know anything. It’s all a matter of diversification. There are clever ways to combine various investments to get higher returns and lower risk, but you can only push out the efficient frontier a bit. You can’t know anything substantive about any specific business. But it’s still optimistic; finance doesn’t work if you’re pessimistic. You have to assume you’re going to make money. […] Indeterminacy has reoriented people’s ideas about investing. Whereas before investors actually had ideas, today they focus on managing risk. Venture capital has fallen victim to this too. Instead of being about well-formed ideas about future, the big question today is how can you get access to good deals. In theory at least, VC should have very little in common with such a statistical approach to the future.“

And he might agree with Mariana Mazzucato during his debate to come with her (at Human After All, Toronto 2014 – program in pdf) : “The size of government hasn’t changed all that much in the last 40-50 years. But what the government actually does has changed radically. In the past, the government would get behind specific ideas and execute them. Think the space program. Today, the government doesn’t do as many specific things. Mainly it just shifts money around from some people to other people. What do you do about poverty? Well, we don’t know. So let’s just give people money, hope it helps, and let them figure it out.”

Darwinism and design.

And all of a sudden, while reading this class 13, Thiel again surprises me! Obviously, the indeterminate optimism can be quite easily linked to Darwin’s theory of evolution. Accidents happen, but there is general positive evolution. And “Applied to start-ups, obsession with indeterminacy leads to the following phenomena:
• Darwinistic A/B testing
• Iterative processes
• Machine learning
• No thinking about the future
• Short time horizons”

Typical Blank’s messages! But Thiel envisages another possibility: “Apple is absolute antithesis of finance. It does deliberate design on every level. There is the obvious product design piece. The corporate strategy is well defined. There are definite, multi-year plans. Things are methodically rolled out.” (I do not think Thiel talks here about intelligent design which is opposed to Darwinian theory, but the coincidence is a little puzzling!

“On the heels of Apple has come the theme of well-designed products being really important. Airbnb, Pinterest, Dropbox, and Path all have a very anti-statistical feel. […] That link—great design—seems to work better and faster than Darwinistic A/B testing or iteratively searching through an incredibly large search space. The return of design is a large part of the countercurrent going against the dominating ethos of indeterminacy. Related to this is the observation that companies with really good plans typically do not sell. If your startup gets traction, people make offers to buy it. In an indefinite world, you will take the money and sell, because money is what you want. […] But when companies have definite plans, those plans tend to anchor decisions not to sell.[..] In an indefinite world, investors will value secret plans at zero. But in a determinate world, robustness of the secret plan is one of the most important metrics […] It’s important to note that you can always form a definite plan even in the most indefinite of worlds. […] We’re falling downwards towards pessimism. Can we shift instead to definite optimism?”

This is the end of my notes on Thiel’s great vision about start-ups.

When Peter Thiel talks about Start-ups – part 6: founder uniqueness, technology singularity

Thiel’s concludes his Class Notes Essays (CS183 —Stanford, Spring 2012) with philosophical considerations about the uniqueness of founders (class 18) and the singularity of technology (class 19). Founders are a topic I regularly covered, for example with European Founders at Work or Founders at Work.

Again Thiel presents unusual ideas about founders. He sees them as a combination of extreme outsiders and extreme insiders.
Thiel-extreme-in-out
which he reinforces with this virtuous/vicious circle:
Thiel-extreme-in-out-circle

If this is not clear, two examples may help:
– “All [these] questions apply to Gates. Was it nature or nurture? He was a Harvard insider but a dropout outsider. He wore big glasses. Did he become a nerd unwillingly? Did he prosper by accentuating his nerdiness? It’s hard to tell.”
– “And then there’s the Steve Jobs version. […] He had all the classic extreme outsider and extreme insider traits. He dropped out of college. He was eccentric and had all these crazy diets. He started out phreaking phones with Steve Wozniak. He took LSD.”

Thiel is convincing when he explains that a start-up is not a democracy. Founders are Kings, and Thiel may have followed René Girard at Stanford since he then develops a theory of scapegoats. The god may become a victim.
Thiel-monarchy

Thiel is a little short about the dual-founder situation: “The dual founder thing is worth mentioning. Co-founders seem to get in a lot less trouble than more unbalanced single founders. Think Hewlett and Packard, Moore and Noyce, and Page and Brin. There are all sorts of theoretical benefits to having multiple founders such as more brainstorming power, collaboration, etc. But the really decisive difference between one founder and more is that with multiple founders, it’s much harder to isolate a scapegoat. Is it Larry Page? Or is it Sergey Brin? It is very hard for a mob-like board to unite against multiple people—and remember, the scapegoat must be singular. The more singular and isolated the founder, the more dangerous the scapegoating phenomenon. For the skeptic who is inclined to spot fiction masquerading as truth, this raises some interesting questions. Are Page and Brin, for instance, really as equal as advertised? Or was it a strategy for safety? We’ll leave those questions unanswered and hardly asked.”

Thiel-dual-founders

Thiel’s vision (as well as the visions of his guests – I mixed them here) of technology was mentioned in my previous post. Again quite fascinating. “People do tend have some view of the future. They usually project relative stagnation. People tend to believe that, not only will most things not change, but what will change won’t change very quickly.” But “there’s a compelling case that we’ll very likely see extraordinary or accelerated progress in the decades ahead.”

