Mostrando entradas con la etiqueta Programación. Mostrar todas las entradas
Mostrando entradas con la etiqueta Programación. Mostrar todas las entradas

domingo, 9 de noviembre de 2014

DARPA funds $11 million tool that will make coding a lot easier


DARPA is funding a new project by Rice University called PLINY, and it's neither a killer robot nor a high-tech weapon. PLINY, named after Pliny the Elder who wrote one of the earliest encyclopedias ever, will actually be a tool that can automatically complete a programmer's draft -- and yes, it will work somewhat like the autocomplete on your smartphones. Its developers describe it as a repository of terabytes upon terabytes of all the open-source code they'll find, which people will be able to query in order to easily create complex software or quickly finish a simple one. Rice University assistant professor Swarat Chaudhuri says he and his co-developers "envision a system where the programmer writes a few of lines of code, hits a button and the rest of the code appears." Also, the parts PLINY conjures up "should work seamlessly with the code that's already been written."

In the video below, Chaudhuri used a sheet of paper with a hole in the middle to represent a programmer's incomplete work. If he uses PLINY to fill that hole, the tool will look through the billions of lines of code in its collection to find possible solutions (represented by different shapes in the video). Once it finds the nearest fit, the tool will clip any unnecessary parts, polish the code further to come up with the best solution it can, and make sure the final product has no security flaws. More than a dozen Rice University researchers will be working on PLINY for the next four years, fueled by the $11 million funding from the Pentagon's mad science division.

[Image credit: Shutterstock / Yellowj]


ORIGINAL: Engadget
November 9, 2014

miércoles, 24 de septiembre de 2014

Made With Code



We started Made with Code because even though technology runs more and more of our lives, women aren't represented in the companies, labs, research, creative arts, design, organizations, and boardrooms that make technology happen

If girls are inspired to see that Computer Science can make the world more beautiful, more usable, more safe, more kind, more innovative, more healthy, and more funny then hopefully they will begin to contribute their essential voices. 

As parents, teachers, organizations, and companies we're making it our mission to creatively engage girls with code. Today, less than 1% of girls are interested in CS. Tomorrow, we can make that number go up.

viernes, 4 de julio de 2014

Google launches ‘Made with Code’ initiative to encourage more girls to code, backed by $50m pledge


Google has announced that it will provide up to $50 million for organizations that can help encourage more girls to take an interest in computer science at an early age.

Revealed as part of its newly launched Made with Code initiative, the cash will be used for things like “rewarding teachers who support girls who take CS courses on Codecademy or Khan Academy,Susan Wojcicki said in a blog post today.


Other aspects of the Made with Code scheme – which is also backed by other organizations like Girls Inc., Girl Scouts of the USA, MIT Media Lab and the National Center for Women & Information Technology, among others – include Blockly-based projects, like making a 3D printed bracelet, learning to create GIFs and “building beats” for a music track.

Google has put together a standalone site for the initiative too, so if you want to get involved you can head across there now.

Things you love are Made with Code [Google]

Don’t miss: Codecademy, Google and DonorsChoose team up to get more girls studying Computer Science

Featured Image Credit – GEORGES GOBET/AFP/Getty Images

ORIGINAL: The Next Web

lunes, 14 de abril de 2014

La receta de Estonia para convertirse en una potencia tecnológica


La programación se enseñará desde la edad de siete años en Estonia.
En algunos países, la programación informática es vista como el reino de los nerds o fanáticos de la computación. Pero en Estonia se ve con ojos muy distintos.

En este pequeño territorio, parte de lo que fuera una vez la Unión Soviética, programar es algo divertido, algo de moda, una asignatura que se enseña a los niños desde la infancia.

A los siete años las escuelas de Estonia ya enseñan a sus alumnos a programar computadoras y el país es considerado uno de los países más dependientes de internet en el mundo.
Una revolución digital
La i-revolución de Estonia empezó en los años 90, no mucho después de la independencia del país. Toomas Hendrik Ilves, entonces el embajador del país en Estados Unidos y hoy presidente de Estonia, se adjudica parte del mérito.

Hay una historia que Hendrik no se cansa de repetir sobre su estadía en Estados Unidos. Cuenta que leyó un libro en el que se hablaba de cómo el auge de las computadoras supondría la muerte del trabajo.

El libro hablaba de una planta de producción de acero en Kentucky donde miles de trabajadores fueron despedidos debido a la automatización. Los nuevos dueños podían producir la misma cantidad de acero con sólo 100 empleados.

"Esto puede que sea malo si eres estadounidense", dice Ilves, "pero desde el punto de vista de un estonio, donde existe una angustia existencial por el pequeño tamaño del país (sólo teníamos entonces 1,4 millones de habitantes), me dije que era exactamente lo que necesitábamos".

"Necesitamos informatizar, de todos los modos posibles, para incrementar nuestro tamaño funcional".


Colegios en línea
 

El presidente Toomas Hendrik Ilves es un promotor de la revolución tecnológica en Estonia.

Así fue como Estonia pasó a convertirse en I-Estonia, bromea Ilves. Y con la ayuda de las inversiones del gobierno para respaldar la tecnología, canalizada a través de la Tiger Leap Foundation, todas las escuelas estonias tenían presencia en internet a finales de los 90.

