Tag Archives: Science

Alexander Grothendieck, 1928 – 2014

What link is there between Andrew Grove (the previous article) and Alexandre Grothendieck? Beyond their common initials, a similar youth – both were born in the communist Eastern Europe they left for a career in the West) and the fact they have become icons of their world, they just represent my two professional passions: startups and mathematics. The comparison stops there, no doubt, but I’ll get back to it.

Two books (both in French) were published in January 2016 about the life of this genius: Alexander Grothendieck – in the footsteps of the last mathematical genius by Philippe Douroux and Algebra – elements of the life of Alexander Grothendieck by Yan Pradeau. If you like mathematics (I should say the mathematical science) or even if you do not like it, read these biographies.


I knew as many others about the atypical route of this stateless citizen who became a great figure of mathematics – he received the Fields Medal in 1966 – and then decided to live in seclusion from the world for over 25 years in a small village close to the Pyrenees until his death in 2014. I also have to confess that I knew nothing of his work. Reading these two books shows me that I was not the only one, as Grothendieck had explored lands that few mathematicians could follow. I also found the following stories:
– At age 11, he calculated the circumference of the circle and deduced that π is equal to 3.
– Later, he reconstructed the theory of Lebesgue measure. He was not 20 years old.
– A prime number has his name, 57, who nevertheless is 3 x 19.
Yes, it is worth discovering the life of this illustrious mathematician.


The reason for the connection I made between Grove and Grothendieck is actually quite tenuous. It comes from this quote: “There are only two true visionaries in the history of Silicon Valley. Jobs and Noyce. Their vision was to build great companies … Steve was twenty, un-degreed, some people said unwashed, and he looked like Ho Chi Minh. But he was a bright person then, and is a brighter man now … Phenomenal achievement done by somebody in his very early twenties … Bob was one of those people who could maintain perspective because he was inordinately bright. Steve could not. He was very, very passionate, highly competitive.” Grove was close Noyce in more ways than one, and extremely rational and according to Grove, Noyce was too lax! Grothendieck would be closer to Jobs. A hippie, a passionate individual and also somehow self-taught. Success can come from so diverse personalities.


Last point in common or perhaps a difference. The migration. Grove became a pure American. Grothendieck was an eternal stateless, despite his French passport. But both show its importance. Silicon Valley is full of migrants. I often talk about this here. We know less that what is called “the French school of mathematics” also has its migrants. If you go to the French wikipedia page of the Fields Medal, you can read:

Ten “Fields medalists’ are former students of the Ecole Normale Superieure: Laurent Schwartz (1950), Jean-Pierre Serre (1954), René Thom (1958), Alain Connes (1982), Pierre-Louis Lions (1994) Jean-Christophe Yoccoz (1994), Laurent Lafforgue (2002), Wendelin Werner (2006), Cédric Villani (2010) and Ngo Bao Chau (2010). This would make “Ulm” the second institution after the ‘Princeton’ winners, if the ranking was the university of origin of the medal and not the place of production. Regarding the country of origin, we arrive at a total of fifteen Fields medalists from French laboratories, which could put France ahead as the formative nations of these eminent mathematicians.

But in addition to Grothendieck, the stateless, Pierre Deligne, Belgian, had his thesis with him, Wendelin Werner was naturalized at the age of 9 years, Ngo Bao Châu the year he received the Fields Medal, after doing all his graduate studies in France, and Artur Avila is Brazilian and French … One could speak of the International of Mathematics, which might not have displeased Alexander Grothendieck.

Emerging Science and Technologies, why so many promises? (Part 4)

This is my final post about what I have learned from Sciences et technologies émergentes, pourquoi tant de promesses? (For the record here are the links to part 1, part 2 and part 3).


The last chapters of this excellent book try to explore ways to solve the problem of excessive promises that have become a system. In Chapter IV.2, it is question of “désorcèlement” (the closest term I found would be “disenchanted”); I read it as a critical analysis of the vocabulary used by those who promise. The chapter speaks at length of the transhumanist movement, the promise of promises! “[…] Describe how these actors certainly produce, but especially divert away, reconfigure and amplify these promises […] in front of passive and naive consumers.” [Page 261] and later “[but] transhumanists are first activists, mostly neither engineers nor practitioners […] attempting answers to questions not asked or badly expressed, […] hence a really caricatural corpus,” to the point of talking about a “cult” (quoting Jean-Pierre Dupuy), “a muddled, often questionable thinking.” [Page 262]

In Chapter IV.3, the authors explore unconventional approaches, a possible sign of disarray to “scientifically” react to the promises. For example, they have contributed to the creation of a comic book to answer another comic which wanted to popularize and promote synthetic biology.