One guest: “My take is that innovation comes from two places: top-down and bottom-up. There’s a huge DIY community. These hobbyists are working in labs they set up in their kitchens and basements. On the other end of the spectrum you have DARPA spending tons of money. Scientists are talking to each other from different countries, collaborating. All this interconnectedness matters. All these interactions in the aggregate will bring the change.

Another guest: “I disagree. There are a very few visionary people who can make a real difference at the formative early stage. This is why mainstream opinion formers are absolutely pivotal. Perhaps no other subset of people could do more to further radical technology. By overpowering public reluctance and influencing the discourse, these people can enable everyone else to build the technology. If we change public thinking, the big benefactors can drive the gears.”

The third guest: “I do not think that progress will come from the top-down or from the bottom-up, really. Individual benefactors who focus on one thing, like Paul Allen, are certainly doing good. But they’re not really pushing on future; they’re more pushing on individual thread in homes that it will make the future come faster. The sense is that these people are not really coordinating with each other. Historically, the big top-down approaches haven’t worked. And the bottom-up approach doesn’t usually work either. It’s the middle that makes change—tribes like the Quakers, the Founding Fathers, or the Royal Society. These effective groups were dozens or small hundreds in size. It’s almost never lone geniuses working solo. And it’s almost never defense departments or big institutions. You need dependency and trust. Those traits cannot exist in one person or amongst thousands.”

Peter Thiel: “That’s three different opinions on who makes the future: a top-down bottom-up combo, social opinion molders, and tribes.”

To be honest, I was more convinced with his analysis of founders than of technologies. His conclusion is worth reading as inspiration: “This course has largely been about going from 0 to 1. We’ve talked a lot about how to create new technology, and how radically better technology may build toward singularity. But we can apply the 0 to 1 framework more broadly than that. There is something importantly singular about each new thing in the world. There is a mini singularity whenever you start a company or make a key life decision. In a very real sense, the life of every person is a singularity. The obvious question is what you should do with your singularity. The obvious answer, unfortunately, has been to follow the well-trodden path. You are constantly encouraged to play it safe and be conventional. The future, we are told, is just probabilities and statistics. You are a statistic. But the obvious answer is wrong. That is selling yourself short. Statistical processes, the law of large numbers, and globalization—these things are timeless, probabilistic, and maybe random. But, like technology, your life is a story of one-time events. By their nature, singular events are hard to teach or generalize about. But the big secret is that there are many secrets left to uncover. There are still many large white spaces on the map of human knowledge. You can go discover them. So do it. Get out there and fill in the blank spaces. Every single moment is a possibility to go to these new places and explore them. There is perhaps no specific time that is necessarily right to start your company or start your life. But some times and some moments seem more auspicious than others. Now is such a moment. If we don’t take charge and usher in the future—if you don’t take charge of your life—there is the sense that no one else will. So go find a frontier and go for it. Choose to do something important and different. Don’t be deterred by notions of luck, impossibility, or futility. Use your power to shape your own life and go and do new things.”

Reading these last lines, I remembered the conclusion of my book: “And I suddenly remembered an essay by Wilhelm Reich, the great psychoanalyst, which he wrote in 1945: “Listen, Little Man”. A small essay by the number of pages, a big one in the impact it creates. “I want to tell you something, Little Man; you lost the meaning of what is best inside yourself. You strangled it. You kill it wherever you find it inside others, inside your children, inside your wife, inside your husband, inside your father and inside your mother. You are little and you want to remain little.” The Little Man, it’s you, it’s me. The Little Man is afraid, he only dreams of normality; it is inside all of us. We hide under the umbrella of authority and do not see our freedom anymore. Nothing comes without effort, without risk, without failure sometimes. “You look for happiness, but you prefer security, even at the cost of your spinal cord, even at the cost of your life”.

When Peter Thiel talks about Start-ups – part 5: a vision of the future of technology

I am still not sure how Thiel’s class notes on start-ups will finish, but they are more and more fascinating, class after class. At least his vision of this world is.

Class 14 is about cleantech and energy. “Alternative energy and cleantech have attracted an enormous amount of investment capital and attention over the last decade. Almost nothing has worked as well as people expected. The cleantech experience can thus be quite instructive. […] To think about the future of energy, we can use the [another] matrix. The quadrants shake out like this:
Determinate, optimistic: one specific type of energy is best, and needs to be developed
Determinate, pessimistic: no technology or energy source is considerably better. You have what you have. So ration and conserve it.
Indeterminate, optimistic: there are better and cheaper energy sources. We just don’t know what they are. So do a whole portfolio of things.
Indeterminate, pessimistic: we don’t know what the right energy sources are, but they’re likely going to be worse and expensive. Take a portfolio approach.”