A través de esta fundación se enseña programación a los alumnos de secundaria, pero los últimos proyectos introducen esta materia a niños de más temprana edad; a la edad de siete. Hasta el momento, ya se ha entrenado a 60 profesores para enseñar durante los próximos cuatro años.

"En septiembre, cuando empiece el nuevo año escolar, espero que cada escuela crea importante integrar la programación en sus clases", afirma Ave Lauringson, de Tiger Leap, quien está a cargo del proyecto.

En un nuevo edificio pintado en amarillo en la localidad de Lagedi, fuera de la capital de Estonia, Tallínn, ya se puede ver cómo esto va tomando forma.

Una clase de niños de diez años diseñan sus propios juegos de computadora bajo la supervisión del profesor de tecnologías de la información y comunicación Hannes Raimets, un callado joven de 24 años.

"Creo que enseñarles a programar conlleva un montón de beneficios. Les ayuda a desarrollar su creatividad y pensamiento lógico", asegura, "también es divertido construir tu propio programa. Creo que es su asignatura favorita en la escuela", asegura.

Lo que es evidente también es que la programación informática, al menos a un nivel básico, no es tan difícil.

Programar, como aprender idiomas




Estonia lleva varios años promoviendo la enseñanza de programación en las escuelas.

Ilves señala lo mismo. Hijo de estonios nacido en Estocolmo, estudió en una escuela estadounidense. Aprendió programación a los 13 años, como parte de una clase experimental de matemáticas y dice que esto le ayudó a financiar su entrada a la universidad.

"No creo que programar computadoras sea un secreto tan profundo y oscuro. Creo que es estrictamente lógica", afirma.

"Aquí en Estonia, empezamos la enseñanza de idiomas extranjeros en Grado Uno o Grado Dos. Si estás aprendiendo las reglas de la gramática a los siete u ocho ¿Cómo difiere de las reglas de la programación? De hecho, programar es mucho más lógico que aprender cualquier idioma".

El presidente argumenta que las reformas educativas tardan entre 15 y 25 años en tener efecto. La prueba, dice, es la cantidad de empresas de tecnología estonias que están atrayendo la atención de los inversores.

Una de ellas es Frostnova, cuyo jefe ejecutivo, Mikk Melder, de 25 años, ha diseñado un videojuego para niños de primaria llamado Ennemuistne, centrado en el folklore y los mitos locales.

La herencia de Skype

Aunque de los inventos tecnológicos estonios, el más popular mundialmente es el servicio de telefonía a través de internet Skype.

Microsoft compró Skype en 2011 por US$8.500 millones, pero todavía emplea a 450 trabadores en su sede local, a las afueras de Tallinn.

Tiit Paananen de Skype, dice que son unos apasionados de la educación y que la empresa trabaja de cerca con las universidades estonias y las escuelas de secundaria.

"Tu capacidad no sólo para usar, sino para crear componentes tecnológicos, te dará competitividad", afirma Paananen, que dice estar feliz de que se empiece a enseñar programación a edades más tempranas.

"Skype ha generado una oleada de innovaciones tecnológicas en Estonia, y estos puestos especializados y bien pagados, necesitarán a estos brillantes cerebros en un futuro".

Siga la sección de tecnología de BBC Mundo a través clic @un_mundo_feliz

ORIGINAL: BBC Mundo
Tim Mansel BBC, Estonia
15 de mayo de 2013

viernes, 28 de febrero de 2014

Stephen Wolfram's Introduction to the Wolfram Language

Stephen Wolfram introduces the Wolfram Language in this video that shows how the symbolic programming language enables powerful functional programming, querying of large databases, flexible interactivity, easy deployment, and much, much more.

To learn more about the Wolfram Language, visit reference.wolfram.com/language.

For the latest information, visit www.wolfram.com.






domingo, 29 de diciembre de 2013

Gorgeous Computer-Generated Flowers Bloom: Photos


British philosopher and mathematician Bertrand Russell once said, "Mathematics, rightly viewed, possesses not only truth, but supreme beauty." One look at these computer-generated images from Daniel Brown and Russell's words come to life.

Brown, a London-based designer, programmer and artist who specializes in digital technology and interactive design uses custom algorithms to "grow" gorgeous floral artwork that will blow your mind. Here are 11 of our favorites.
Courtesy Daniel Brown


It all started in 1999, when Brown demonstrated a computer program and mathematical model that used special code to produce fractals. The resulting animations were almost hypnotic. "It was the first time I realized that non-technical people could aesthetically appreciate mathematical formulas if they saw them 'come alive,'" he said.
Courtesy Daniel Brown


Brown created the pieces in this slideshow for the Victoria and Albert Museum and the D'Arcy Thompson Zoology Museum, as well as projects for corporate clients. A swimming accident in 2003 broke Brown's spinal cord, causing paralysis. As a result, he uses a finger-splint device and a large track pad to operate a computer. Even without this added challenge, his flowers are uniquely beautiful; no two look exactly the same.
Courtesy Daniel Brown


Several years ago Brown produced a three-story-high projection of flowers for the Victoria and Albert Museum. Each petal generated contained combinations of images from the museum's textile collection. The work was named in honor of D'Arcy Wentworth Thompson, a pioneering bio-mathematician known for his 1917 book On Growth and Form.
Courtesy Daniel Brown


Last year, the D'Arcy Thompson Zoology Museum at the University of Dundee in Scotland contacted Brown after seeing his Victoria and Albert Museum work and asked him to create a piece for them. Brown said he used generative design to create the realistic flowers for this newer exhibition, which went up last spring. Each flower shape is determined by an algorithm that is then altered to take into account natural variation.
Courtesy Daniel Brown


Another mathematical formula is used to generate the color and texture applied to the shapes. Each arrangement is grown over about 50 seconds, resembling time-lapse photography that's been sped up. "After this, they fade out and another arrangement is created," he said.
Courtesy Daniel Brown


Brown's original pieces only used two-dimensional computer graphics that mimicked a 3-D look. However, in the past few years, computer technology has evolved so that he can simulate surfaces, behaviors and lighting in real time.