The final chapter explores scenarios that may follow the explosion of promises, like the idea of ​​increasing the number of Nobel Prize. New promises?!! More concretely, the author shows that the initial promises are not followed in practice: “The wait & see phenomenon in investment, or lack of innovation, is less known, though widespread: the effect of general and diffuse promises maintains the interest of players but too much uncertainty holds back investment in cycles of concrete promises-requirements.” [Page 297] “A game is at work which continues as long as the players follow the rules, […] they are prisoners of the game. […] They may also leave it if the right circumstances occur and then the game collapses.” [Page 298]

In conclusion, beyond a very rich description of many examples of scientific and technical promises, the authors have shown how a system of promises was built through interactions between the various stakeholders (the researchers themselves, the (political, social and economic) decision makers who fund them, and the general public which hopes and feels anxiety). The relationship to time, not only the future but also the present and the past, is beautifully described, in addition to a desire for eternity. And finally, we mostly discover that the promises have led to numerous debates that were perhaps, if not entirely, useless, as we could have known that the promises can not be kept, even from the moment they were created…

Emerging Science and Technologies, why so many promises? (Part 3)

This is my third article about the book Sciences et technologies émergentes, pourquoi tant de promesses? After the general considerations on the system of promises, the book presents contributions describing specific areas:

I.3: nanotechnologies
II.1: semiconductors through Moore’s Law
II.2: big ata
II.3: digital Humanities
III.1: neurosciences and psychiatry
III.2: The Human Brain Project (HBP)
III.3: personalized medicine
III.4: biodiversity and nanomedicine
IV.1: assisted reproduction
IV.2: regenerative medicine


Each chapter is interesting for the curious reader as it shows the dynamics between promises and expectations of stakeholders (researchers, politicy makers, general public). The chapter about the HBP is particularly interesting in the description of the disconnection between content and form. “How was it possible that the HBP “won the competition” despite the lack of evidence to establish pragmatically the scientific relevance and the legitimacy of its ambitious organizational goals? We develop the hypothesis that this deficit, criticized afterwards, was both hidden and compensated by the production of promises shaped to anticipate and / or respond effectively to the political, economic, social and health-realted stakes on the agenda of the “challenges to come”. [Page 166] The credibility of the HBP sealed by this decision has been built […] following an adaptation process and reciprocal validations in the double register of the politicization of science and the scientification of politics. In other words, we show that one of the important conditions of this credibility was the successful co-production of a strategic congruence between [scientific] promises and the agenda of policy issues. [Page 171] The connection between knowledge of the brain and forms of social life took place mainly in the domain of discourse. […] In this contrasting situation, discursive inflation around the brain and neuroscience seems to be the consequence of a lack of evidence, as if it had overcome, positively or negatively, the differences between the present and the future, the proven and the possible, the absence and the desire. This regular feature of big science projects has resulted in the development and implementation of a prophetic rhetoric that seeks to anticipate the possibility of a better future by borrowing to the notions of hope and promise.” [Page 176-77]

I come back to a quote from chapter 3 that is essential to me as a conclusion to this new post: The real progress of techno-science will less come from their ability to keep promises than from their ability to do without them, to inherit critically from the era of great technological promise. This is not to break an idol, but to learn how to inherit. [Page 111]

Emerging Science and Technologies, why so many promises? (Part 2)

(A word of caution: my English is reaching its limits in trying to analyze a demanding book, written in French. I apologize in advance for the very awkward wording…)

So just one day after my article describing Chapter 1 of Emerging Science and Technologies, why so many promises?, here comes an analysis of the second chapter, where the relation to time is analyzed, as well as presentism, futurism and the role of time in the promise system. There is the nice following passage:


Since The New Atlantis, futuristic speculations have accompanied the development of modern science. And in the twentieth century, Jean Perrin has sealed a new alliance between science and hope. But for him, it is science that preceded and provoked hope while now, it is rather hope that drives research. Technosciences reverse, in fact, the order of the questions that was following the three critiques of Kant: “What can I know?” – the issue addressed in Critique of Pure Reason – then the question “What can I do?” – treated in the Critique of Practical Reason – finally the question “What can I expect?” – discussed in the Critique of Judgment. In contrast, in the current scientific policies, one determines what to do and what we can possibly acquire as knowledge by identifying the hopes and promises. (Page 50)

Yet there is a paradox already expressed in the first chapter between futurism with the terms of promise, foresight and prophecy that project us and presentism particularly marked by the memory that freezes the past and transforms the future as a threat that no longer enlightens neither the past nor the present. To the point of talking about a future presentification…

The chapter also deals with the question of the future as a shock, a time “crisis” due to the acceleration. To the feeling of the misunderstanding and helplessness, is added the experience of frustration and stress caused by the accelerated pace of life, the disappointment of a promise related to modernity, where techniques were supposed to save time, to emancipate.

Another confusion: the features of planning and roadmap which are typical of technology projects slipped into research projects where is used the term of production of knowledge, while in research, it is impossible to guarantee a result. But the author shows through two examples, that this development is complex.

In the case of nanotechnology, there has been roadmap with the first two relatively predictable stages of component production followed by a third stage on more speculative systems crowned by a fourth stage which speaks of emergence, and all this by also “neglecting contingency, serendipity and possible bifurcations,” not to predict, but to “linearize the knowledge production”. The roadmap predicts the unexpected by announcing an emergence, combining a reassuring scenario of control which helps in inspiring confidence and with at the same time an emerging scenario, to create dreams. (Pages 55-56)

In the case of synthetic biology “despite a clear convergence with nanotechnology,” the rapid development occurs without any roadmap. “A common intention – the design of the living – gathers these research paths.” And it is more to redo the past (“3.6 billion years of genetic code”) than to imagine the future. The future becomes abstract and it comes as proofs of concept. And the author adds that in normal science in the sense of Kuhn, these proofs of concepts would have fallen into oblivion. The paradox is that there is no question of right or wrong, but of designing without any needed functionality.

In the first case, “prediction or forecasting are convened as the indispensable basis for a strategy based on rational choice”, “the future looks to the present. “In the second case, there is the question of “towing the present” and “fleeing out of time.” We unite and mobilize without any necessary aim. The future is virtual, abstract, and devoid of culture and humanity; the life of the augmented human looks more like eternal rest …

Ultimately, the economy of promises remains riveted on the present either by making the future a reference point to guide action in the present, or it is seeking to perpetuate the present.

Chapters three and four are less theoretical, describing on one hand new examples in the field of nanotechnology and on the other, how Moore’s Law became a law when it was initially a prospective vision of progress in semiconductor. Perhaps soon a follow-up about the next chapters…

Emerging Science and Technologies, why so many promises? (Part 1)

Sciences et technologies émergentes, pourquoi tant de promesses? (Emerging Science and Technologies, why so many promises?) is the title of a book (in French only) from a group of authors under the direction of Marc Audétat, a political scientist and researcher at the Sciences -Society Interface of the University of Lausanne. This is not an easy reading book, it is quite demanding, but it raises important questions.

I have already reported on this blog about books that speak of a certain crisis of science, for example in The Crisis and the American model (in French), about the books “La Science à bout de Souffle” or “The University bubble. Should we pursue the American dream?” or in The Trouble With…, a book by Lee Smolin, not to mention the most violent criticism of the promises of technology by Peter Thiel in Technology = Salvation.


This new book explores the promises related to science and technology to the point of talking about an economy of promises. This is a collective work which does not make it an easy reading, but the diversity of points of views is certainly an asset. I have not finished reading it and I will certainly come back to it. In the first chapter, P.-B. Joly describes the system of techno-scientific promises. He begins by introducing the concepts of Imaginary and Vision [Page 33] This “couple of concepts takes into account how various sources of inspiration are involved in the technical creation. […] The Imaginary gives an almost tangible appearance to concepts and ideals that are a priori devoid of it … [and becomes] a common sense that founds the action into society. […] The concept of Vision is close to that of Imaginary, but on a smaller scale. It is akin to that of “rational myth” used to analyze the dynamics of collective action in changing contexts. […] Coalitions of actors form around these visions of a prospective order and contribute to their dynamics. […] If we accept this conceptual distinction between Imaginaries (at large scales – the Nation – and in the long term) and Visions (at a level of coalitions of actors and active over periods of medium length) then comes the question of the interaction between the two.”