Both for energy and transportation, Thiel’s fills his quadrants with interesting examples:
Thiel-World3

and he adds: “Petroleum has dominated transportation. Coal has dominated in power generation. […] Typically a single source dominates at any given time. There is a logical reason for this. It doesn’t make sense that the universe would be ordered such that many different kinds of energy sources are almost exactly equal. Solar is very different from wind, which is very different from nuclear. It would be extremely odd if pricing and effectiveness across all these varied sources turned out to be virtually identical. So there’s a decent ex ante reason why we should expect to see one dominant source. This can be framed as a power law function. Energy sources are probably not normally distributed in cost or effectiveness. There is probably one that is dramatically better than all others.”

But the analysis explaining the cleantech bubble were far from clear. “One problem was that people were ambiguous on what was scarce or problematic. Was there resource scarcity? Or were the main problems environmental?” […] “To have a successful startup, you must have good answers—or at least a good plan for getting those answers.” Answers to many issues such as
– the market
– the secrets
– the team and its culture
– the funding
and unfortunately many mistakes were made.

Regarding the market, there was the issue of both explaining how to become a leader of one segment (PV, wind,…) and why a segment was better. Regarding the secret: “If you want to start a company, you should have some important secret. But in practice, most wind, solar, and cleantech ventures relied on incremental improvements.” Even worse, “most cleantech companies in the last decade have had shockingly non-technical teams and cultures. Culture defaulted toward zero-sum competition. Savvy observers would have seen the trouble coming when cleantech people started wearing suits and ties. Tech people and computer people wear t-shirts and jeans. Cleantech people, by contrast, looked like salesmen. And indeed they were. This is not a trivial point. If you’re dealing in something that’s incremental and of questionable durability, you actually have to be a really good salesman to convince people that it’s dramatically better.” Finally “a good, broad rule of thumb is to never invest in companies who are looking for less than $1 million or more than $1 billion. If companies can do everything they want for less than a million dollars, things may be a little too easy. There may be nothing that is very hard to build, and it’s just a timing game. On the other extreme, if a company needs more than a billion dollars to be successful, it has to become so big that the story starts to become implausible.”

If Thiel were to bet on soemthing, it would apparently be Thorium as a nuclear fuel.

Class 15 is about other future bets.

Thiel-World4a
Thiel-World4b

Thiel is a strong believer in contrarian (and sometimes huge) bets. He is interested in or at least puzzled by transportation, robotics, weather and energy storage. And his way of choosing is to look at what did not work (yet) in the past: “Various VC firms in Silicon Valley warned expressed concern about [investing in unique technologies]. They warned us that investing in SpaceX was risky and maybe even crazy. And this wasn’t even at the very early stage. […] (Danielle Fong:) People like to act like they like being disruptive and taking risks. But usually it’s just an act. They don’t mean it. Or if they do, they don’t necessarily have the clout within the partnership to make it happen. (Peter Thiel:) It is very hard hard for investors to invest in things that are unique. The psychological struggle is hard to overstate. People gravitate to the modern portfolio approach. The narrative that people tell is that their portfolio will be a portfolio of different things. But that seems odd. Things that are truly different are hard to evaluate. […] The upside to doing something that you’re unfamiliar with, like rockets, is that it’s likely that no one else is familiar with it, either. The competitive bar is lowered. You can focus on learning and substantive things over process, which is perhaps better than competing against experts.”

Class 16 is about maybe the highest of all bets: life and death.

I have not so far mentioned the sentence which comes at the top of each series of class notes: “Your mind is software. Program it. Your body is a shell. Change it. Death is a disease. Cure it. Extinction is approaching. Fight it.”

The problem.

“Like death itself, modern drug discovery is probably too much a matter of luck. Scientists start with something like 10,000 different compounds. After an extensive screening process, those 10,000 are reduced to maybe 5 that might make it to Phase 3 testing. Maybe 1 makes it through testing and is approved by the FDA. It is an extremely long and fairly random process. This is why starting a biotech company is usually a brutal undertaking. Most last 10 to 15 years. There’s little to no control along the way. What looks promising may not work. There’s no iteration or sense of progress. There is just a binary outcome at end of a largely stochastic process. You can work hard for 10 years and still not know if you’ve just wasted your time.

To be fair, we must acknowledge that all the luck-driven, stats-driven processes that have dominated people’s thinking have worked pretty well over the last few decades. But that doesn’t necessarily mean that indeterminacy is sound practice. Its costs may be rising quickly. Perhaps we’ve found everything that is easy to find. If so, it will be hard to improve armed with nothing but further random processes. This is reflected in escalating development costs. It cost $100 million to develop a new drug in 1975. Today it costs $1.3 billion. Probably all life sciences investment funds have lost money. Biotech investment has been roughly as bad a cleantech.”

The perspectives.

“Drug discovery is fundamentally a search problem. The search space is extremely big. There are lots of possible compounds. An important question is thus whether we can use computer technology to reduce scope of luck. Can Computer Science make biotech more determinative?”

“These are big secrets that play out over long time horizons, not web apps that have a 6-week window to take over the world.”

“The sequencing of the genome is like the first packets being sent over ARPANET. It’s a proof of concept. This technology is happening, but it isn’t yet compelling. So there is a huge market if one can make something compelling enough for people to actually go and get a genome sequenced. It’s like e-mail or word processing. Initially these things were uncomfortable. But when they become demonstrably useful, people leave their comfort zones and adopt them.”