Sometimes Brown produces a flower that even amazes him. "I can't work out the particular parameters that would have gone into it, and am left scratching my head," he said. "Because the flowers regenerate every minute or so, it's a fleeting moment, and there is something almost poetic knowing that no one will ever see that one flower again."
Courtesy Daniel Brown


D'Arcy Wentworth Thompson was a Scottish scientist and scholar who took various natural processes such as evolution and tried to question them mathematically. He sought to discover out how differences in shape and form between two genetically related species could be mathematically modeled, Brown explained.

He also wondered about physical processes like weather, and how they could change one shape into another. Getting contacted by the D'Arcy Thompson Zoology Museum was the ultimate honor, Brown said. "I couldn't think of a more fitting thing to do for one of my scientific heroes."
Courtesy Daniel Brown


Brown's flowers are so realistic that occasionally museum visitors won't realize they're computer graphics and will insist on asking him what kind of flowers they are. Other reactions are more visceral.

"When my work was on show in the Victoria and Albert Museum, young children -- toddlers rather -- would run up to the wall it was being projected on and try and hug it," he said. "At that moment people stop seeing technology, and just see beauty."
Courtesy Daniel Brown


While he's staying quiet about plans for future art projects, Brown said he looks forward to a future when 3-D printing is refined enough to print realistic versions of his computer flowers.

Courtesy Daniel Brown


He imagines he'll be able to make ever more intricate and extraordinary flowers. "Although I was both an artist and programmer before my injury, I have switched to creating art purely with code," Brown said. "In that way I consider myself incredibly lucky. I think I had one of the only jobs in the world that could 'survive' such a life changing event as that."

To see more images, visit Daniel Brown's Flickr page.
Courtesy Daniel Brown


ORIGINAL: Discovery
by Alyssa Danigelis
Nov 21, 2013

lunes, 2 de diciembre de 2013

Sentient code: An inside look at Stephen Wolfram’s utterly new, insanely ambitious computational paradigm

Stephen  Wolphram

In 2002 Stephen Wolfram released A New Kind of Science and immediately unleashed a firestorm of wonder, controversy, and criticism as the British-born scientist, programmer, and entrepreneur overturned conventional ideas on how to pursue knowledge. Earlier this month, he teased something with the capacity to create as much passion — and, likely, much more actual change — in the world of programming, computation, and applications.

Today, Wolfram gave me a glimpse under the hood in an hour-long conversation. And I have to say, what I saw was amazing.


Whether you think his 1,300-page tome on the future of scientific exploration is seminal or fanciful, you can’t question that the man is a genius. Born of Jewish parents who fled persecution in pre-WWII Germany (remind you of another scientist?), Wolfram wrote a dictionary on physics at age 12 and three books on particle physics by the time he was 14, publishing his first scientific papers at 15.

In 1988 he released the first version of Mathematica, a platform for technical computation, and in 2009, he released the Wolfram Alpha search engine, a computational knowledge engine. His new project, he says, is a perfect marriage.

Mathematica is this perfect precise computation engine, and WolframAlpha is general information about the world,” Wolfram told me. “Now we can combine the two.”

The combination is just part of the picture. Included in the new project is natural language programming — not that a program can be created exclusively with natural language, but that a developer can use some natural language. Also included is a new definition of literally anything in your application — from code to images to results to inputs — as being usable and malleable as a symbolic expression. There’s a whole new level of automation and a completely divergent approach to building a programming language, away from the small, agile core with functionality pushed out to libraries and modules and toward a massive holistic thing which treats data and code as one. And there’s a whole new focus on computation that knows more about the world than the programmer ever could.

‘Insanely more ambitious’ than Google knowledge graph
But don’t compare it to Google’s knowledge graph or semantic search.

Wolfram
Components of the Wolfram language.
The knowledge graph is a vastly less ambitious project than what we’ve been doing at Wolfram Alpha,” Wolfram says quickly when I bring it up. “It’s just Wikipedia and other data.

Google wants to understand objects and things and their relationships so it can give answers, not just results. But Wolfram wants to make the world computable, so that our computers can answer questions like “where is the International Space Station right now. That requires a level of machine intelligence that knows what the ISS is, that it’s in space, that it is orbiting the Earth, what its speed is, and where in its orbit it is right now.

That’s not static data; that’s a combination of computation with knowledge. WolframAlpha does that today, but that is just the beginning.

Search engines aren’t good at that, Wolfram argues, because they’re too messy. Questions in a search engine have many answers, with varying degrees of applicability and “rightness.” That’s not computable, not clean enough to program or feed into a system.

We want to be right,” Wolfram told me. “Making the world computable is a much higher bar than being able to generate Wikipedia-style information … a very different thing. What we’ve tried to do is insanely more ambitious.