“Unlike Visions and Imaginaries, for which the content of technical arrangements is essential, what is essential for the techno-scientific promises is the creation of a relation, as well as a time horizon of expectations. […] Promises are essential in technology creation, because they enable innovators to legitimize their projects, to mobilize resources and to stabilize their environment. […] Any techno-scientific promise must convince a large audience that it determines a better future than the alternatives, even if the realization of the promise requires major, sometimes painful changes.” (The author mentions the history of electricity or the green revolution as the solution to world hunger)

“Our concept of techno-scientific promises has been systematized and became in the last forty years the governance of the new techno-sciences (biotechnology and genomics, nanotechnology, neuroscience, synthetic biology, geo -engineering, etc.) The construction of a techno-scientific promise meets two conflicting constraints: the constraint Radical Novelty and that of Credibility. […] (And I interpret that) for this request to be credible, one must disqualify alternatives. [Furthermore] For a scientific theory to be credible, its validity is neither necessary nor sufficient. […] The techno-scientific promises must have the support of a circle of specialists. Otherwise, they cannot resist the opposition manifested either in scientific arenas, or in public arenas. An extreme version is observed when the specialists refer to natural laws to justify the inevitability of technological change. (Examples are Moore’s Law and Gabor’s Law.) Thus, in principle, generic promises are not subject to validity tests.”

Finally, this intensification is reinforced by three complementary elements [page 39]:
– the future is more a threat than a source of hope;
– research and innovation are often presented as the only way to solve problems;
– the research stakeholders should demonstrate their societal impacts.

This leads to pathologies [pages 40-43]:
– the myth of a public victim of irrational fears and to be educated becomes an intangible scheme;
– the promises turn into bubbles;
– the radical novelty and uncertainty create conflicting discourses, sources of mistrust because the effects of such radicalism is not predictable so that through experimentation, the technologists become sorcerer’s apprentices and society, a laboratory;
– finally promises lead to endless discussions on fictions, on issues that may have nothing to do with the reality of research.

In conclusion Joly thinks this promises system is one of the enemies of the future because of the clear separation it creates between those who make the promise and those who are supposed to accept it. The recognition of this regime and therefore these problems is a prerequisite imperative.

After reading the first chapter, I remembered the societal concerns of Cynthia Fleury, about whom I have already said a few things in a digression in the article On France Culture, Transhumanism is Science Fiction. Our democratic societies are in crisis, and the distrust of politics as well as of experts has never been stronger. The issue of research and innovation is a component of this crisis. I am eager to discover the rest of this very interesting (and important) work …

A brilliant conversation about science between Gérard Berry and Etienne Klein

Indeed a brilliant and “crazy” conversation between Etienne Klein, the physicist, and Gerard Berry, Gold Medal of the CNRS for his work in computer science on France Culture’s Conversation Scientifique. They speak about so many beautiful “provocative” things.


On the serious side Berry talks about the difficulty of predicting and the danger of impossible promises, also about the courage in science. Physics talks about energy, computer science about information and so do the new generations, Berry claims. Berry also speaks of the machine and the human. The digital machine, the computer goes very fast, but not with much more intelligence than a steam engine. Except the computer is everywhere. But we, humans, are intuitive, there is no insight in a computer. We are very complementary. Again, I do not agree with transhumanists who believe that the machine will overtake us – in the short term at least. Berry is very annoyed by the notion of intelligence in computers. The performance is not intelligence, but there are many interesting things in AI such as learning, find people in a photo database fascinates Berry.

On the politics of science, Berry expresses great caution and wisdom. “Claiming that a research topic will happen right away is the best way to kill it.” He was answering a question about the quantum computer. “This was the case of artificial intelligence”. There are people willing to promise the moon and more people willing to believe them. They promise sensational things in interesting topics. One must look into these areas, but one should make no promise. Among the possible benefits, but unpredictable, there will be some interesting things.

