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Futuristic Design Names


[music playing] richard devaul:the actual moonshot is wonderful, inspirational,poetic, beautiful, involved, great technical challenges,genuine heroism-- it brought the world together. but think about thepolynesian islander, on a dugout canoe,deciding one day they were going to go that way. no one had ever beenthat way before.

no one even knew if there wasanything that way, before. it was amazing. and it changed the world. astro teller: peoplecan set their minds to magical, seeminglyimpossible ideas. and then, throughscience and technology, bring them to reality. and that, then setsother people on fire. then other thingsthat look impossible

might be accomplishable. john f. kennedy(voiceover): many years ago, the great britishexplorer, george mallory, who was to die onmount everest, was asked, why did hewant to climb it? he said, because it is there. richard devaul: everyoneelse in the world is working on that next 10%. if you could be the onethat delivers that 10 times

improvement, you have a chanceto really change things. astro teller(voiceover): if you want cars to run at 50miles per gallon, fine, you can retool yourcar a little bit. but if i tell you it hasto run on a gallon of gas for 500 miles, youhave to start over. megan smith: you need a lotof courage in this work, and you need a lotof persistence. even if you don'treally, 100% believe

it's possible-- likeyou might think, this might be possible--have the courage to try. that's how the greatestthings have happened. astro teller: you don't spendyour time being bothered that you can't teleport fromhere to japan, because there's a part of you thatthinks it's impossible. moonshot thinking is choosingto be bothered by that. john f. kennedy(voiceover): we choose to go to the moonin this decade,

and do the other things. not because they are easy,but because they are hard. richard devaul:humanity's progress has been a series ofamazing audacious things, from the verysmall and personal, up to the great, big and grand. and we are a speciesof moonshots. and to me, that's likethe really amazing, poetic inspirational thing.

megan smith: when you find yourpassion, you're unstoppable. you can make amazingthings happen. it's been true throughall of history. when kennedy said that wewould put a man on the moon, it's about thefact that he said, we don't know howto do this yet, and we're going to do it anyway. and that sends chillsup everybody's spine. because if that happens,what couldn't we do?

megan smith: welcome tosolve for x. i'm megan smith, and this is-- [applause] i have a fan down there. and puneet ahira. and when we started solve forx, the idea of it-- actually, the original crazy idea wasthat when we had begun google x, we were looking for projects. and we were going to havea conference to brainstorm.

and so we started thinkingabout the conference. and then we had way toomany ideas for google x, and there was no waywe could do anymore. but we decided to stillhave the conference. and the reason for that is,there is extraordinary people all around the world. and there always have been. who just are inspired, andtaking these moonshots, and really trying to make theworld better, in radical ways.

and many of themare techies like us. and so we wanted to have a placewhere we can celebrate people who are in the middle of trying. not when they're in historybooks later, because they get celebrated. but in the middle of trying. you know that moment for like,elon musk-- i don't know, about five years ago, whenpeople were like the rockets are blowing up.

tesla, how is itgoing to make money? you know, that justno one believed. and he needed help then. and i feel like those arethe people that solve for x are really about. we call them thesemoonshot pioneers. and the structure of amoonshot, in our mind, of a tech moonshot, is reallycharacterized by these three circles.

there's some kind of problem inthe world, or opportunity that really would affecta lot of people, that someone's identified. there's some kind ofbreakthrough technology. it might sound like sciencefiction, but it's available. or some new wayof doing something that we already knowwell, in the tech area. and they've got a radicalsolution, a product or service, or way, that actuallycould scale in the world.

so even if you took somethinglike a self driving car. the problem is, of course,you know, billions of people wasting time in traffic. safety. texting and driving. all those kinds of issues--fuel efficiencies-- a really seriousproblem worth solving. the breakthroughtechnology today, are things like real timesensors, the level of mapping

we have, kind of robotics, etcetera-- that would allow us to, in a radical way,have a car drive itself, in the current system. not some kind of special route. so that's the moonshotof the self driving car. so today, we're going to hearfrom four extraordinary teams. the first one isactually a team of 10, so it's five amazingpeople who have moonshots. and the format is the following,you want to tell the format?