It’s so ambitious, and so far-reaching, that it’s hard to describe. Wolfram says that of all the different things he’s done in his life, this is the most horribly complicated to explain. Remember, this is a man who has written on particle physics. It’s both intellectually deep and far-reaching, with many implications — “tentacles,” Wolfram calls them — into different areas of programming and science and knowledge and business.

There’s no good elevator pitch for the language, and even though it’s not entirely released yet, there are 11,000 pages of documentation already. In one of any number of nutshells, however, it’s a giant leap forward in building accessibility to the world’s knowledge, in making programs — and eventually things — smart.

Making the computer do the work
In general, what we’re trying to do is so that as long as a person can describe what they want, our goal is to get that done. A human defines what the goal should be, and a computer does its best to figure out what that means, and does its best to do it,” Wolfram says.

I watched him do it, live.
Countries and flags in South America, thanks to Wolfram language. John Koetsier
In about 30 seconds, Wolfram created a small web application that drew circles on a web page and included a user interface so a visitor could make them bigger or smaller, or change their colors. That’s doable simply because the Wolfram language — with its access to a vast reservoir of knowledge — knows what a circle is and can make it, and it automatically provides web-native user controls to manipulate it. It was a trivial example, but in another 30 seconds, Wolfram built a code snippet that defined the countries in South America and displayed their flags. Then he called up a map of Europe and highlighted Germany and France in different colors computationally, in seconds.

This is only possible because the new Wolfram computational framework includes the complex and precise algorithms developed in over 20 years of Mathematica development, plus the knowledge engine built up inside WolframAlpha.

And the results are shocking.

Automation through information

viernes, 13 de septiembre de 2013

Polina Raygorodskaya de Wanderu recomienda a las emprendedoras aprender a escribir código (programar)

ORIGINAL: Pulso Social
Por Camila Carreño 
Septiembre 13, 2013
Polina Raygorodskaya de Wanderu
Viajó tanto en bus por su primera compañía que a Polina Raygorodskaya se le ocurrió crear Wanderu, la plataforma que permite encontrar y reservar buses y trenes para moverse entre ciudades en el noreste de Estados Unidos. La speaker de Pulsoconf nos dio algunos tips para las emprendedoras.

Polina Raygorodskaya era modelo y su primer emprendimiento fue una compañía de PR para marcas de moda. Estaba en segundo año en Babson College cuando creó Polina Fashion. Pero la startup que ahora la apasiona es Wanderu, que ella co-fundó y donde actualmente es CEO.

Con Wanderu busca mejorar un proceso por el que ella pasó muchas veces: moverse en bus de forma más eficiente. Y no sólo se ahorra tiempo, sino que también destaca que es mucho más sustentable que viajar en auto.
Y al parecer está funcionando, porque recientemente levantaron US$2.45 millones. Polina Raygorodskaya nos explica cuáles son sus planes:

Nuestro objetivo es seguir creciendo y expandiéndonos través de Norteamérica. Ya tenemos más de 13 asociaciones que nos dan 80% de cobertura del mercado del noreste y estamos expandiéndonos activamente región por región a lo largo del país. También estamos contratando y haciendo crecer nuestro equipo técnico para poder seguir desarrollando la tecnología más avanzada en la industria”.

Algunos consejos para las emprendedoras

Ya en el 2007, Polina Raygorodskaya fue elegida por Business Week como parte de los “25 mejores emprendedores de menos de 25“. En 2011 co-fundó Wanderu con Igor Bratnikov (COO) y Eddy Wong (CTO), y en el directorio cuentan con personas clave como Craig Lentzsch, ex CEO de Greyhound –una de las compañías de buses más grandes de Estados Unidos–, y Rogelio De los Santos, partner del fondo Alta Ventures Mexico.

Wanderu fue uno de los primeros equipos en el la aceleradora de PayPal Start Tank en Boston y este año la compañía fue la ganadora del South by Southwest Interactive Accelerator Award.

Hablamos con Polina Raygorodskaya antes de que aterrizara en Guadalajara para Pulsoconf :

En Latinoamérica no hay muchas fundadoras tech, ¿cómo ha sido la experiencia para ti?
–La mayor parte de mi tiempo lo he pasado en Estados Unidos, pero en el tiempo que he pasado en México no he notado ningún tipo de discriminación por ser una mujer que fundó una empresa tech. Incluso en Estados Unidos es un mundo de hombres, la mayoría de los fundadores tech son hombres, pero ha habido una gran tendencia en la última década para que más y más mujeres lancen startups de tecnología. Creo que es un momento muy emocionante para las mujeres interesadas en el emprendimiento y la tecnología.

–¿Cuáles son los principales desafíos para las mujeres en el mundo de los negocios tech? 
 –Creo que uno de los principales desafíos es que hay menos mujeres que hombres que estudian ingeniería, y por eso es más difícil crear una empresa sin ser capaz de construir un producto. Una de las cosas más difíciles para un fundador no técnico es encontrar un co-fundador técnico. A cualquier mujer interesada en crear una startup tech le recomendaría aprender a escribir código. Si no estudiaron programación en la universidad, hay muchos cursos y recursos disponibles específicamente para las chicas que quieren aprender a hacerlo. También hay programas como Codecademy.