He also talks about neuroscience. He is fascinated by the way children learn, which is difficult to understand; why the brain freezes after a while. His fascination is that the brain processes information, but we do not understand creativity, the brain is a huge machine which we do not understand. But again, it will be difficult, no doubt very difficult to understand how the brain works. Berry believes “no more than that” in our ability to build artificial neurons to simulate the brain mechanisms. We also discover that pleasure and boredom, motivation are essential to learning. Finally Berry started a short analysis on the current state of research. “Do not do anything new when you want to be successful. Or rather you have to fight.” (just as in any art).

I let you discover the last quarter of an hour which talks about the college of Pataphysique… but you need to understand French…

At the Frontier of Research – the Universe and the Brain – and how Science works?

I just read two amazing books, which at first sight do not seem to have much in common, but indeed have. The first one is Time Reborn by Lee Smolin. The second one is Touching a Nerve by Patricia Churchland.


Beware Newton, Leibniz (not only Einstein) is back!

Lee Smolin revisits the current challenges of the physics of the universe – the incompatibility of general relativity and quantum physics – and tries to bring new ideas such as thinking again about what Time is. It’s not a difficult book but it is so rich with ideas, I am not sure what is the most important. His main idea is that time matters. For example, the law of physics may evolve over time. He also believes that Leibniz’s philosophy is very helpful to understand the universe. [What I remembered of Leibniz is Voltaire critics of him in Candide, with the recurrent “best of all possible worlds“]. Let me just quote Smolin: “the picture of the history of the universe given by causal relations realizes Leibniz’s dream of a universe in which time is defined completely by relations between events. Relationships are the only reality that corresponds to time – relationships of a causal sort.” [Page 58, Penguin 2014 edition]

There is something as stimulating: “Leibniz’s principle has some consequences that should constrain a cosmological theory. One is that there should be nothing in the universe that acts on other things without itself being acted upon.” [Page 116] This is the principle of no unreciprocated actions. I had learnt this when I was shocked to understand that the earth attracts me and keep me from flying, but I also attract the earth. With Einstein, matter modifies space. So if laws act on the universe and its components, then the reverse is true. Laws can evolve and Smolin thinks that this is following a Darwininian natural selection…

Smolin concludes his book with more general considerations about science and society, which are also very interesting. I had already mentioned here his previous book The Trouble with Physics. His views about science are not original but strong. For example “to be scientific, hypotheses must suggest observations by which they could be verified or falsified.” [page 247] and he indeed hates some features of politics in science. Truth is the ultimate even if unreachable goal. “Scientific communities and larger democratic societies from which they evolved, progress because their work is based by two basic principles:
(1) when rational argument from public evidence suffices to decide a question, it must be considered to be so decided,
(2) when rational argument from public evidence does not suffices to decide a question, the community must encourage a diverse range of viewpoints and hypotheses consistent with a good faith attempt to develop convincing public evidence.”
[page 248]

And I will conclude on Smolin with a final quote: “We need a new philosophy, one that anticipates the merging of the natural and the artificial by achieving a consilience of the natural and social sciences, in which human agency has a rightful place in nature. This is not relativism, in which anything we want to be true can be. To survive the challenge of climate change, it matters a great deal what is true. We must also reject both the modernist notion that truth and beauty are determined by formal criteria and the postmodern rebellion from that, according to which reality and ethics are mere social constructions. What is needed is a relationalism, according to which the future is restricted by, but not determined by, the present, so that novelty and invention are possible”. [p 257]


As a transition to the brain, I cheat here and quote Smolin one final time (promised!): “By the problem of consciousness I mean that if I describe you in all the languages physical and biological sciences make available to us, I leave something out. Your brain is a vast and highly interconnected network of roughly 100 billion cells, each of which is itself a complex system running on controlled chains of chemical reactions. I could describe this in as much detail as I wanted, and I would never come close to explaining the fact that you have an inner experience, a stream of consciousness. If I didn’t know, from my own case, that I’m conscious, my knowledge of your neural process would give me no reason to suspect that you are. […] Suppose we mapped the neuronal circuits in your brain onto silicon chips and upload your brain into a computer. Would that computer be conscious? […] Would there now be two conscious beings with your memories whose futures diverge from there.” [pages 268-69]