yeah, sure. so we're going tohave each of them come up on stage, present their10 minute proposal to you, which goes through this format,of what they're working on, what their breakthrough idea is,and how they're going to do it. and then after wehear from all of them, what we're going to do is, inthese tables that you guys are sitting in, to do an interactivebrainstorming session-- we borrowed thisconcept from improv,

spend two-thirds ofyour time thinking, 'yes, and what else could wedo?' what resources can we provide? what people could we connectthese moonshot pioneers to, that are really going toaccelerate how quickly they can get this out in the world? and then, spendsome of the time-- a third of the time doing 'yes,but.' does the math add up? is the physics right?

does this make sense? what are maybe some of theblind spots or questions that might not havebeen asked before? so we'll do that forabout 25 minutes, and then have each of the groupscome back, and report out. and it's actually themost fun, interesting part of this session-- wherewe get an explosion of different directions andideas, that come out of this. megan smith: and the thing aboutit is, that you may be like,

oh my god, i don't knowanything about these topics. but the best ideas--sometimes on your table, there is going tobe somebody who's a super expert of the topic, andsomebody who's knows nothing. and that mix is wherewe get the best ideas. and so, we'll haveenough so that we'll have two tables per idea. and they're bringingmore chairs. they said they'd be herein about 5 or 10 minutes.

so we'll make anothertable back there. so that's the plan. and thanks for being here. and then, we'llcome do report outs. so, we want to get started. it's a bit-- the style is kindof like a short ted-like talk, these guys aregoing to do, to make this proposal in the format. puneet ahira: we have sara,who's joining us right now,

who's going to talk to us abouther vision of how to make food globally cheap and abundant. and we've beenworking with-- do you want to come up and get set up? we've been working with sarafor the last few months, and have been so excitedabout all of the progress that she's made. and so we're soexcited that she's been able to fly overhere from nairobi, to be

able to share thisstory with you. and hopefully, they'llbe areas for you guys to collaborate with, withthis project, as well. megan smith: whileshe's setting up-- one of the things that'sinteresting in solve for x, we've done-- we do a summit with18 proposals every february, and then we've 10 ofthese mini events. one at congress actually,which was great, to try to get them moving onproposals, and stop arguing.

so, one of the areas thatwe're always looking for, because it's 10%of gdp of countries is agricultural breakthroughs. and so, it wasgreat to find sara. sara menker: and actually,i have a gift for every one. so i want you guysto pass this around and, just takeone tortilla chip. you've not allowed tohave more than one. and don't eat it.

sorry. it'll defeat the purpose ofwhat i'm trying to achieve. i guess, as it'sbeing passed around, i want you guys to havethat tortilla chip as a way to contextualizethe conversation, i want us all to have. but you know, show ofhands, just for the sake of show of hands, who hasa smartphone of any kind? 100% of the room.

so a decade ago, smartphonesthat we have today, with the functionalitythat we have, would have been over twotimes expensive, if not more. so we've managed to half theprice of the devices we use. the tortilla chip,in your hand however, has gone up by twoand a half times. so the one thing we need tolive with, and survive with, is the one thing that we'vemanaged to not solve for. and how expensive food hasgotten and will continue

to get, is a veryscary proposition. so by way of background,i'm ethiopian. i was raised inethiopia in the 80s, at the peak of the food crisis. so my natural transition wasto become a commodities trader on wall street. now, in 2008,there was something that happened in thecommodities markets. oil hit $150, and globalfood prices and grain prices

hit what was an all time high. at that point intime, i freaked out. and my freaking out wasreally driven by a fear that 20 years downthe line, there's no way we're going to be ableto afford food, personally. so i just kind of developed anobsession around agriculture. i was tradingenergy at the time, so there wasn't areason why i should be obsessed with this problem,other than i knew the markets.