–¿Qué le recomendarías a las emprendedoras mujeres que quieren empezar su propia compañía?  
–Mi mayor recomendación es que simplemente lo hagan. Una de las cosas más difíciles es dar el paso, especialmente cuanto tu carrera te está dando dinero. Si encuentras algo que te apasiona y quieres empezar tu propio negocio deberías hacerlo. También creo que es importante si no sabes cómo programar, al menos aprender algo de programación básica. Les ayudará a encontrar un co-fundador técnico y ser capaz de comunicarse con el equipo tecnológico en el futuro. Si estás construyendo una empresa de tecnología al menos deberías entender lo básico de la tecnología que está usando para construirla.

–¿Qué opinas del ecosistema latinoamericano de startups? ¿Es un mercado interesante para tu compañía? 

–Creo que América Latina es un mercado en auge y hay un montón de oportunidades para aprovechar en este momento. Estamos muy interesados y entusiasmados en el mercado de América Latina, especialmente México.

Sigue las novedades de Polina Raygorodskaya en twitter (@polinatravels) y no te pierdas su charla en Pulsoconf.

[Imagen Destacada]

About Camila Carreño Camila Carreño es periodista. Ha trabajado en el diario El Mercurio en temas de política, en la Universidad Católica en materia de políticas públicas y como editora sobre emprendimiento digital en Chile. Síguela en Twitter: @camicarreno.
View all posts by Camila Carreño ?

jueves, 25 de abril de 2013

Bioengineers Build Open Source Language for Programming Cells

ORIGINAL: Wired
04.19.13

Image: Steve Jurvetson/Flickr.
Drew Endy wants to build a programming language for the body. 

Endy is the co-director of the International Open Facility Advancing BiotechnologyBIOFAB, for short — where he’s part of a team that’s developing a language that will use genetic data to actually program biological cells. That may seem like the stuff of science fiction, but the project is already underway, and the team intends to open source the language, so that other scientists can use it and modify it and perfect it. 

Photo: BIOFAB
The effort is part of a sweeping movement to grab hold of our genetic data and directly improve the way our bodies behave — a process known as bioengineering. With the Supreme Court exploring whether genes can be patented, the bioengineering world is at crossroads, but scientists like Endy continue to push this technology forward. 

Genes contain information that defines the way our cells function, and some parts of the genome express themselves in much the same way across different types of cells and organisms. This would allow Endy and his team to build a language scientists could use to carefully engineer gene expression – what they callthe layer between the genome and all the dynamic processes of life.” 

According to Ziv Bar-Joseph, a computational biologist at Carnegie Mellon University, gene expression isn’t that different from the way computing systems talk to each other. You see the same behavior in system after system. “That’s also very common in computing,” he says. Indeed, since the ’60s, computers have been built to operate much like cells and other biologically systems. They’re self-contained operations with standard ways of trading information with each other. 
In synthetic biology, the equivalent of a Java virtual machine might be that you could create your own compartment in any type of cell, so your engineered DNA wouldn’t run willy-nilly.
— Drew Endy 

The BIOFAB project is still in the early stages. Endy and the team are creating the most basic of building blocks — the “grammar” for the language. Their latest achievement, recently reported in the journal Science, has been to create a way of controlling and amplifying the signals sent from the genome to the cell. Endy compares this process to an old fashioned telegraph

If you want to send a telegraph from San Francisco to Los Angeles, the signals would get degraded along the wire,” he says. “At some point, you have to have a relay system that would detect the signals before they completely went to noise and then amplify them back up to keep sending them along their way.” 

And, yes, the idea is to build a system that works across different types of cells. In the 90s, the computing world sought to create a common programming platform for building applications across disparate systems — a platform called the Java virtual machine. Endy hopes to duplicate the Java VM in the biological world. 

Java software can run on many different hardware operating system platforms. The portability comes from the Java virtual machine, which creates a common operating environment across a diversity of platforms such that the Java code is running in a consistent local environment,” he says. 

In synthetic biology, the equivalent of a Java virtual machine might be that you could create your own compartment in any type of cell, [so] your engineered DNA wouldn’t run willy-nilly. It would run in a compartment that provided a common sandbox for operating your DNA code.” 

According to Endy, this notion began with a group of students from Abraham Lincoln High School in San Francisco a half decade ago, and he’s now calling for a commercial company to recreate Sun Microsystems’ Java vision in the biological world. It’s worth noting, however, that this vision never really came to fruition — and that Sun Microsystems is no more. 

Nonetheless, this is what Endy is shooting for — right down to Sun’s embrace of open source software. The BIOFAB language will be freely available to anyone, and it will be a collaborative project. 

Progress is slow — but things are picking up. At this point, the team can get cells to express up to ten genes at a time with “very high reliability. A year ago, it took them more than 700 attempts to coax the cells to make just one. With the right programming language, he says, this should expand to about a hundred or more by the end of the decade. The goal is to make that language insensitive to the output genes so that cells will express whatever genes a user wants, much like the print function on a program works regardless of what set of characters you feed it. 

What does he say to those who fear the creation of Frankencells — biological nightmares that will wreak havoc on our world? “It could go wrong. It could hurt people. It could be done irresponsibly. Assholes could misuse it. Any number of things are possible. But note that we’re not operating in a vacuum,” he says. “There’s history of good applications being developed and regulations being practical and being updated as the technology advances. We need to be vigilant as things continue to change. It’s the boring reality of progress.” 

