Cells that fire together wire together” and Stanford Media X

That is the goal of Stan­ford Uni­ver­si­ty Media X: to fos­ter deep col­lab­o­ra­tions between indus­try and acad­e­mia, as high­light­ed in Busi­ness Week’s recent arti­cle The Vir­tu­al Meet­ing Room. The 5th Annu­al Media X Con­fer­ence on Research, Col­lab­o­ra­tion, Inno­va­tion and Pro­duc­tiv­i­ty served its pur­pose well for the last cou­ple of days: very fun and insight­ful pre­sen­ta­tions by Stan­ford researchers (and a few exter­nal experts) and a great list of par­tic­i­pants to get to know.

No doubt, a great source of men­tal stim­u­la­tion for all of us. Charles House, Media X’s Exec­u­tive Direc­tor, framed the dia­logue as an effort to gen­er­ate the right ques­tions and then engage the best minds in answer­ing them.

Some of (my) main take-aways

  • The world does not come to us as neat dis­ci­pli­nary prob­lems, but as com­plex inter­dis­ci­pli­nary chal­lenges” (great quote by Dean John Hen­nessy)
  • Per­son­al Robot­ics is poised to explode soon-and soft­ware will be key (pre­dict­ed by Paul Saffo)
  • An incon­ve­nient truth: Al Gore had to be con­vinced to bring his pre­sen­ta­tion into a movie, since he was very attached to each and every of his X hun­dred slides. We are hap­py it happened!
  • Neu­ro­sci­en­tists know what pat­terns in the brain indi­cate cer­tain inten­tions-and are start­ing to use tech­nolo­gies to help immo­bi­lized patients com­mu­ni­cate with exter­nal devices based mere­ly on their thoughts
  • We need to learn to embrace change- a lot of it is coming!

Now, some key points from sev­er­al pre­sen­ta­tions (there were more than these, but I could­n’t attend all). I encour­age you to vis­it the web­site of each pre­sen­ter if you are inter­est­ed in learn­ing more about that topic.

a. Paul Saf­fo on Inno­va­tion

  • It usu­al­ly takes 20 years since basic sci­ence until appli­ca­tions reach inflec­tion point and take the world by storm
  • Next big thing: per­son­al robot­ics. Indi­ca­tors: DARPA spon­sored first attempts in mid-80s, and now we have appli­ca­tions such as the Room­ba vac­u­um-clean­er, and Stan­ford rac­ing car team (see below). The key is the soft­ware man­ag­ing the hardware.
  • Pay atten­tion to how you feel about change. Embrace change. Learn that change means opportunity

b. Scott Z. Burns, co-pro­duc­er of An Incon­ve­nient Truth

  • Gore was reluc­tant, but he was con­vinced to accel­er­ate learn­ing giv­en the increas­ing threat of glob­al warming.
  • The pow­er of analo­gies: in order to find the right for­mat for the movie, they were inspired by Scorce­se’s The Last Waltz
  • Goal of the movie: Al Gore saw an anal­o­gy between the movie and a bio-feed­back device that her daugh­ter used to treat her migraines. In biofeed­back, one learns how to man­age vital body vari­ables (such as Heart Rate Vari­abil­i­ty) in order to reach a goal (pre­vent­ing migraines, man­ag­ing stress…). Sim­i­lar­ly, Gore want­ed each view­er to find his or her own “levers” or “mus­cles” and ways to act ‑not just be told what to do. This is why the movie focus­es more on describ­ing the sit­u­a­tion than on propos­ing solutions.
  • The only act­ing advice to Gore was “think of this pre­sen­ta­tion as your last presentation”.
  • The movie’s bud­get was $1.5m. It was risky movie, in terms of the sub­ject and the for­mat, that has paid off very well.

c. Prof. Lau­ra L. Carstensen, on the Stan­ford Cen­ter on Longevity

  • Tech­nol­o­gy & Sci­ence has been improv­ing Biol­o­gy for the last 150 years, and now we need to focus on how to help peo­ple remain phys­i­cal­ly fit and men­tal­ly sharp as we age
  • We need to rede­fine “aging”. Nowa­days, there are many role mod­els in their 70s and 80s that show how age is not an obsta­cle for being active con­trib­u­tors in society

d. Prof. Krish­na Shenoy on Brain Com­put­er Interfaces

  • Prob­lem: many peo­ple can’t move/ communicate
  • Solu­tion: trans­late brain sig­nals into con­trol sig­nals, by implant­i­ng elec­trodes in brain that mea­sure sig­nals (action poten­tials) and help pre­dict behav­iors based on response pat­tern recognition
  • There are already appli­ca­tions today that help mon­keys and humans move cur­sors based on their thoughts

e. Dr. LeRoy Hein­richs on Vir­tu­al Sim­u­la­tions for med­ical education

  • Sim­u­la­tions work very well to train sur­geons and oth­er med­ical pro­fes­sion­als learn how to per­form their jobs.
  • Vir­tu­al sim­u­la­tions (in a sim­u­lat­ed vir­tu­al envi­ron­ment) can work as well as phys­i­cal ones (which typ­i­cal­ly are more expen­sive and less scalable)

f. Prof. Robert Sut­ton on run­ning Orga­ni­za­tions (see his blog)

  • Treat your orga­ni­za­tion as an unfin­ished pro­to­type: as a leader, you need to act on your best knowl­edge right now, while doubt­ing what you know
  • Data-based deci­sion-mak­ing is key: Yahoo Strate­gic Data Ser­vices con­ducts over 20 con­trolled exper­i­ments per day
  • Yet, even if you are learn­ing all the time, you need to act with total con­vic­tion, or peo­ple won’t follow.