and that obsession eventuallyled me to quit my job in 2012, to go down this pathof trying to help make food cheap and abundant. now when i left, it wasthe beginning of 2012, and what i didn't knowwas later that year, we'd hit new highsin grain prices. and little did i know thatthe country i had chosen to move to, which waskenya-- so i left new york, and moved to kenya-- would behit particularly hard by it.

see, what happened in2012 is, in 2011, kenya had experienced a drought, thatit was barely recovering from. and as it wasstarting to recover, a disease had beendiscovered-- a crop disease had been discovered. and just as that diseasestarted to spread, droughts in the us andrussia hit simultaneously. now the us and russia aretwo of the world's largest grain exporting countries.

what that meant, was thatkenyan corn prices went from being belowthe global average, to being well above the average. and it kept gettingworse, because what happened waspolicymakers then adopted a policy of reinstatinga 50% import tax on corn. now corn, in the usmight mean something like tortilla chips, highfructose corn syrup, ethanol. corn in kenya, is whatkenyans eat every single day.

it provides almost half ofthe calorie requirements for the country. and the poorest quarter in thecountry, spend about a third of their incomeon that one grain. now when i graduatedfrom college, i remember beingtold to spend about-- to expect to spend about athird of my salary on rent. so now imagine spending a thirdof your total income, not all your food requirements,but on a single good.

see, there's nomore room for error, in the way we thinkabout food, and the way we think about food prices. and we're already at a stagewhen we have no room for error. and areas like the one igave as an example in kenya, unfortunately happenall over africa. and it happens notbecause policymakers are malicious or malintention. it happens because there'sa lack of information

and clarity, in the typeof information needed, to make the policydecisions being made. now fast forward in wherewe're going to, as a world. we are expected to be 9.1billion people by 2050. as a wealthier population, we'reexpected to need 70% more food. because we consume a lotmore, than we actually growing as a population. so in this space wherethere's no room for error, you have this happeningwith population.

and to top it off, youhave climate change. the frequency ofdroughts, floods, wind-related crop damagehas grown exponentially-- such that, actually figuringout agricultural production, and productivity, hasbecome impossible. so what happens next? we've got it--it's clear we have to increase food production. how does that happen?

it's got to happenin one of two ways. we're either goingto have to start growing more foodon the plots of land that we're growing foodin, so increasing yield. or we're going to haveto plant new land. now i'll argue, as much as isaid about africa, that africa is actually the placefor that to happen. not only does it have thelargest swath of arable land remaining in the world-- fourtimes the amount in the us,

planted across the us today. it also has such low yields,that if in 2012, african corn yields were just equivalentto the world average, we could have actuallyincreased corn production by 12% that year. it was a 2% reduction incorn production globally, that actually led tothat sort of price spike. so imagine what a 12% increasein production can happen. so the next question youask is, so how are we

going to solve this mess? and how do we goabout doing that? that's where we liketo think of the work that we're doing as beingthat moonshot around how to addressproductivity in africa. we've created a real time,basically tracking application, that allows all sorts of users,from policymakers to traders, to basically visualize andanalyze all sorts of data around agriculture.

so the applicationcurrently, basically-- it's not that the data isn'tavailable by the way, in terms of whatpolicymakers are using. it's that it'shighly disaggregated. it's comes in multiple formats. and nobody knows where it sits. so what ends uphappening, is that a user doesn't know whichsource to tap, for what piece of information.