He believes this work is not only essential, but closer to reality than the world realizes. “Our entire civilization depends on biology. We need to figure out how to partner better with nature to make the things we need without destroying the environment,” Endy says. “It’s a little bit of a surprise to me that folks haven’t come off the sidelines from other communities and helped more directly and started building out this common language for programming life. It kind of matters.

sábado, 2 de febrero de 2013

Life, the Universe, and Everything: An Interview with David Haussler

ORIGINAL: PLOS GENETICS
Jane Gitschier
January 31, 2013

David Haussler. Photograph by Ron Jones, courtesy of the Center for Biomolecular Science and Engineering, University of California Santa Cruz.doi:10.1371/journal.pgen.1003282.g001
Citation: Gitschier J (2013) Life, the Universe, and Everything: An Interview with David Haussler. PLoS Genet 9(1): e1003282. doi:10.1371/journal.pgen.1003282

Copyright: © 2013 Jane Gitschier. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Among the pantheon of computer scientists who have framed our capacity to interpret DNA sequences stands David Haussler of the University of California, Santa Cruz (UCSC). Applying his prowess in computer learning theory to the problems of protein modeling and gene structure prediction, Haussler emerged in the mid-1990s as a trail-blazer in the field of computational biology. He came to wider prominence in 2000 during the frenetic race to produce a draft sequence of the human genome by nucleating an impassioned team of coders and engineers who assembled the sequence data and launched the UCSC Genome Browser. Fittingly, his team's contribution made manifest the vision of Robert Sinsheimer, who as Chancellor of UCSC in 1985 convened a pivotal workshop to explore sequencing the human genome.

Haussler (Image 1) now plays, by my count, at least half-a-dozen leadership roles, including co-director of the Genome 10 K project, coordinating committee member of The Cancer Genome Atlas project, and director of the Center for Biomolecular Science and Engineering at UCSC. He is easily spotted by his predilection for Hawaiian shirts, whose informality, he suggests, fosters inter-disciplinary collaboration. Indeed, Haussler's ken for machine learning and his quest for the meaning of life are so expansive that I was tempted to title this piece “Deep Thought”, a nod to the fictional computer in Douglas Adams' The Hitchhiker's Guide to the Galaxy, but chose a more subdued allusion instead.

I located Haussler on the upper reaches of the stunning UCSC campus in the engineering building, a sleek structure of glass and aluminum, tucked into a redwood grove that was still dripping and fragrant from the morning's rain. The anteroom to his modest office was decorated with handsome prints from UCSC's scientific illustration program as well as books on the genome project, and a box labeled “for the intron lounge” was piled high with journals. Haussler swept in via bicycle, swiftly signed a few documents, and downed a cold drink as we began with a discussion of his growing up in the town of North Hills in the San Fernando Valley.

Haussler: My dad went to Caltech and because of the economic pressures of having a young family, decided not to pursue pure science, but to pursue a professional position in structural engineering. He worked on mathematical problems as a hobbyist and had a love of pure science. Both my brother and I ended up living out his dream to be a scientist. My brother is a highly accomplished biochemist.

Gitschier: I saw that your first paper in the early '70s was with a Haussler and had assumed it was your father, but then, looking at his picture, I realized he must be your sibling.

Haussler: My only sibling is my brother. He was professor of biochemistry in University of Arizona and taught me how to do science. And he is really one of the leading scientists in the world on vitamin D, which was the subject of that first paper.

Gitschier: How much older is he?

Haussler: Twelve years.

Gitschier: So he was established when you were just a kid.

Haussler: Right. The summer after my freshman year [in college], I spent time in his lab. Every third week, I would sacrifice a chick that was raised without vitamin D. I would take out its intestines for receptors for the hormonal form of vitamin D, and we used those receptors in a radio-receptor competitive binding assay to first measure the level of the hormonal form of vitamin D in the human bloodstream, in both normal and diseased humans. By the end of the summer, we had a paper in Science! You know, big breakthrough.

Then I went back the next summer, and nothing worked. I remember my brother saying to me, “Now, this is how science really is.” But I was undaunted.

Gitschier: Let's talk about your transition to science, because I know your first college experience was in art.

Haussler: I did visual art mostly. Acrylic painting and metal sculpture were probably my favorites, although I did stone lithography and all kinds of fabulous things in the San Francisco Academy of Art. Then, I switched schools and into psychology.

Gitschier: And that was where?

Haussler: That was actually at a crazy little experimental college. You have to understand that this was the early '70s…

Gitschier: I do understand! [Haussler and I were born the same year.]

Haussler: My mother was hoping I'd go to UCLA, but I was a rebel and said “No, I want to go to a crazy place,Immaculate Heart College [IHC] in Hollywood.

Gitschier: Immaculate Heart doesn't sound so “crazy” on the surface.

Haussler: It doesn't, not at all, but the thought leader there was Sister Corita Kent, and you remember from the '60s, those love posters? A lot of the art movement and the philosophy that was expressed in art and posters in that era actually came out of Sister Corita Kent and a number of other rebels. The sisters at IHC were essentially kicked out of the Catholic Church for being radicals, and they had an extremely experimental college. So I, being the contrarian I was, applied there. It was strong in art and music and psychology. We studied Fritz Perls and Carl Rogers and all of these self-realization psychology thinkers at the time. And I was extremely into that. We had intensive encounter groups and dug very deeply into personal interactions.