“Biotech got quite a burst in late 70s early 80s, with new recombinant DNA and molecular biology techniques. Genentech led the way from the late 70s to the early 80s. Nine of the 10 biggest American biotech companies were founded during this really short time. Their technology came out some 7-8 years later. And that was the window; not very many integrated biotech companies have emerged since then. There was a certain amount of stuff to find. People found it. And before Genentech, the paradigm was pharma, not biotech. That window (becoming an integrated pharmaceutical company) had been closed for about 30 years before Genentech. So the bet is that while the traditional biotech window may be closed, the comp bio window is just opening.”

“There’s really no rush to spill the secret plans. This space is very much unlike fast-moving consumer Internet startups. Here, if you have something unique, you should nurse it.”

“Slow iteration is not law of nature. Pharma and biotech usually move very slowly, but both have moved pretty fast at times. From 1920-1923 Insulin moved at the speed of software. Today, platforms like Heroku have greatly reduced iteration times. The question is whether we can do that for biotech. Nowhere is it written in stone that you can’t go from conception to market in 18 months. That depends very much on what you’re doing. Genentech was founded the same year as Apple was, in 1976. Building a platform and building infrastructure take time. There can be lots of overhead. Ancillary things can take longer than a single product lifecycle to accumulate. [… the] VC is broken with respect biotech. Biotech VCs have all lost money. They usually have time horizons that are far too short. VCs that say they want biotech tend to really want products brought to market extremely quickly. “Integrated drug platform” is an ominous phrase for VCs. More biotech VCs are focused on globalization than on real technical innovation. VCs typically found a company around a single compound and then pour a bunch of money into it to push it through the capital-intensive trial process. Most VCs not interested in multi-compound companies doing serious pre-clinical research.”

And as a conclusion of class 16, “Startups are always hard at the start. There are futons and ironing boards in the office. You have to rush to clean up for meetings. But maybe the hardest thing is just to get your foundation right and make sure you plan to build something valuable. You don’t have to do a science fair project at the start. You just have to do your analytical homework and make sure what you’re doing is valid. You have to give yourself the best chance of success as things unfold in the future.”

Class 17 is about the brain, artificial intelligence, maybe the last frontier in technology, certainly going further than the previous topics addressed here.

thiel-world5

Not much more to add except maybe the short description of the approach by 3 start-ups:
Vicarious is trying to build AI by develop algorithms that use the underlying principles of the human brain. They believe that higher-level concepts are derived from grounded experiences in the world, and thus creating AI requires first solving a human sensory modality.
Prior Knowledge (acquired by Salesforce since Thiel’s class) is taking a different approach to building AI. Their goal is less to emulate brain function and more to try to come up with different ways to process large amounts of data. They apply a variety of Bayesian probabilistic techniques to identifying patterns and ascertaining causation in large data sets. In a sense, it’s the opposite of simulating human brains.
– The big insight at Palantir (…) isn’t regression analysis, where you look at what was done in the past to try to predict what’s going to be next. A better approach is more game theoretic. Palantir’s framework is not fundamentally about AI, but rather about intelligence augmentation.

And one more comment: “For the most part, academics aren’t (working on strong AI or crazy things) because their incentive structure is so weird. They have perverse incentive to make only marginally better things. And most private companies aren’t working on it because they’re trying to make money now.(…) Bold claims also require extraordinary proof. If you’re pitching a time machine, you’d need to be able to show incremental progress before anyone would believe you. Maybe your investor demo is sending a shoe back in time. That’d be great. You can show that prototype, and explain to investors what will be required to make the machine work on more valuable problems. It’s worth noting that, if you’re pitching a revolutionary technology as opposed to an incremental one, it is much better to find VCs who can think through the tech themselves. When Trilogy was trying to raise their first round, the VCs had professors evaluate their approach to the configurator problem. Trilogy’s strategy was too different from the status quo, and the professors told the VCs that it would never work. That was an expensive mistake for those VCs. When there’s contrarian knowledge involved, you want investors who have the ability to think through these things on their own.”

End of part 5!

When Peter Thiel & Friends talk about Start-ups – part 3: company culture, founders, team, investors

Part 3 of my series of comments about Thiel’s class notes at Stanford mainly cover his Class 5-8. But first I should add that Thiel invited a “honor class” of innovators during his 19 classes. Quite fascinating!

Thiel-Friends-CS1st row: Stephen Cohen, co-founder and Executive VP of Palantir Technologies,
Max Levchin, co-founder PayPal and Slide,
Roelof Botha, partner at Sequoia Capital and former CFO of PayPal,
2nd row: Paul Graham, partner and co-founder of Y Combinator,
Bruce Gibney, partner at Founders Fund,
Marc Andreessen, general partner Andreessen Horowitz,
3rd row: Reid Hoffman, co-founder of LinkedIn,
Danielle Fong, Co-founder and Chief Scientist of LightSail Energy,
Jon Hollander, Business Development at RoboteX,
4th row: Greg Smirin, COO of The Climate Corporation,
Scott Nolan, Principal at Founders Fund and former aerospace engineer at SpaceX,
(Elon Musk was going to come, but he was busy launching rockets),
5th row: Brian Slingerland. Co-Founder, President & COO at Stem CentRx,
Balaji S. Srinivasan, CTO of Counsyl,
Brian Frezza, Co-founder, Emerald Therapeutics,
6th row: D. Scott Brown, co-founder of Vicarious,
Eric Jonas, CEO of Prior Knowledge,
Bob McGrew, Director of Eng, Palantir,
7th row: Sonia Arrison, Associate Founder of Singularity University,
Michael Vassar, the Singularity Institute for the study of Artificial Intelligence (SIAI),
Aubrey de Grey, Chief Science Officer at the SENS Foundation.