so what we've done is we'vecreated a blank slate. it's a blank slate thatactually sucks in and aggregates all sorts of data-- over 40,000indicators, that basically look at all sorts of analytics aroundafrica, african agriculture, but also global agriculture. so metrics fromemissions, to rainfall, to vegetation, to production. so what ends up happening is, acontinent where 30% of its gdp comes from agriculture--less than 1%

of outstanding bank loans todayare to the agricultural sector, the reason is capitalis not available. so what we're tryingto do, is basically make the data available thatlets capital be unleashed. so in this context, now youtake your tortilla chips-- and i want everybody toimagine being a credit officer for farmers in nigeria. and you have andnigerian cassava farmer that comes to your office.

in the past, the way decisionsare made is a yes or no, and oftentimes,it ends with a no. what we are envisioning,is a future, where if you area credit officer, you have a tool thatlets you go in and look at all sorts of parameters,around say, supply and the supply ofcertain different crops that are important in nigeria. so to give an example,tomatoes-- nigerians

are actually one of the largestimporters of tomato paste, and wheat. and so, it allows you to goin, and create this real time tracking system, thatallows you to look at a series of theseindicators, in such a way that you can generatea series of charts. now, i've kind of fasttracked this process, so that we can get towhat we actually track. so we track everythingfrom-- so imagine

you have a cassava farmercoming in for a loan. now, cassava tonigerians is what's equivalent to the corn storythat i told you about in kenya, they eat it every single day. now, as you can see,cassava production-- if you're a creditofficer, you have to understand the volatilityin production cycles. that you'll see in 2009,there was a cassava crisis. you'll want to understandwhy that happened,

and how you can thinkof that differently. that actuallyhappened because there was flooding in the core cassavaproducing regions of nigeria at the time. now what ends up happening whenyou have that sort of rainfall, and that sort of dropin cassava production, is you have a drasticimport of wheat. wheat is the alternative to it. and the us provides 80%of the wheat into nigeria.

and so you can track vegetation. so you can actuallywatch how vegetation in a particular region evolves. by being able to lookat, and dynamically visualize all this datathat is incredibly complex-- this is not comingfrom a single source. each one looks atvarious sources to extrapolate what thetrue number should be. because no one sourceactually tells us what it is.

and so what we'rehoping, is that this tool becomes the tool that allowsus to basically unleash capital into african agriculturalmarkets, to increase the yields so that farmers canbasically produce more on the existing plots of land,which then feeds into more investment going into allthat other arable land that i discussed, whichthen leads to abundant food, and hopefully cheap food. thanks.

megan smith: ok, so a quickquestion for sara before you go down, and then we'lltake the next one up. so we're going togo to brainstorming, and there's goingto be two tables who are going to work on this idea. so in addition to allthe ideas that they think of, whatever they thinkof, two thirds yes and-- what kind of distro,technology, partners, money, other ideas thatyou guys can think of,

that would help this idea. and then, one thirdyes but, meaning like, what are yourcritiques and challenges you think are there,and some ideas there. is there any set of things, oneor two things that you really need help on right now, thatyou know, as you are building? sara menker: aswe're building, well, there's two thingsi can think of. one is, we just actuallyfinished our first fund raise,

and we're out there hiring allsorts of talent from front end, to back end, to machine learningengineers-- we need people. and the second,is the tool that i showed you, which is thevisualization around satellite imagery, and weather data,everything we've done is basically, allowit to be animatable. so a user gets tocurate their experience and get to zoom in toa particular region. and then say, i want tounderstand the 10 day

average in thisparticular region, versus the 10 day average there. and so when you're runninga series of computations on images that arevarying anyway, that are coming in daily, orvarying anywhere from being 50 meter squared to youknow, 100 meter square, you run into allsorts of challenges, in terms of givingit to the user. so we're thinking about waysof optimizing that further--

megan smith: tosimplify, and enhance-- sara menker: yes,simplifying that process. megan smith: --and figureout how to interact. ok. sara menker: yeah, sowe're on geospatial. megan smith: ok, super. all right, thank you. next up is a reallyinteresting idea around environmentaldata and impact.