Gitschier: But you didn't stick with Immaculate Heart.

Haussler: I got interested in science by working with my brother. I then transferred to Connecticut College back east. Again, I liked very intimate, individual learning. This was part of my whole psychology background. I view essential human progress being made, including learning, within a very intensive, one-on-one or small group interaction.

Gitschier: When you went there, you knew you wanted to do math?

Haussler: Yes. During those two summers with my brother, the one thing that mattered most was not the wet lab experiments that I had done, but when it came to analyzing the data. Someone in the lab was showing concentration in relation to a radioactive response curve and trying to fit that data with a linear function. And I said, “Well you can't use linear regression on this until you transform the variables.” And they looked at me and said, “Can you do that?”

And then I realized, hey wait a minute, I can contribute on the math side and it's a lot more fun than grinding up chicken guts! I like the quote that “mathematics is the queen of sciences” [attributed to Gauss]. Mathematics is the beautiful unity in the universe, and that's what totally captivated me.

Gitschier: Then, you find yourself at the University of Colorado doing PhD work in computer science. That seems like a logical transition to me.

Haussler: Logical is the correct word. After studying pure mathematics as an undergrad, I decided that the foundation for everything was logic. And I read extensively before I went to graduate school, but even after getting my undergraduate degree in mathematics and a minor in physics, I still hadn't decided to pursue a life of science.

Gitschier: What were you thinking of—art, philosophy, psychology?

Haussler: I wanted to get at the heart of the meaning of life.

Gitschier: Wow. [I had to swallow the answer, “42”.]

Haussler: Still this rebel spirit, I guess. I wasn't convinced that I would find that at traditional institutions. I spent about nine months wandering around Europe and then settled in San Luis Obispo on the family farm, kind of between generations. My grandfather was aging and my father was active as an engineer, so there was no one to take care of it.

While I was there, I wanted to keep touch with my intellectual side, so my friends and I—it was almost like a commune—believed in working hard on the ranch during the day and then reading and discussing philosophy, history, literature, and psychology at night.

Gitschier: Who were these people that you recruited to the farm?

Haussler: Well, important people that I met in my life and in my travels. We read books and had wonderful discussions. I remember my favorite title was The Origin of Consciousness in the Breakdown of the Bicameral Mind. We were trying to build a non-traditional intellectual environment.

But size is a factor there. What was missing at that time was the Internet. There was no way to get in touch with other people who had very specific interests except through the library and through post. So it became a 19th century gentleman-scholar kind of activity, which has very limited impact.

Gitschier: What happened to the farm after you left?

Haussler: My father did retire there. He and my mother had a spectacular retirement, raising organic fruit and selling it at the farmers market. So I played an important role in the family; I was the bridge to that retirement and it allowed me close friendship and think time.

Gitschier: And what firm had your father worked for?

Haussler: Oh, in my family, we never worked for anybody else! Robert Haussler Structural Engineering!

Gitschier: I see. It was a tradition!

Haussler: My great grandfather, my grandfather, my father always ran their own businesses. Never had a boss. It was a crazy, fierce, independent kind of tradition.

Gitschier: So this was instilled in you very early. I'm now seeing the fuller context!

Haussler: Right. I wasn't going to play along with any institutional programs! Those were the days when you could be anti every institution and get away with it.

Well, I look back at my writings from that time and there was some very creative stuff but isolated from the bulk of the intellectual mainstream, it's very hard to make progress. So I was thrilled to get re-engaged, just by taking advanced math classes at Cal Poly [San Luis Obispo].

Applied mathematics was my major, but I took computer science classes as well. I seized on the question of what is computable. What can be formalized by mathematics? And the answer, according to Alan Turing, was that this is the same as what can be computed on a very simple kind of machine. I was tremendously taken by that and by the fact that Turing and Kurt Gödel had established that there were things that were fundamentally uncomputable; true but unprovable. It appealed to my mystical side. I was always interested in the unity of the universe and the mystery of it.

Gitschier: Are you still?

Haussler: I still am in many ways. The mystery of “why life” and “is there a mathematical inevitability that there will be life” are questions that I spend quite a bit of time thinking about. I don't write much about them because I'm engaged in areas that are more immediately applied and have urgent impact, but I think a lot about them.

And there's a theme in my thinking and in my life that has been constant since those days as a young adult searching for answers. I turned away from thinking about that as a humanistic quest—to understand my psychology and our interactions—into an absolute quest for knowledge about the universe. In a sense that is the one thread that unites my entire adult life because I've been in so many different scientific areas.

But life itself has always been something that fascinated me, life in the broadest sense, that spans everything from the actual biological life that we observe on this planet, to the abstract notion of life. Like in Conway's Game of Life where you have a disarmingly simple mathematical system that nevertheless is sufficiently complex that it is naturally an incubator of self-reproducing patterns; you start with a random pattern, and you will have emergent forms that will be self-replicating entities that interact, as in living systems.

miércoles, 24 de octubre de 2012

Training Your Robot the PaR-PaR Way - Berkeley Lab and JBEI Researchers Develop a Biology-Friendly Robot Programming Language


Berkeley Lab and JBEI Researchers Develop a Biology-Friendly Robot Programming Language

OCTOBER 23, 2012
Lynn Yarris (510) 486-5375 lcyarris@lbl.gov



Feature

Teaching a robot a new trick is a challenge. You can’t reward it with treats and it doesn’t respond to approval or disappointment in your voice. For researchers in the biological sciences, however, the future training of robots has been made much easier thanks to a new program called “PaR-PaR.”