Thiel covered how to build a company from the ideas and vision of founders, through hiring and sometimes funding from investors. But he began with a critical though fuzzy concept, the company culture: “A robust company culture is one in which people have something in common that distinguishes them quite sharply from rest of the world.”

He mentions also some important dimensions of the culture:
– Consultant-nihilism or Cultish Dogmatism: “You want to be somewhere in the middle of that spectrum. To the extent you gravitate towards an extreme, you probably want to be closer to being a cult than being an army of consultants.” which could be why Thiel said earlier,
pre-money valuation = ($1M*n_engineers) – ($500k*n_MBAs).
– To Fight or Not To Fight (i.e. Nerds or Athletes or again Zero-sum and Non zero-sum). “So you have to strike the right balance between nerds and athletes. Neither extreme is optimal. Consider a 2 x 2 matrix. On the y-axis you have zero-sum people and non zero-sum people. On the x-axis you have warring, competitive environments and then you have peaceful, monopoly/capitalist environments. The optimal spot on the matrix is monopoly capitalism with some tailored combination of zero-sum and non zero-sum oriented people. You want to pick an environment where you don’t have to fight. But you should bring along some good fighters to protect your non zero-sum people and mission, just in case.”
I was just told this is crytic… I agree… another reason to read Thiel directly!

Foundings are obviously temporal. But how long they last can be a hard question. The typical narrative contemplates a founding, first hires, and a first capital raise. But there’s an argument that the founding lasts a lot longer than that. The idea of going from 0 to 1—the idea of technology—parallels founding moments. The 1 to n of globalization, by contrast, parallels post-founding execution. It may be that the founding lasts so long as a company’s technical innovation continues. Founders should arguably stay in charge as long as the paradigm remains 0 to 1. Once the paradigm shifts to 1 to n, the founding is over. At that point, executives should execute.”

Max Levchin: The notion that diversity in an early team is important or good is completely wrong. You should try to make the early team as non-diverse as possible. There are a few reasons for this. The most salient is that, as a startup, you’re underfunded and undermanned. It’s a big disadvantage; not only are you probably getting into trouble, but you don’t even know what trouble that may be. Speed is your only weapon. All you have is speed. […] How to hire? A specific application of this is the anti-fashion bias. You shouldn’t judge people by the stylishness of their clothing; quality people often do not have quality clothing. Which leads to a general observation: Great engineers don’t wear designer jeans. So if you’re interviewing an engineer, look at his jeans. There are always exceptions, of course. But it’s a surprisingly good heuristic. […] PayPal also had a hard time hiring women. An outsider might think that the PayPal guys bought into the stereotype that women don’t do CS. But that’s not true at all. The truth is that PayPal had trouble hiring women because PayPal was just a bunch of nerds! They never talked to women. So how were they supposed to interact with and hire them?

“No CEO should be paid more than $150k per year” (in Silicon Valley)
“Another important insight is that people must either be fully in the company or not in it at all.”

Dilution and funding
Building a valuable company is a long journey. A key question to keep your eye on as a founder is dilution. The Google founders had 15.6% of the company at IPO. Steve Jobs had 13.5% of Apple when it went public in the early ‘80s. Mark Pincus had 16% of Zynga at IPO. If you have north of 10% after many rounds of financing, that’s generally a very good outcome. Dilution is relentless. The alternative is that you don’t let anyone else in. It’s worth remembering that many successful businesses are built like this. Craigslist would be worth something like $5bn if it were run more like a company than a commune. GoDaddy never took funding. Trilogy in the late 1990s had no outside investors. Microsoft very nearly joined this club; it took one small venture investment just before its IPO. When Microsoft went public, Bill Gates still owned an astounding 49.2% of the company. So the question to think about with VCs isn’t all that different than questions about co-founders and employees. Who are the best people? Who do you want—or need—on board?

The VC model in a nutshell: a power law. “To a first approximation, a VC portfolio will only make money if your best company investment ends up being worth more than your whole fund. (And the investment in the second best company is about as valuable as number three through the rest.)”

I have not yet read the following classes…

When Peter Thiel talks about Start-ups – part 2: value creation

As promised, here are additional comments from my reading Peter Thiel’s class notes on start-ups at Stanford University (after the general ones in part 1 about innovation). And today, it’s about value creation. When I teach valuation techniques at EPFL, I provide similar information: value creation is future cash flows adjusted for time value (check Wikipedia for valuation using DCF). The difficulty with DCF is that in the case of start-ups most of the value appears in the very long term and given the uncertainty of start-up projection revenues, it makes DCF nearly useless… This is why, for start-ups, it is often easier to use techniques based on multiples & comparables (again check Wikipedia for valuation using multiples.)