Patricia Churland begins her book with the “fears” that scientific research brings when you are at the frontier. “I hate the brain, I hate the brain” is what a philosopher said at a conference, maybe to explain his discomfort with the importance of biology to explain the mind processes. Churchland adds that discovering that the earth is not the center of the universe, or the heart is just a pump had similar results in society: fear and denial. But Churchland is not afraid of knowledge and of progress. “My business is to teach my aspirations to conform themselves to fact, not to try and make facts harmonize with my aspirations”

Near the end of her book [page 240], she addresses the topic of consciousness:
In about 1989, psychologist Bernard Baars proposed a framework for research on consciousness with a view to fostering a coevolution of psychology and neurobiology.
First, […] sensory signals of which you are conscious are highly integrated and highly processed by lower-level (nonconscious) brain networks. That is, when you hear [something], you are not first conscious of a string of sounds, then conscious of figuring out how to chunk the string into words, then conscious of figuring out what the words means, then conscious of putting it all together to understand the meaning of the sentence. You hear [it]; you are aware of what [it] meant.
Second, the information stored concerning [the event] are suddenly consciously available to help you decide what to do in this novel situation. This means there must be integration of sensory signals with relevant background knowledge—with stored information.
The third important point is that consciousness has a limited capacity. You cannot follow two conversations at once, you cannot at the same time do mental long division and watch for dangerous eddies in a fast-moving river. When we think we are multitasking, we are probably shifting attention back and forth between two or possibly three tasks, each of which is familiar and which we can perform with minor vigilance.
Fourth, novelty in a situation calls for consciousness and for conscious attention. If you are fighting a barn fire, you must be alert and vigilant. On the other hand, if you are a veteran cow milker, you can milk the cow and can pay attention to something else.
Fifth, information that is conscious can be accessed by many other brain functions, such as planning, deciding, and acting. The information can be accessed by the speech areas so that you can talk about it. Conscious information is kept “on the front burner,” so to speak. That is, the information is available for some minutes in working memory so that your decisions are coherent and flow sensibly together. The widespread availability of a conscious event was a hypothesis that Baars proposed, not an established fact, but it seemed completely plausible and provoked other questions, such as the regulation of access and the range of functions that can have access.
None of these five features is a blockbuster on its own, but notice that collectively they yield a sensible and rather powerful framework for guiding research into further matters, such as how information is integrated and rendered coherent in our experience. Wisely, Baars avoided trying to identify the essence of consciousness, realizing that essences are an old-fashioned way of thinking about phenomena that impede making actual progress. This contrasts with the approach favored by some philosophers, whereby they tried to identify the defining property of consciousness, such as self-referentially, which is knowing that you know that you are feeling an itch or pain.

But in between you might also learn about the role of DNA and genes; of proteins and hormons and other molecules such as androgen, cortisol, dihydrotestosterone, dopamine, estradiol, estrogen, melatonin, nitric oxide synthase, noradrenaline, oxytocin, serotonin, testosteron, vasopressin; and the multiple modules and subsets of our brain.

Both Smolin and Churchland have the highest respect for scientific research and researchers on a quest for truth. Just for that reason, you should read them!

When Science Looks Like Religion: The theory That Would Not Die.

It is the third book I read about statistics in a short while and it is probably the strangest. After my dear Taleb and his Black Swan, after the more classical Naked Statistics, here is the history of the Bayesian statistics.


If you do not know about Bayes, let me just add that I like the beautiful and symmetric formula: [According to wikipedia]
For proposition A and evidence B,
P(A|B) P(B) = P(B|A) P(A)
P(A), the prior, is the initial degree of belief in A.
P(A|B), the posterior, is the degree of belief having accounted for B.
the quotient P(B|A)/P(B) represents the support B provides for A.
Another way of explaining it mathematically is Bayes’ theorem gives the relationship between the probabilities of A and B, P(A) and P(B), and the conditional probabilities of A given B and B given A, P(A|B) and P(B|A).

I was never really comfortable with its applications. I was probably wrong again, given all what I learnt after reading Sharon Bertsch McGrayne’s rich book. But I also understood why I was never comfortable: for three centuries, there’s been a quasi-religious war between Bayesians and Frequentists on how to use probabilities. Are these linked to big, frequent numbers only or can they be applied for rare events? What is the probability of a rare event which may never occur or maybe just once?