Nathan Hillson, a biochemist at the U.S. Department of Energy (DOE)’s Joint BioEnergy Institute (JBEI), led the development of PaR-PaR, which stands for Programming a Robot. PaR-PaR is a simple high-level, biology-friendly, robot-programming language that allows researchers to make better use of liquid-handling robots and thereby make possible experiments that otherwise might not have been considered.

The syntax and compiler for PaR-PaR are based on computer science principles and a deep understanding of biological workflows,” Hillson says. “After minimal training, a biologist should be able to independently write complicated protocols for a robot within an hour. With the adoption of PaR-PaR as a standard cross-platform language, hand-written or software-generated robotic protocols could easily be shared across laboratories.



Hillson, who directs JBEI’s Synthetic Biology program and also holds an appointment with the Lawrence Berkeley National Laboratory (Berkeley Lab)’s Physical Biosciences Division, is the corresponding author of a paper describing PaR-PaR that appears in the American Chemical Society journal Synthetic Biology. The paper is titled “PaR-PaR Laboratory Automation Platform.” Co-authors are Gregory Linshiz, Nina Stawski, Sean Poust, Changhao Bi and Jay Keasling.

Using robots to perform labor-intensive multi-step biological tasks, such as the construction and cloning of DNA molecules, can increase research productivity and lower costs by reducing experimental error rates and providing more reliable and reproducible experimental data. 

To date, however, automation companies have targeted the highly-repetitive industrial laboratory operations market while largely ignoring the development of flexible easy-to-use programming tools for dynamic non-repetitive research environments. As a consequence, researchers in the biological sciences have had to depend upon professional programmers or vendor-supplied graphical user interfaces with limited capabilities.

The PaR-PaR development team included (from left) Nina Stawski, Changhao Bi, Nathan Hillson, Sean Poust and Gregory Linshiz. (Photo by Roy Kaltschmidt)
Our vision was for a single protocol to be executable across different robotic platforms in different laboratories, just as a single computer software program is executable across multiple brands of computer hardware,” Hillson says. “We also wanted robotics to be accessible to biologists, not just to robot specialist programmers, and for a laboratory that has a particular brand of robot to benefit from a wide variety of software and protocols.

Hillson, who earlier led the development of a unique software program called “j5” for identifying cost-effective DNA construction strategies, says that beyond enabling biologists to manually instruct robots in a time-effective manner, PaR-PaR can also amplify the utility of biological design automation software tools such as j5.

Before PaR-PaR, j5 only outputted protocols for one single robot platform,” Hillson says. “After PaR-PaR, the same protocol can now be executed on many different robot platforms.

The PaR-PaR language uses an object-oriented approach that represents physical laboratory objects – including reagents, plastic consumables and laboratory devices – as virtual objects. Each object has associated properties, such as a name and a physical location, and multiple objects can be grouped together to create a new composite object with its own properties.
PaR-PaR makes it much easier to train robots to perform labor-intensive multi-step biological tasks. (Photo by Roy Kaltschmidt)
Actions can be performed on objects and sequences of actions can be consolidated into procedures that in turn are issued as PaR-PaR commands. Collections of procedural definitions can be imported into PaR-PaR via external modules.

A researcher, perhaps in conjunction with biological design automation software such as j5, composes a PaR-PaR script that is parsed and sent to a database,” Hillson says. “The operational flow of the commands are optimized and adapted to the configuration of a specific robotic platform. Commands are then translated from the PaR-PaR meta-language into the robotic scripting language for execution.

Hillson and his colleagues have developed PaR-PaR as open-source software freely available through its web interface on the public PaR-PaR webserver http://parpar.jbei.org.

Flexible and biology-friendly operation of robotic equipment is key to its successful integration in biological laboratories, and the efforts required to operate a robot must be much smaller than the alternative manual lab work,” Hillson says. “PaR-PaR accomplishes all of these objectives and is intended to benefit a broad segment of the biological research community, including non-profits, government agencies and commercial companies.

This work was primarily supported by the DOE Office of Science.

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JBEI is one of three Bioenergy Research Centers established by the DOE’s Office of Science in 2007. It is a scientific partnership led by Berkeley Lab and includes the Sandia National Laboratories, the University of California campuses of Berkeley and Davis, the Carnegie Institution for Science, and the Lawrence Livermore National Laboratory. DOE’s Bioenergy Research Centers support multidisciplinary, multi-institutional research teams pursuing the fundamental scientific breakthroughs needed to make production of cellulosic biofuels, or biofuels from nonfood plant fiber, cost-effective on a national scale. For more, visit www.jbei.org

Lawrence Berkeley National Laboratory addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science. For more, visit www.lbl.gov.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit the Office of Science website atscience.energy.gov/.

Additional Information

The ACS Synthetic Biology paper “PaR-PaR Laboratory Automation Platform,” by Hillson, et. al., can be viewed and downloaded here

The PaR-PaR software is also available at https://github.com/jbei/parpar

To learn more about the j5 DNA construction software visit the j5 Website athttp://j5.jbei.org/