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#431159 How Close Is Turing’s Dream of ...

The quest for conversational artificial intelligence has been a long one.
When Alan Turing, the father of modern computing, racked his considerable brains for a test that would truly indicate that a computer program was intelligent, he landed on this area. If a computer could convince a panel of human judges that they were talking to a human—if it could hold a convincing conversation—then it would indicate that artificial intelligence had advanced to the point where it was indistinguishable from human intelligence.
This gauntlet was thrown down in 1950 and, so far, no computer program has managed to pass the Turing test.
There have been some very notable failures, however: Joseph Weizenbaum, as early as 1966—when computers were still programmed with large punch-cards—developed a piece of natural language processing software called ELIZA. ELIZA was a machine intended to respond to human conversation by pretending to be a psychotherapist; you can still talk to her today.
Talking to ELIZA is a little strange. She’ll often rephrase things you’ve said back at you: so, for example, if you say “I’m feeling depressed,” she might say “Did you come to me because you are feeling depressed?” When she’s unsure about what you’ve said, ELIZA will usually respond with “I see,” or perhaps “Tell me more.”
For the first few lines of dialogue, especially if you treat her as your therapist, ELIZA can be convincingly human. This was something Weizenbaum noticed and was slightly alarmed by: people were willing to treat the algorithm as more human than it really was. Before long, even though some of the test subjects knew ELIZA was just a machine, they were opening up with some of their deepest feelings and secrets. They were pouring out their hearts to a machine. When Weizenbaum’s secretary spoke to ELIZA, even though she knew it was a fairly simple computer program, she still insisted Weizenbaum leave the room.
Part of the unexpected reaction ELIZA generated may be because people are more willing to open up to a machine, feeling they won’t be judged, even if the machine is ultimately powerless to do or say anything to really help. The ELIZA effect was named for this computer program: the tendency of humans to anthropomorphize machines, or think of them as human.

Weizenbaum himself, who later became deeply suspicious of the influence of computers and artificial intelligence in human life, was astonished that people were so willing to believe his script was human. He wrote, “I had not realized…that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people.”

“Consciously, you know you’re talking to a big block of code stored somewhere out there in the ether. But subconsciously, you might feel like you’re interacting with a human.”

The ELIZA effect may have disturbed Weizenbaum, but it has intrigued and fascinated others for decades. Perhaps you’ve noticed it in yourself, when talking to an AI like Siri, Alexa, or Google Assistant—the occasional response can seem almost too real. Consciously, you know you’re talking to a big block of code stored somewhere out there in the ether. But subconsciously, you might feel like you’re interacting with a human.
Yet the ELIZA effect, as enticing as it is, has proved a source of frustration for people who are trying to create conversational machines. Natural language processing has proceeded in leaps and bounds since the 1960s. Now you can find friendly chatbots like Mitsuku—which has frequently won the Loebner Prize, awarded to the machines that come closest to passing the Turing test—that aim to have a response to everything you might say.
In the commercial sphere, Facebook has opened up its Messenger program and provided software for people and companies to design their own chatbots. The idea is simple: why have an app for, say, ordering pizza when you can just chatter to a robot through your favorite messenger app and make the order in natural language, as if you were telling your friend to get it for you?
Startups like Semantic Machines hope their AI assistant will be able to interact with you just like a secretary or PA would, but with an unparalleled ability to retrieve information from the internet. They may soon be there.
But people who engineer chatbots—both in the social and commercial realm—encounter a common problem: the users, perhaps subconsciously, assume the chatbots are human and become disappointed when they’re not able to have a normal conversation. Frustration with miscommunication can often stem from raised initial expectations.
So far, no machine has really been able to crack the problem of context retention—understanding what’s been said before, referring back to it, and crafting responses based on the point the conversation has reached. Even Mitsuku will often struggle to remember the topic of conversation beyond a few lines of dialogue.

“For everything you say, there could be hundreds of responses that would make sense. When you travel a layer deeper into the conversation, those factors multiply until you end up with vast numbers of potential conversations.”