Thiel enlighted me here by providing a very interesting explanation of why DCF still makes sense for start-ups. First he defines “Great Technology Companies”: “Great companies do three things. First, they create value. Second, they are lasting or permanent in a meaningful way. Finally, they capture at least some of the value they create.” Surprisingly (for me), the second thing is the most important: they are lasting or permanent in a meaningful way. He then introduces DCF with a growth rate:
dcf-valuation
and then he adds: “Tech and other high growth companies are different. At first, most of them lose money. When the growth rate—g, in our calculations above—is higher than the discount rate r, a lot of the value in tech businesses exists pretty far in the future. Indeed, a typical model could see 2/3 of the value being created in years 10 through 15. This is counterintuitive. Most people—even people working in startups today—think in Old Economy mode where you have to create value right off the bat. The focus, particularly in companies with exploding growth, is on next months, quarters, or, less frequently, years. That is too short a timeline. Old Economy mode works in the Old Economy. It does not work for thinking about tech and high growth businesses. Yet startup culture today pointedly ignores, and even resists, 10-15 year thinking.”

I will not add much more here but just mention that Thiel has in this Class 3 & 4 very interesting arguments about why competition may not be that good and monopoly not that bad for the economy and individuals… “Whether competition is good or bad is an interesting (and usually overlooked) question. Most people just assume it’s good. The standard economic narrative, with all its focus on perfect competition, identifies competition as the source of all progress. If competition is good, then the default view on its opposite—monopoly—is that it must be very bad. But exactly why monopoly is bad is hard to tease out. It’s usually just accepted as a given. But it’s probably worth questioning in greater detail.”

He does the analysis not only for companies but also for individuals with a moving section about fierce competition at Princeton, Yale or Harvard with an interesting comparison with Stanford: “Of all the top universities, Stanford is the farthest from perfect competition. Maybe that’s by chance or maybe it’s by design. The geography probably helps, since the east coast doesn’t have to pay much attention to us, and vice versa. But there’s a sense of structured heterogeneity too; there’s a strong engineering piece, the strong humanities piece, and even the best athletics piece in the country. To the extent there’s competition, it’s often a joke. Consider the Stanford-Berkeley rivalry. That’s pretty asymmetric too. In football, Stanford usually wins. But take something that really matters, like starting tech companies. If you ask the question, “Graduates from which of the two universities started the most valuable company?” for each of the last 40 years, Stanford probably wins by something like 40 to zero. It’s monopoly capitalism, far away from a world of perfect competition.”

zerotoone

He finishes with an analysis consistent with his first class on zero to one: “If globalization had to have a tagline, it might be that “the world is flat.” Technology, by contrast, starts from the idea that the world is Mount Everest. If the world is truly flat, it’s just crazed competition. (…) And yet, the single business idea that you hear most often is: the bigger the market, the better. That is utterly, totally wrong. The restaurant business is a huge market. It is also not a very good way to make money.
(…)
Where does venture capital fit in? VCs tend not to have a very large pool of business. Rather, they rely on very discreet networks of people. That is, they have access to a unique network of entrepreneurs. So VC is anti-commoditized. That kind of dynamic arguably characterizes all great tech companies, i.e. last mover monopolies. Last movers build non-commoditized businesses. They are relationship-driven. They create value. They last. And they make money.”

More to come…

Myths and Realities of Innovation in Switzerland

Xavier Comtesse has just published an excellent report The Health of the Swiss innovation – Ideas for its strengthening, which he gave a summary on his blog, Innovation in Switzerland: it is primarily the domain of Health! This is a very interesting report and it is challenging for me because it “proves” that Silicon Valley is not and should not be a model for innovation in Switzerland: in his introduction he states that “the success of Switzerland in this area is still largely and for many people a mystery, especially since the only model actually known and studied is that of Silicon Valley and it does not fit, as we shall demonstrate, that of Switzerland. Although this model has made California the envy of all, it seems to have finally not been fully copied by anyone.”

cover_dp_innovation_f_400-282x400

But as Comtesse is a bit “Contrarian” (as I am also – my friends often accuse me of debating with myself), he cannot be satisfied with the health of the Swiss innovation. “As soon as the lines of the Swiss model will emerge, it will also show its weaknesses. This will allow us to propose changes to the current situation for a successful future evolution.”

He begins by showing the strength of R&D from the private sector – 75 % of the 16 billion spent in Switzerland. He adds that Roche and Novartis in pharma represent a large portion of this amount (approximately 30% of all R&D spent in Switzerland) and they invest more abroad.

A first point of divergence, R&D is not innovation … In simple terms, innovation is the creation, closer to entrepreneurship than to R&D. Apple has always innovated and much better than other companies, but its R&D ratio is very low.

swiss-r6d-spending
(Click on image to enlarge)

Then he compares Silicon Valley and Switzerland: “Silicon Valley massively encourages the emergence of new actors (start-ups) in the field of information technology and communication (ICT) while the Swiss model promotes rather large incumbents in the field of health.” [Page 20] and even [page 25] “Silicon Valley has deliberately chosen the new technologies of information and telecommunications (including the Internet) as the innovative axis of its development.” He concludes with: “You could say that Switzerland is for health what Silicon Valley is for ICT.”