[Let me give you a personal example: I am interested in serial entrepreneurship, and did and still do tons of statistics on Stanford-related companies. I have more than 5’000 entrepreneurs, and more than 1’000 are serial. I have results showing that serial entrepeneurs are not on average better than one-time, using frequency and classical methods. But now I should think about using:
P(Success|Serial) = P(Serial|Sucess) P(Success) / P(Serial)
I am not sure what will come out, but I should try!].

If you want a good summary of the book, read the review by Andrew I. Daleby (pdf). McGrayne illustrates the “recent” history of statistics and probabilities through famous (Laplace) and less famous (Bayes) scientists, through famous (the Enigma machine and Alan Turing) and less famous (lost nuclear bombs) stories and it is a fascinating book. I am not convinced it is great at explaining the science, but the story telling is great. Indeed, it may not be about science at all. But about belief as is mentioned in the book: Swinburne inserted personal opinions into both the prior hunch and the supposedly objective data of Bayes’ theorem to conclude that God was more than 50% likely to exist; later Swinburne would figure the probability of Jesus’ resurrection at “something like 97 percent” [Page 177]. It obviously reminded me of Einstein’s famous quote: “God does not play dice with the universe.” This is not directly related but for the second time in my life, I was reading about links between science, probability and religion.

Statistics: Garbage In, Garbage Out?

I have already talked about statistics here, and not in good terms. It was mostly related to Nicholas Nassim Taleb‘s works, The Black Swan and Antifragile. But this does not mean statistics are bad. They may just be dangerous when used stupidly. It is what Charles Wheelan explains among otehr things in Naked Statistics.


Naked Statistics belongs to the group of Popular Science. Americans often have a talent to explain science for a general audience. Wheelan has it too. So if you do not know about or hate the concepts of mean/average, standard deviation, probability, regression analysis, and even central limit theorem, you may change your mind after reading his book.

Also you will be explained the Monty Hall problem or equivalent Three Prisoners problem or why it is sometimes better (even if counterintuitive) to change your mind.

Finally Wheelan illustrates why statistics are useless and even dangerous when the data used are badly built or irrelevant (even if the mathematical tools are correctly used!). Just one example in scientific research (which is another topic of concern to me) “This phenomenon can plague even legitimate research. The accepted convention is to reject a hypothesis when we observe something that would happen by chance only 1 in 20 times or less if the hypothesis were true. Of course, if we conduct 20 studies, or if we include 20 junk variables in a single regression equation, then on average, we will get 1 bogus statistically significant finding. The New York Times magazine captured this tension wonderfully in a quotation from Richard Peto, a medical statistician and epidemiologist: “Epidemiology is so beautiful and provides such an important perspective on human life and death, but an incredible amount of rubbish is published”.
Even the results of clinical trials, which are usually randomized experiments and therefore the gold standard of medical research, should be viewed with some skepticism. In 2011, the Wall Street Journal ran a front-page story on what it described as one of the “dirty little secrets” of medical research: “Most results, including those that appear in top-flight peer-reviewed journals, can’t be reproduced. […] If researchers and medical journals pay attention to positive findings and ignore negative findings, then they may well publish the one study that finds a drug effective and ignore the nineteen in which it has no effect. […] On top of that, researchers may have some conscious or unconscious bias, either because of a strongly held prior belief or because a positive finding would be better for their career. (No one ever gets rich or famous by proving what doesn’t cure cancer. […] Dr. Ionnadis [a Greek doctor and epidemiologist] estimates that roughly half of the scientific papers published will eventually turn out to be wrong.”
[Pages 222-223]

When age does not hinder creativity: a rare example in mathematics

I seldom (but sometimes) talk about Science or Mathematics. Mostly when it helps me illustrate what innovation or creativity is about, and sometimes when I see analog crises in all these fields (see for example the posts on Dyson, Thiel or Smolin). And there is another related point: it is often claimed that major scientific discoveries or entrepreneurial ventures are done at a young age.

Yitang Zhang

You probably never heard of Yitang Zhang who has stunned the world of mathematics last month by proving a centuries-old problem. He is a totally unknown mathematician and more surprising, he is (over) 50-year old. For those interested in the problem, you can read Nature’s First proof that infinitely many prime numbers come in pairs. Basically, Zhang proved that there are infinitely many pairs of primes that are less than N apart. Mathematicians still dream to prove that N is equal to 2 – the twin prime conjecture -, but Zhang was first to prove that N exists … even if N is 70 million!