and randy, i just lovewhen, a lot of times we think about china, andwe hear terrible stories, scary stories about environment. and you guys are such a hopeful,and inventive, and ingenious story from china,of what you've done. and so i look forwardto everybody hearing what you guys are proposing. liu chunlei: ok thank you. hi, everybody.

good afternoon. i'm lui chunlei,from shanghai, china. my topic is how to supportthe environmental protection information technology in china? this is our website. ok i think many guysknow china is facing one the most seriousenvironment issues. billions of people are impactedby this, such as water. this is the fromnew, the [inaudible].

the water qualityof most of the river are the worst level in china. and also, the ground wateris a polluted heavily. for air, more than1,200,000 people died earlier due to theair pollution in china. you can see shanghai is in haze. and the farmland. more than 50 millionacres of farmland are heavily polluted in china.

we know the environmentissue is very, very serious. this is also an example,the haze of days in 2013. we know, almost everydaywe can find the [inaudible] from the news paper, or the tv. but we are not sure,first for citizens, they're not sure what exactlyis the environment around him. and how to resolve thepollution issue in a rapid way, because you know thereis some relationship between the governmentand the factory.

it's not so easy toresolve this issue. so this is why i leftalcatel-lucent-- i worked there for more than eightyears-- to start this job. i want to help peoplein a foreign way. out of our million users, youcan find [inaudible], how to, through maps, how to helphim, and to resolve something. he wants an apartment. so he search onereal estate website, and found this apartment is ok.

but he want to knowwhether it is safe or not. then he could go to thedanger map, and to search. input the address, and search. and then he found thatthere are many-- not many-- for some site, there aresome pollutions issues wrong. so he need toreconsider this choice, and he need to try again. after sometimes searching,he found [inaudible] is ok. but of some amounts,he found that the water

released some bad materials. so he bought a watertesting kits [inaudible], and he started tosample the water. the results was varying. so he upload this resultwith the smartphone onto the [inaudible] map. and shared this mapto his neighbors, and also [inaudible]. then the neighbors gathertogether, and have a meeting.

they decided to walkalong the river, to find the cause,why this is polluted? why is this [inaudible]? and finally, theyfound one factory, releasing the pollution waterdirectly without any deals. they put the exactposition on the danger map. and they searchedthe number the epb, and tried to push themto stop this factory, to stop this pollution.

but it's not so easy. just [inaudible], there'sa complex relationship between the government andthe factory for some tax, or for other reasons,corruption and so on. so they need to continue,they need to go on, to push, and go on to such,many more pollutions. now this is the currentdanger map, they can help, it can help. it can help to found someof the pollution around it.

and to gather theneighbors, to [inaudible]. and now, they are more bigcompanies, also in the world , such as alibaba. the prompt there, [inaudible]. and water test kitsto their employees. so last year, they hadtested the 420 locations across 28 provinces. and also, more mediasand foundations involved, such as southernweekly, [inaudible] dfdaily,

and the see foundation. and also, there are manyngos are using this tool to identify thesepollutions and recourse. but citizens think itis not good enough. so the need better services. so we are planning thefollowing features. not only now, whetherthere are pollution, there are factories,but know exactly is there any recordfor the pollution,

and what the realtimewater or gas is released and whether itexceeded the threshold. with this information published,so the real estate developers, many of them aremillionaires or billionaires, can help control the pollution,because this ill impact the price to their apartment. also, currently there are manydata controlled by government, but they didn't publishor not a convenient way. so we needed tosummit the application

to open it, and show them,and analyze and show them to the citizens, ina convenient way. also, they need-- maybe youhave the air quality and water quality, with realtime history and trend. and also, we needto know if there any good things aroundus, not only bad things. so we can give people some hope. and also commentsabout the environment from the local citizens.

