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Rafael Ferreira
Works at EO2
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Rafael Ferreira

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I'm working on it
About 18 months ago, reports indicating that the NSA spied on the private communications of Brazilian President Dilma Rouseff began to surface. Now comes word via Bloomberg that Brazil is working h...
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John von Neumann on how failure precautions shape systems.

"If you look at automata which have been built by men or which exist in nature you will very frequently notice that their structure is controlled to a much larger extent by the manner in which they might fail and by the (more or less effective) precautionary measures which have been taken against their failure. And to say that they are precautions against failure is to overstate the case, to use an optimistic terminology which is completely alien to the subject. Rather than precautions against failure, they are arrangements by which it is attempted to achieve a state where at least a majority of all failures will not be lethal. There can be no question of eliminating failures or of completely paralyzing the effects of failures. All we can try to do is to arrange an automaton so that in the vast majority of failures it can continue to operate. These arrangements give palliatives of failures, not cures. Most of the arrangements of artificial and natural automata and the principles involved therein are of this sort."

Quoted in General Systems Thinking by Gerald Weinberg
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Not terribly surprising, but useful to know: "Now researchers have taken a more rigorous approach to evaluating peer review, by tracking the fate of more than 1,000 papers that were submitted ten years ago to the Annals of Internal Medicine, the British Medical Journal and The Lancet.  Using subsequent citations as a proxy for quality, the team found that the journals were good at weeding out dross and publishing solid research. But they failed — quite spectacularly — to pick up the papers that went to on to garner the most citations. The shocking thing to me was that the top 14 papers had all been rejected, one of them twice,” says Kyle Siler, a sociologist at the University of Toronto in Canada, who led the study"

(via many people)

CC +Joshua Gans 
Top medical journals filter out poor papers but often reject future citation champions.
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Another project out of MIT media lab. Fairly compelling UX with 3D interaction (above and behind) with a tablet. Would be a lot better without the glove, though I'm not sure any of the gesture recognition out there yet (using, eg, interference with WiFi/cell signal, cameras, or sonor) is up to the fine-grained requirements of the task. Paper (http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/43152.pdf) and video (http://vimeo.com/42173010).
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This is an incredibly interesting and potentially important bit of research. A few years ago, the neural connectome of the worm C. elegans was mapped -- that is, we have a map of all 302 neurons in this worm, and how they're connected to one another and to things like muscles and sense organs. +Timothy Busbice's team used this information to make a simple computer simulation of the worm's neurons. (I'm saying "neurons" instead of "brain" because this worm doesn't actually have a discrete brain; it's a simple enough creature that its neurons are just spread throughout its body) 

They connected their simulation to a simple robot. The worm's "nose touch" sense neurons were connected to a sonar sensor on the robot, so the robot coming within 20cm of an object will give the neurons the signals that a worm would get if it touched something. The motor neurons which control the 95 body muscles of the worm were instead hooked up to a computer simulation of the muscles which boils down their actions to simple "squinch left" and "squinch right" motions, which were translated into the motions of two wheels.

When it was wired together and powered up, the robot started to show clear worm-like behaviors, as you can watch in this video (CElegans Neurorobotics): it could sense and avoid simple obstacles and head towards food.

This simulation is currently incredibly crude. The simulation of the neurons themselves, for example, only allows one kind of "connection" between neurons; real neurons can interact in a few ways, chemically, electrically, and so on. One of the team's next tasks is to make that simulation more realistic. Another issue may be to give it a better robotic analogue, so that they can replace (for example) the crude mapping of motor neurons to wheels with a more intricate mapping to actual muscle behaviors and the way real worms move. And of course, there are other kinds of interaction which this doesn't yet capture at all -- for example, the hormone-mediated interactions which connect the neurons to the worm's digestive system.

However, even in its very crude initial state, this research tells us some very important things.

First and foremost, the simple simulation of neurons themselves is enough to mimic basic worm behaviors. This is important because, while we've always theorized that mind and behavior come from our neurons, and not from any additional source, this is the acid test which we've never been able to do before: strip away everything but the neurons, and see if pure neural connections can really explain behavior.

Second, this is a baseline system which can easily be expanded to have all of the additional details which we've been lacking, and C. elegans is a simple enough creature that it's quite feasible to think that we'll be able to map and simulate all of the requisite parts -- not just a crude simulation. We could expect that this system will ultimately grow to be a complete enough simulation that, if it were to fail to mimic any observed behavior of the actual worm, we would have thereby discovered an important part of how biology works which we had not yet mapped. That, in turn, can drive discovery of more mechanisms, and ultimately we expect that we should be able to make a 100% mimic of the worm. If we can't, then there's a major discovery right there.

Most importantly, this sort of simulation allows us to understand the actual workings of biology much more deeply. For example, one thing we already know about the connectome is that it is highly recursive: that is, neural connections loop back on each other extensively. This is different from how we normally build neural nets in AI research, and one of its consequences is that once signals start coming in to the worm's brain, persistent patterns start getting set up in it: things which we can consider to be the precursors of memory and consciousness. 