Second point of divergence: Silicon Valley is not the Mecca of ICT, but that of high-tech entrepreneurship. Genentech and Chiron were the leaders of biotech before being bought by Roche and Novartis respectively. Intuitive Surgical is a leading medical technology company, Tesla Motors could become a major player in the automotive industry and there are hundreds of other start-ups in the fields of energy (massively financed by funds like Khosla or KP), in clean technology and health. Furthermore Silicon Valley has also large established companies such as HP and Intel which are no longer startups.

Comtesse is convinced that Switzerland is less fragile. “As amazing as it may seem, the Swiss model is more robust and efficient over the long term than Silicon Valley because it is less dependent on global rivalries and Silicon Valley may be under threat from Korea, China or any other part of the world. Switzerland is less so because the entry ticket in the field of health, namely the huge investment to develop higher education, university hospitals, research centers, the creation of companies producing blockbusters (products reaching the billion in sales) is so high that few regions can compete in this field.”

Third point of disagreement: I do see how Korea (through Samsung and LG) has indeed become a threat to Silicon Valley but I cannot see why it could not be in the field of health. Investments in electronics and telephony were also huge. Also, the higher and higher reluctance of emerging countries with intellectual property protection (patents) on drugs and the emergence of generics seem to me equally destabilizing.

Finally Comtesse also describes the weaknesses of innovation in Switzerland: “But the question that no politician really wanted to answer was the lack of good projects. If this question is asked the answer is obviously not the creation of science and technology parks, or even the transfer of technology, let alone coaching. It is the creativity that is lacking. How to make Switzerland and especially young people from higher education to be more creative?” Neil Rimer, from Index Ventures, said similar things: “There is innovation in Switzerland, but few entrepreneurs are ready to conquer the world” and “To attract [ … ] you need a critical mass of start-ups so that there are other options available in case of failure. […] Switzerland and its cantons seek to attract traditional companies or the administrative centers of large corporations. […] My biggest wish would be that the authorities encourage the creation of jobs creation in engineering, design, marketing and management. This is how we will attract a critical mass of professionals who create and grow start-ups in Switzerland.” (See L’innovation en Suisse d’après Neil Rimer).

There is a slight difference. Neil Rimer is not talking about good or bad projects, but about ambition. He even said on this blog a few months ago : “I continue to be amazed to hear that there is not enough support in Switzerland for ambitious projects. We and other European investors are perpetually in search of global projects from Switzerland. In my opinion, there are too many projects lacking ambition artificially supported by institutions – who also lack ambition- which gives the impression that there is enough entrepreneurial activity in Switzerland.”

Comtesse then returns to the role of government by distinguishing incremental innovation and disruptive innovation . “Indeed what matters to a nation is its overall innovation capacity including disruptive innovation. But if the State does not take all the risks, then nobody will do it. That is why it is urgent to give further instructions or guidelines to the CTI. Financing incremental innovation should not be its task, or only marginally.” [Page 27] “The Commission for Technology and Innovation (CTI) tends to support incremental innovation projects, which are less risky and easier to implement. These should be the prerogative of private companies and therefore should not benefit from government support. On the contrary, disruptive innovation, similarly to basic research, should be largely the responsibility of government.” [Page 30] “So on the one hand our innovation system is supported by large companies, and on the other hand by innovative SMEs as well, but those do not reach a sufficient critical mass to make often a difference. The idea would be not to finance individual projects as does CTI in general, but multi-partners programs led by one of the major Swiss companies.” [Page 28] “This approach does not preclude the emergence of new start-ups but these would be placed under the protective wing of medium and large Swiss companies. This would avoid start-ups to be immediately sold to the Americans (a phenomenon called “born to be sold”) or and help to counter the fact that they are never able to grow. It should be remembered that over 80 % of our start-ups do not perish in 7 years, while the “normal” rate is 50 % (one might well say that “never die” is another Swiss phenomenon).” [ Page 31]

I agree with him on the analysis, less on the implemention solutions. I find interesting the idea of giving priority of government support to disruptive innovation. It reminds me of the excellent analysis of Mariana Mazzucato about the Entrepreneurial State. I remain much more cautious about the idea of ​​a consortium of major companies to develop and protect our start-ups. I understand the desire to reduce the risk of the sale, but I do not think the concept is realistic. Which real entrepreneur wants to be protected or controlled by a big even if nice brother… I also have some doubts about the ability and entrepreneurial desire of large corporations.

In a little artificial manner, Comtesse adds the idea of ​​a tax incentives for innovation companies. “The Swiss tax system does not explicitly provide incentives for companies that conduct R&D. The simplest solution is the tax credit for innovation that would, in various ways, decease the burden of corporate tax based on their spending in innovation. Many large countries (the United States, Canada, England, Spain and France) have already implemented such an instrument. It is not, however, about encouraging any sector by this tool but rather to create an emulation for long-term innovation in the country. This device must provide to companies, especially SMEs, more freedom of maneuver to face the innovation process.” (See again Comtesse’s blog).