when he found somepollution issue, he can share this informationto also ngos and medias. because this, theywill help them to fix this, toresolve this issue. and we will present thephone number, email, weibo, and weixin, in the epb. so they can contact thepartners in a really rapid way, to set up the [inaudible]. and if the citizen contributeto a local environment

reach some criteria,you will get some gifts from some big company. this company-- this bigcompanies, [inaudible] their brand, and want to makeof their brand environment friendly. so in this way,also the employees of these big companiescan be involved. it's millions, i think. and in china, thereare also many ngos

for environment protection. we will design amechanism, so they can be involved ina more deeper way. so we can support each other,and also impact their fans. the draft plan-- a new,open interactive danger maps with solid data, will bebuilt in the following way. because china, thereare many provinces. so we want to run it this way. and then we want to implement,with this architecture.

so, with the air quality,water quality, land quality, and the pollution sources. all data will be collectedinto the open db. open means open to thethird party and you. and other stakeholders. and then, with theepb and the web, the information can easilybe shared, or feed back to the government,factory, and the reporters. so, citizens can know theoverall environment around us,

and also, action, tochange them in a rapid way. technically, we will implementthis with such technologies, internal db, node.js, mirrors,and hybrid app, binaries, and so on. that's the technicalarchitecture. yeah, that's all. thank you. puneet ahira: fantastic. thank you so much, liu.

i think what's amazing aboutthis story, is how much attention it'sgotten within china. jack ma, who is the ceoand founder of alibaba, has personally beensupporting this, trying to get allof his employees to be much moreenvironmentally active. and this just provides anoutlet for all of that, to become so much moreexposed and transparent. liu, if you have-- i wantedto get your perspective, what

are the biggestchallenges that you're facing that this groupcan brainstorm about, during our breakout session? liu chunlei: thefirst one is the data. the environmental datais [inaudible] for china, such as farmland. pollution data isa secret of nation. so we can not get it. and there are alsomany data [inaudible]

that is not so easyto dig, to analysis. so we need some way tomany, many application, for to government,to open the data. this is the first one. i think the secondone is we need more support fromfinancial partners. there are manyjobs needed to do. but we need moresupport, i think, yeah. puneet ahira: excellent.

thank you so much again. liu chunlei: yeah, thank you. puneet ahira: our next-- sorry,another round of applause, if you-- our next speaker isprofessor sarah bergbreiter, from the university of maryland. and she's got afascinating proposal that she's going topresent, on the use of micro roboticplatforms, and all

of the incredibleapplications it has for many of thechallenges that we face. sarah bergbreiter: all right. thank you very much. so this is the minnesota i-35bridge, about seven years ago in 2007. this bridge supported over140,000 cars each day. when the bridge collapsed,there were over 150 casualties, including about 13 deaths.

to avoid scenes likethis, which are far, far more common in thedeveloping world, the current solution isto do something like this. basically hang a coupleguys under a bridge, with some lights, looking atthe bridge structure, and joints and sure making sure everythingis structurally sound. and honestly, you'reprobably lucky if this happens every couple years. in the developing world, you'relucky if it happens at all,

i think. so we'd like to come up witha better solution for that. another thing that yousee on tv way too often, is scenes like this. so this is the aftermath of thenew zealand earthquake in 2011. you see a bunch of guyssearching through some rubble, trying to find survivors,after this rather catastrophic earthquake. and you have even morecatastrophic earthquakes,

like in haiti and the like. but these enormouspiles of rubble, and how do you get through them? how do you find survivors? we'd like to be able to createmore scenes like this one, where rescuers found a fourmonth old baby, shortly after the japanese tsunami. so what kind of infrastructure--what kind of platform can we use to help us solveboth of these problems?

things like civil infrastructuremonitoring, and searching for survivors aftersomething like an earthquake. i'm going to propose this guy. this is an ant. or more appropriately,this guy, right here. this is a roboticversion of an ant, that we're working on in my labat the university of maryland. so i'll talk a little bitmore about this guy later. and i have it withme, in my bag,

if anybody would like to seeit a little bit later, as well. but these things can do somefascinating things, right? we have some amazingexistence proofs in biology of whatthese insects can do. ants can build bridges out ofthemselves, for other ants. really incredible stuff. you've all seen ants carrycheerios or potato chips off of your picnic table, i'm sure. much to your chagrin, right?

