Dear Krassimir,

Formalism is nice, but it can be unreasonable.

Your example of 2 naked men on a beach can be made simpler by adding a dog,
a sausage and a whistle.

Person A (the dog's owner) sounds the whistle. The dog is apparently used
to being fed and runs up, waging its tail.

1) person A think:
a) the dog thinks it will be fed,
b) this other naked guy thinks I am introducing Pawlow to formal logic;

2) person B think:
a) the measure of intelligence is based on the number of repetitions of a
stimulus until the conditioned reflex is established,
b) this other naked guy apparently teaching his dog to learn to listen to
the whistle;

3) the dog think
a) food coming,
b) the connection between whistle and sausage is a secret that I have
mastered, no other dog will ever figure out the mystery,
c) we dogs live in a world in which past and future exist; these are
connected by the moment, which is the natural home  (in fact, so far, the
only home) of formal logic;
d) poor humans have no fur and can not therefore think.

Do you think you can't navigate a crossing because you are not able to
figure out what the drivers in the cars coming will think? Because they are
not naked?

It is time to start talking about what Pawlow said.  Maybe, after that we
can start discussing what Gregor Mendel said. After that, one will cry

Time slips by while we waste time.


Am 07.03.2018 21:10 schrieb "Krassimir Markov" <>:

> Dear Alberto,
> Let imagine that we are at the naturist beach, i.e. naked.
> OK!
> You will see all what I am and I will se the same for you.
> Well, will you know what I think or shall I know the same for you?
> Simple answer: NOT!
> No Data base may contain any data about my current thoughts and feelings.
> Yes, the stupid part of humanity may be controlled by big data centers.
> But all times it had been controlled. Nothing new.
> The pseudo scientists may analyze data and may create tons of papers.
> For such “production” there was and will exist corresponded more and more
> big cemeteries.
> I had edited more than one thousand papers.
> Only several was really very important and with great scientific value !!!
> Collection of data is important problem and it will be such for ever.
> But the greater problem for humanity is collection of money [image: Smile]
> And the last cause the former!
> And the last is many times more dangerous than former!
> Do not worry of Data-ism!
> Be worried of the Money-ism!
> I will continue next week because this is my second post  ( Thanks to
> wisdom of Pedro who had limited Writing-letter-ism in our list! ).
> Friendly greetings
> Krassimir
> *From:* Alberto J. Schuhmacher <>
> *Sent:* Tuesday, March 06, 2018 10:23 PM
> *To:* fis <>
> *Subject:* [Fis] Is Dataism the end of classical hypothesis-driven
> research and the beginning of data-correlation-driven research?
> Dear FIS Colleagues,
> I very much appreciate this opportunity to discuss with all of you.
> My mentors and science teachers taught me that Science had a method, rules
> and procedures that should be followed and pursued rigorously and with
> perseverance. The scientific research needed to be preceded by one or
> several hypotheses that should be subjected to validation or refutation
> through experiments designed and carried out in a laboratory. The Oxford
> Dictionaries Online defines the scientific method as "a method or procedure
> that has characterized natural science since the 17th century, consisting
> in systematic observation, measurement, and experiment, and the
> formulation, testing, and modification of hypotheses". Experiments are a
> procedure designed to test hypotheses. Experiments are an important tool of
> the scientific method.
> In our case, molecular, personalized and precision medicine aims to
> anticipate the future development of diseases in a specific individual
> through molecular markers registered in the genome, variome, metagenome,
> metabolome or in any of the multiple "omes" that make up the present
> "omics" language of current Biology.
> The possibilities of applying these methodologies to the prevention and
> treatment of diseases have increased exponentially with the rise of a new
> religion, *Dataism*, whose foundations are inspired by scientific
> agnosticism, a way of thinking that seems classical but applied to
> research, it hides a profound revolution.
> Dataism arises from the recent human desire to collect and analyze data,
> data and more data, data of everything and data for everything-from the
> most banal social issues to those that decide the rhythms of life and
> death. “Information flow” is one the “supreme values” of this religion. The
> next floods will be of data as we can see just looking at any electronic
> window.
> The recent development of gigantic clinical and biological databases, and
> the concomitant progress of the computational capacity to handle and
> analyze these growing tides of information represent the best substrate for
> the progress of Dataism, which in turn has managed to provide a solid
> content material to an always-evanescent scientific agnosticism.
> On many occasions the establishment of correlative observations seems to
> be sufficient to infer about the relevance of a certain factor in the
> development of some human pathologies. It seems that we are heading towards
> a path in which research, instead of being driven by hypotheses confirmed
> experimentally, in the near future experimental hypotheses themselves will
> arise from the observation of data of previously performed experiments. Are
> we facing the end of the wet lab? Is Dataism the end of classical
> hypothesis-driven research (and the beginning of data-correlation-driven
> research)?
> Deep learning is based on learning data representations, as opposed to
> task-specific algorithms. Learning can be supervised, semi-supervised or
> unsupervised. Deep learning models are loosely related to information
> processing and communication patterns in a biological nervous system, such
> as neural coding that attempts to define a relationship between various
> stimuli and associated neuronal responses in the brain. Deep learning
> architectures such as deep neural networks, deep belief networks and
> recurrent neural networks have been applied to fields including computer
> vision, audio recognition, speech recognition, machine translation, natural
> language processing, social network filtering, bioinformatics and drug
> design, where they have produced results comparable to and in some cases
> superior to human experts. Will be data-correlation-driven research the new
> scientific method for unsupervised deep learning machines*? *Will
> computers became fundamentalists of *Dataism*?
> Best regards,
> AJ
> ---
> Alberto J. Schuhmacher, PhD.
> Head, Molecular Oncology Group
> Aragon Health Research Institute (IIS Aragón)
> Biomedical Research Center of Aragon (CIBA)
> Avda. Juan Bosco 13, 50009 Zaragoza (Spain)
> email:
> Phone:(+34) 637939901
> ------------------------------
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