g. Prof. Gilbert M. Mas­ters on Green Build­ing and Green Cars

  • He rec­om­mends read­ing “It’s the Archi­tec­ture, Stu­pid!” to under­stand how build­ings account for 35–45% car­bon emis­sions in the US, more than trans­porta­tion and indus­try (each)
  • Rank­ing of main sources of pol­lu­tion in the “build­ing” cat­e­go­ry: res­i­den­tial space heat­ing, com­mer­cial light­ing, res­i­den­tial water heating
  • Inter­est­ing ini­tia­tives: Stan­ford Green Dorm Project and Tes­la Motors

h. Prof. Ken­neth Sal­is­bury on Per­son­al Robotics

  • There are robots today with great motor dexterity‑i.e., they can unload a dishwasher
  • The sec­tor needs to cre­ate and build on an open-source plat­form, to avoid mul­ti­ple frag­men­tary efforts that pre­vent faster progress for the field as a whole

i. Prof. Sebas­t­ian Thrun, on the DARPA Urban Challenge

  • The Stan­ford Rac­ing Team won the 2005 DARPA Chal­lenge and is get­ting ready for The Urban Chal­lenge (Novem­ber 3rd, 2007), where their ful­ly autonomous car will need to dri­ve in a ful­ly urban environment
  • This requires more sophis­ti­cat­ed soft­ware, mov­ing from per­cep­tion to Under­stand­ing (object detec­tion, pre­dic­tion, interaction)
  • Pre­dict­ed time­line for ful­ly autonomous dri­ving: mil­i­tary vehi­cles in 2015, civ­il cars by 2030

j. Prof. B.J. Fogg on how email “cheap­ens our lives”

  • Main­tain­ing close rela­tion­ships is crit­i­cal for happiness
  • Email is a very bad tool to man­age close relationships
  • Tips: draw a map of your key rela­tion­ships; share emo­tions often; know oth­er peo­ple’s details; just hang out; give gifts with shared mean­ing; remem­ber to use ALL media, not just emails
  • Yack­Pack: “walkie-talkie” wid­get for web­sites to help peo­ple com­mu­ni­cate via voice

k. Prof. Roy D. Pea on Inno­va­tions in Learning

  • There is an increas­ing need for DIY videos in pro­to­col shar­ing among sci­en­tists, so they can bet­ter repli­cate experiments
  • Lab is cre­at­ing new ways to enable peo­ple cre­ate con­ver­sa­tions ABOUT video to enhance diver­si­ty of views and connections

l. Stu­art Gannes on the Dig­i­tal Vision Fel­low­ship Program

  • Brij Kothari: large ini­tia­tive in India to fos­ter lit­er­a­cy by intro­duc­ing same lan­guage sub­ti­tles in TV programs.
  • Adam Tol­nay: design­ing games in cell phone to improve teenage finan­cial lit­er­a­cy, to help pre­vent mis­takes with cred­it cards that may cost as much as 200 points in cred­it scoring.

m. Prof. Brigid Bar­ron on suc­cess­ful group dynamics

  • The key fac­tor seems to be how to man­age Attention
  • Both suc­cess­ful and unsuc­ces­sul groups gen­er­ate a sim­i­lar amount and qual­i­ty of proposals
  • But only suc­cess­ful ones respond pos­i­tive­ly to good pro­pos­als and main­tain con­tin­u­ous shared atten­tion until the prob­lem is solved
  • (Which means maybe brain­storm­ing is over­rat­ed by now?)

n. Prof. Dan Schwartz on new meth­ods for learn­ing out­side the classroom

  • Games help merge for­mal & infor­mal learning
  • Teach­able agents are com­put­er pro­grams cre­at­ed by stu­dents to make their knowl­edge explic­it, and can be used as part of games to moti­vate stu­dents do their homework

o. Prof. Jere­my Bailen­son on Vir­tu­al Worlds

  • Our dig­i­tal iden­ti­ties (avatars, pro­files…) don’t just reflect us: they shape us. Our choic­es have consequences

p. Prof. Paul Brown on 3D Sci­en­tif­ic Imaging

  • There are new imag­ing and soft­ware pack­ages that allow doc­tors nav­i­gate vir­tu­al­ly into the bod­ies of patients, in a non-inva­sive way
  • The images are sim­ply spectacular.
  • They used these tech­nolo­gies to see in detail the inte­ri­ors of an Egypt­ian mummy

Which of these top­ics are more inter­est­ing to you? Just let us know and we will do a fol­low-up arti­cle. Enjoy!


  1. Randy Bryan on April 25, 2007 at 7:19

    Great arti­cle! Thanks for sub­mit­ting it to my blog car­ni­val at:


    Randy Bryan

  2. Dr. Pam on February 16, 2008 at 7:45

    Thank you!! Great site, pro­duc­tive links, nice range of dif­fer­ent top­ics. Like I said, Thank you!!

  3. Alvaro on February 17, 2008 at 10:01

    Thank you for your visit!

About SharpBrains

SHARPBRAINS is an independent think-tank and consulting firm providing services at the frontier of applied neuroscience, health, leadership and innovation.
SHARPBRAINS es un think-tank y consultoría independiente proporcionando servicios para la neurociencia aplicada, salud, liderazgo e innovación.

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