A simulation allows us to make changes and understand their effects. By adding and removing connections, for example, we can start to learn why the brain is wired the way it is, and what the ways are in which it can fail. (Which can have significant medical consequences!) Likewise, as our simulation of C. elegans becomes more and more sophisticated, we can look at every aspect of biology and how it influences the system as a whole.

Over time, of course, we could even expect to simulate far more complex creatures. Mapping the connectome of more complex creatures -- insects, small mammals, and even humans -- is a work in progress. We are unlikely to be able to map the complete network of all of the biology of a complex creature in the near future, but this work on C. elegans should be able to hint to us which aspects of the biology are most important to map correctly in order to understand the function of mind.

It is not at all out of the question that within the next decade, we will have a meaningful simulation of the mind of a rat or a similarly complex creature. This would be a major work, of course, of a complexity on a par with any of the major scientific efforts of our time, but its impact on our world could be profound -- from the perspective of understanding ourselves, from the perspective of medicine, and even from the perspective of artificial intelligence.

(Or, I suppose, from the perspective of being to upload our brains into computers in a meaningful way, which is certainly an interesting approach to the problem of medicine and extending life.)

The projects in this field, including large individual efforts like the Human Connectome Project (humanconnectomeproject.org), which is trying to map the connectome of the human brain at MRI granularity, and data informatics efforts like the Open Connectome Project (openconnectomeproject.org), which aims to pull together and make available a wide variety of connectome data, are among the most interesting directions in science today. 

h/t +Jeff Dean.
Editor's note: this is an excerpt from the latest edition of BioCoder; it is republished here with permission. Get your free copy of BioCoder Fall 2014 here. One...
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Tom Ball, Ras Bodik, +Greg Morrisett, and I are organizing a new kind of programming languages conference. We already have several excellent conferences, but they are focused on incremental bits of novelty. We want to create a new kind of venue that complements these: to present and discuss big-picture questions and long-running programs; to view progress along the long arc of a research effort. The conference is May 3-6, 2015 in lovely Asilomar (on the Pacific Coast), CA, USA.

If this sounds interesting, please: don't just +1 it, reshare it. Why? To keep costs down and retain ownership of the conference with the community, we are independent, not affiliated with any organizations. That means you are the only PR channel we have. So please do us a favor. Thanks.
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Maybe the most beautiful factory-tour video ever made.
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Survivorship bias is when you only pay attention to the data points that "survived" and ignore the ones that failed. A classic example is when comparing financial funds. Funds that lose money will eventually get shut down, boosting the average performance for funds that survive. You can be sure that the people who run financial firms are aware of this.

Apparently survivorship bias is a problem when comparing schools using test scores. If a school is particularly strict and has a high drop-out rate, it will tend to have higher scores than a more lenient school that gives students more chances after they screw up. This will be true whether or not being strict is a good policy for students.

We don't have to assume that schools are intentionally gaming test scores. If charter schools with higher test scores tend to survive then this will have an evolutionary effect encouraging strictness. But you can be sure that many school administrators are smart and, even if they didn't know the effect of strictness on test scores going in, they will eventually figure it out.

(Of course, people don't have to act on incentives, and we can praise schools that try to do the right thing in spite of them. But knowing that leniency is against your interests probably doesn't help, particularly when stricter schools are getting a lot of positive publicity.)

The statistical solution is to make sure that dropouts are counted when evaluating performance. We might even consider taking the school's admission policies into account, since not letting poor-performing students into the school in the first place is another way to increase test scores.

But if schools can choose how to present statistics about test scores when promoting themselves and we naively believe what we read in the news, these adjustments won't be made. Furthermore, this will tend to convince parents that stricter schools are better for their children, whether or not it's really true.

Something to remember when thinking about how incentives work.
An experienced researcher saw a story in the Economist about charter schools. It was, as is typical among news stories, incredibly naive. The writer didn't ask the right questions. Maybe he already...
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Photo Sphere made on Café Tortoni, Buenos Aires, Argentina. 
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Photo spheres from Mendoza, Argentina. 
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In his circles
1,292 people
Have him in circles
291 people
Lucio Cristiano's profile photo
Walzenir Carvalho's profile photo
Mike Higgins's profile photo
Scott Arenz's profile photo
PATRÍCIA JULIANE's profile photo
Leonardo Lorieri's profile photo
Rodrigo Sposito's profile photo
Andrei Formiga's profile photo
Willlians Queiroz's profile photo
Work
Occupation
Programmer,
Employment
  • EO2
    Senior Software Engineer, 2013 - present
  • R7.com
    Systems Architect, 2011 - 2013
  • R7.com
    Specialist Software Engineer, 2010 - 2011
  • Caelum
    Programmer,, 2008 - 2010
  • Sun
    2006 - 2008
  • Twic
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Map of the places this user has livedMap of the places this user has livedMap of the places this user has lived
Currently
São Paulo
Previously
Curitiba
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http://rafaelferreira.net
Introduction
Programming language enthusiast and all-around loudmouth.
Education
  • USP
    2003
  • CEFET-PR
  • Jean Piaget
Basic Information
Gender
Male
Other names
Rafael de F. Ferreira, Rafael de França Ferreira