termites, which are verymuch on the same scale, build these incrediblestructures, up to eight meters high-- effectively wellventilated, air conditioned, apartment buildingsfor other termites. right? so impressive structures. i don't thinkanybody would argue that somethingthe size of an ant can get throughsome of that rubble,

and has the appropriate sensors,and communications on board, notify first respondersafter an earthquake. and the ants andinsects this size can also make themselvescomfortably at home, on fairly complexstructures like a bridge. so what do we need to do inorder to engineer this ant? what do we need to do tocreate an engineered robot ant? or probably more appropriately,bunches of these robot ants. so we can needbuckets full of them.

so i'll briefly go throughsome of the big challenges that i see. so, one is mobility. i'm really small. everything elsearound me is big. how do i get through that? i also needmechanisms, and motors, in order to supportthat mobility. and i need them to berobust, and efficient,

in order to getthrough these things. i need the power, the control,the integration, in order to add sensors, communicationpotentially, in order to be able to localmote, andget through these environments. and perhaps even moreimportantly, in the end, i need group behavior. so i can do impressivethings like this, which you've all seen probably. in this case, a bunch ofants found a tasty treat,

a dead grasshopper. they're managing to extricateit from these dead leaves, and slowly move ittowards their nest. and you can see thisincredible locomotion through this ratherrough terrain. imagine your roombaat home, trying to do this kind ofsame thing, right? horrible. like it sees a step,and it's like, ah!

so we want to be able todo something like this. so for the sakeof time, i'm going to focus on a coupleof these challenges. we're working on allof them in my lab. and i'm happy to talka little bit more about some of theother ones as well. but i'll focus a little bit onmobility mechanisms and motors. so first, mobility. so this is another insect.

you already saw the antsmoving through these things. this is from across the bay atbob full's lab at uc berkeley, watching cockroaches get throughthis incredible environment, right? if you and i tried to getthrough an environment like this, right? we're looking down, makingsure our foot is stable, before we take our next step. cockroaches don'tdo any of this.

the mechanisms in theirleg provide the control and the stability,so that they can run through theseenvironments at high speeds. and part of whatallows them to do that, is a combination ofrigid materials, which is what we traditionally usedto make robots, but also soft, [inaudible], elastic materials,that give them the damping, to enable them to do this. another interestingmethod of locomotion,

if you're reallysmall, is jumping. and there's all sorts ofinteresting jumping insects out there. in this case, they storeenergy in effectively, a spring, and releasethat very quickly, to get the high powerthey need to jump. and then once again, it's acombination of rigid materials and soft materials, thatenable them to do things like jump out of water,which is quite impressive.

so our big contribution hasbeen to add soft materials to traditional microfabrication processes. so micro fabrication allowsus to get structures down to microns in size-- right? your hair is typically 50to 100 microns in diameter, for reference. and in this case,we can also take advantage of a lot of thesensors and actuators, that people are youdoing in silicon,

with our future micro robots. so what do we do to dothis, to incorporate these soft materials,is we effectively have a micro molding process. we etch trenches intoour silicon wafer. we refill that with arubber, silicone elastomer, which is the blue here. we etch more trenches, tocreate our silicon features. and we can do this, acrossa whole silicon wafer,

so we can make thousandsof these at once-- which is the cool thing. so we can make someinteresting structures. but you ask, ok,so this is cool, but how do i get my robot? so this is an interestinglittle jumping mechanism that we put together. this video, this whole thingis about four millimeters on a side.