Here I can speak of complete disagreement. You can read again my analysis of Mazzucato denouncing tax optimization in this area. I never believed in tax incentives and I could be wrong. I understand the greater effectiveness of the approach, but I believe there are more perverse effects than real positive ones. Just look at the plight of the American Taxation system of the large technology companies.

Despite my criticism, this is an excellent report. Like all Contrarians, I focus more on disagreements but there are, in this analysis, extremely interesting points about the myths and realities of innovation in Switzerland. A short reminder as a way to end this post: Comtesse published a few months ago a Prezi presentation on the same topic, and you can read my comments about the Swiss model innovation : is it the best?

Silicon Valley and (a)politics – Change the World

My colleague Andrea just mentioned to me this exceptional article about Silicon Valley and its lack of interest, not to say distrust, for politics. It’s been published in the New Yorker in May 2013 and is entitled: Change the World – Silicon Valley transfers its slogans—and its money—to the realm of politics by George Packer.

130527_r23561_p233“In Silicon Valley, government is considered slow, staffed by mediocrities, and ridden with obsolete rules and inefficiencies.” Illustration by Istvan Banyai.

All this is not so far from a recent post I published: The Capital Sins of Silicon Valley. George Packer’s analysis is however profound, subtle and quite fascinating. I will not analyze the article, you have to read it even if it is a vrey long article, and to encourage you in doing so, here are just five quotes:

– “People in tech, when they talk about why they started their company, they tend to talk about changing the world,” Green said. “I think it’s actually genuine. On the other hand, people are just completely disconnected from politics. Partly because the operating principles of politics and the operating principles of tech are completely different.” Whereas politics is transactional and opaque, based on hierarchies and handshakes, Green argued, technology is empirical and often transparent, driven by data.

– Morozov, who is twenty-nine and grew up in a mining town in Belarus, is the fiercest critic of technological optimism in America, tirelessly dismantling the language of its followers. “They want to be ‘open,’ they want to be ‘disruptive,’ they want to ‘innovate,’ ” Morozov told me. “The open agenda is, in many ways, the opposite of equality and justice. They think anything that helps you to bypass institutions is, by default, empowering or liberating. You might not be able to pay for health care or your insurance, but if you have an app on your phone that alerts you to the fact that you need to exercise more, or you aren’t eating healthily enough, they think they are solving the problem.”

– a system of “peer production” could be less egalitarian than the scorned old bureaucracies, in which “a person could achieve the proper credentials and thus social power whether they came from wealth or poverty, an educated family or an ignorant one.” In other words, “peer networks” could restore primacy to “class-based and purely social forms of capital,” returning us to a society in which what really matters is whom you know, not what you could accomplish. (…) Silicon Valley may be the only Americans who don’t like to advertise the fact if they come from humble backgrounds. According to Kapor, they would then have to admit that someone helped them along the way, which goes against the Valley’s self-image.

– “There is this complete horseshit attitude, this ridiculous attitude out here, that if it’s new and different it must be really good, and there must be some new way of solving problems that avoids the old limitations, the roadblocks. And with a soupçon of ‘We’re smarter than everybody else.’ It’s total nonsense.”

– “This is one of the things nobody talks about in the Valley,” Andreessen told me. Trying to get a start-up off the ground is “absolutely terrifying. Everything is against you.” Many young people wilt under the pressure. As a venture capitalist, he hears pitches from three thousand people a year and funds just twenty of them. “Our day job is saying no to entrepreneurs and crushing their dreams,” he said. Meanwhile, “every entrepreneur has to pretend in every interaction that everything is going great. Every party you go to, every recruiter, every press interview—‘Oh, everything’s fantastic!’—and, inside, your soul is just being chewed apart, right? It’s sort of like everybody’s fake happy all the time.”

France: a New Deal for Innovation?

It can be said: France is trying hard to change its innovation culture. After many months of thinking (I was part of an expert group, the Beylat-Tambourin mission), French Minister for Innovation and the Digital Economy, Fleur Pellerin announced a New Deal for Innovation. Some will smile, another state decision! But if you read my posts about Mariana Mazzucato’s The Entrepreneurial State, you will understand my interest.

Fleur Pellerin, à Paris le 30 octobre 2011

In a nutshell, Fleur Pellerin and her team are focusing on:
additional resouces: money is the fuel of innovation, far from sufficient, but critical. A new €500M fund, Large Ventures as well as €30k grants for new entrepreurs (about €10M per year). It’s important to cover seed funding as well as later stage.
attracting talent with a “New Argonaut” policy. there are 50’000 French people in Silicon Valley, they have experience to bring.

Exactly what Paul Graham says in How to be Silicon Valley: you need nerds and rich people. And it is not just the state. Xavier Niel, the most succesful French entrepreneur in recent years is launching 1000start-ups, a huge and ambitious initiative in the heart of Paris with a lot of money…

Yes, France is trying hard!

1000start-ups

You can have a look at the following references, but you need to read French!

L’innovation, c’est un projet de société” in La Tribune
Nous avons une vision trop idéologique de l’entreprise” in Le Monde
Une nouvelle donne pour l’innovation (A New Deal for Innovation) with a 25-page pdf (in French)

Nouvelle-donne-innovation-dossier-presse-France-2013