this video is very freaky,to any [inaudible] person, or micro fabricationperson, because you're not used to seeing strains like thisin traditional micro machining materials. so the basic ideabehind this is, i'm going to take the structureof four millimeters in size, compress it, and release thatenergy, in order to get a jump. so there's no motorson this, no power yet. this is actuated in a veryfancy method, we have in our lab

called graduatestudent with tweezers. so what we're going tosee in the next video, is a black, fuzzy dotflying through the air. so this is a verysmall, black, fuzzy dot. this is erin, the graduatestudent in question. and what you see here, is thislittle four millimeter device jumping almost 100times it's own length. but once again, no motors, nopower or anything like that. but incredibly robust-- itactually bounces on the table.

it's survives over and over,and over, until we eventually lose it, when itflies off the screen. how are we going toactuate these things? well, this is some of the motorsthat we're doing in our lab. they have high power densities--higher than insect flight muscle, in fact. but they're still very hard tointegrate with the mechanisms that i just showed you, inorder to really study locomotion at this scale.

so we're going to cheat. we're going to putmagnets in here right now. and this is controlled withan external magnetic field. but you can see, i have thiscompliant elastomer joint. i've got a magnetembedded in there. and this is effectively,a little robot leg. so this would be part ofwhat i showed you earlier, in this littlemicro robot mock up. one of the interesting thingsabout locomotion at this scale,

is that we don't reallyknow how to do it yet. so we have goodmodels for everything from a cockroach on up. if you want to knowhow we run, you can basically thinkof a mass on a spring. and we compressthis spring as we land, and release thatenergy as we take off. everything does this. as you get smaller, the forcesin interacting with the ground

are going to start toaffect your locomotion, more potentially than your massand your inertia-- which is very tiny, whenyou're this small. so this particular oneis not working quite yet. but we have ones atcentimeter cubed, to show you what thesethings actually look like, when they're moving around. so these guys, we've moved at upto 10 body lengths per second. so they can move quite quick,and that's really only limited

by our test set up. so this gives you an ideaof how the magnetic field is controlling these guys. so we can actually startstudying how we ultimately want to locamote, to solvesome of these challenges. but ultimately, we want toadd our sensors and control, and everything on board too. so this guy is aboutfour millimeters, by four millimeters, byseven millimeters in size.

it has capacitors for power. it has a transistor for control. and it has a lightsensor on board. so it's going to react tolight in its environment. and the actuatorin this case-- this is done by my student,wayne churaman, who's also at thearmy research lab. the actuator, we don't need tonecessarily be bio inspired. the actuator is an energetic.

it goes boom. so in this case, we can microfabricate small, little pixels of this energetic material. and we can set themoff independently, from multiple jumps or jumpsin different directions. and the cool thing aboutthis, is that we can actually combine this then, withour robot that i showed you earlier, put it onthe belly of this. and we can effectively haveour little micro rocket robot

for jumping. so the next video, oneof my favorite videos, you see this thing jump up--the big flash at the beginning, this is at 1,000frames per second, and it flies through the air. so, pretty, prettycool, i think, at least. so i think you have some ideaof how we can kind of jump around, crawl aroundthese big structures, or where we're goingwith that, at least.

but they're certainly notlimited-- these robotic insects are certainly notlimited to those ideas. imagine like,something even a larger than the fantastic, voyagevehicle, for robotic surgery. either in the us, or inthe developing world, you could do some reallyfascinating things with that. or imagine, if you cancombine sensors and actuators, and mechanisms invery small packages, maybe you can create luke'shand from "star wars"

versus the most advanced,prosthetic hands that we have today. or one of the big problems withthese earthquake disasters, is not necessarilythe disaster, itself, but the humanitarian disasterthat happens afterwards. so imagine buildingtemporary housing with lots of little robots,like our termite mounds. or even radically changingthe construction industry with this.

so this gives yousome idea of some of the possibilitiesof things that i think we could dowith small robots. and i think we're kind of onthe verge of really pushing this area out there. and so i think it's apretty fantastic moonshot. and i thank you for your time.

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