This is, of course, understandable. Conversation can be almost unimaginably complex. For everything you say, there could be hundreds of responses that would make sense. When you travel a layer deeper into the conversation, those factors multiply until—like possible games of Go or chess—you end up with vast numbers of potential conversations.
But that hasn’t deterred people from trying, most recently, tech giant Amazon, in an effort to make their AI voice assistant, Alexa, friendlier. They have been running the Alexa Prize competition, which offers a cool $500,000 to the winning AI—and a bonus of a million dollars to any team that can create a ‘socialbot’ capable of sustaining a conversation with human users for 20 minutes on a variety of themes.
Topics Alexa likes to chat about include science and technology, politics, sports, and celebrity gossip. The finalists were recently announced: chatbots from universities in Prague, Edinburgh, and Seattle. Finalists were chosen according to the ratings from Alexa users, who could trigger the socialbots into conversation by saying “Hey Alexa, let’s chat,” although the reviews for the socialbots weren’t always complimentary.
By narrowing down the fields of conversation to a specific range of topics, the Alexa Prize has cleverly started to get around the problem of context—just as commercially available chatbots hope to do. It’s much easier to model an interaction that goes a few layers into the conversational topic if you’re limiting those topics to a specific field.
Developing a machine that can hold almost any conversation with a human interlocutor convincingly might be difficult. It might even be a problem that requires artificial general intelligence to truly solve, rather than the previously-employed approaches of scripted answers or neural networks that associate inputs with responses.
But a machine that can have meaningful interactions that people might value and enjoy could be just around the corner. The Alexa Prize winner is announced in November. The ELIZA effect might mean we will relate to machines sooner than we’d thought.
So, go well, little socialbots. If you ever want to discuss the weather or what the world will be like once you guys take over, I’ll be around. Just don’t start a therapy session.
Image Credit: Shutterstock Continue reading

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#430814 The Age of Cyborgs Has Arrived

How many cyborgs did you see during your morning commute today? I would guess at least five. Did they make you nervous? Probably not; you likely didn’t even realize they were there.
In a presentation titled “Biohacking and the Connected Body” at Singularity University Global Summit, Hannes Sjoblad informed the audience that we’re already living in the age of cyborgs. Sjoblad is co-founder of the Sweden-based biohacker network Bionyfiken, a chartered non-profit that unites DIY-biologists, hackers, makers, body modification artists and health and performance devotees to explore human-machine integration.
Sjoblad said the cyborgs we see today don’t look like Hollywood prototypes; they’re regular people who have integrated technology into their bodies to improve or monitor some aspect of their health. Sjoblad defined biohacking as applying hacker ethic to biological systems. Some biohackers experiment with their biology with the goal of taking the human body’s experience beyond what nature intended.
Smart insulin monitoring systems, pacemakers, bionic eyes, and Cochlear implants are all examples of biohacking, according to Sjoblad. He told the audience, “We live in a time where, thanks to technology, we can make the deaf hear, the blind see, and the lame walk.” He is convinced that while biohacking could conceivably end up having Brave New World-like dystopian consequences, it can also be leveraged to improve and enhance our quality of life in multiple ways.
The field where biohacking can make the most positive impact is health. In addition to pacemakers and insulin monitors, several new technologies are being developed with the goal of improving our health and simplifying access to information about our bodies.
Ingestibles are a type of smart pill that use wireless technology to monitor internal reactions to medications, helping doctors determine optimum dosage levels and tailor treatments to different people. Your body doesn’t absorb or process medication exactly as your neighbor’s does, so shouldn’t you each have a treatment that works best with your unique system? Colonoscopies and endoscopies could one day be replaced by miniature pill-shaped video cameras that would collect and transmit images as they travel through the digestive tract.
Singularity University Global Summit is the culmination of the Exponential Conference Series and the definitive place to witness converging exponential technologies and understand how they’ll impact the world.
Security is another area where biohacking could be beneficial. One example Sjoblad gave was personalization of weapons: an invader in your house couldn’t fire your gun because it will have been matched to your fingerprint or synced with your body so that it only responds to you.
Biohacking can also simplify everyday tasks. In an impressive example of walking the walk rather than just talking the talk, Sjoblad had an NFC chip implanted in his hand. The chip contains data from everything he used to have to carry around in his pockets: credit and bank card information, key cards to enter his office building and gym, business cards, and frequent shopper loyalty cards. When he’s in line for a morning coffee or rushing to get to the office on time, he doesn’t have to root around in his pockets or bag to find the right card or key; he just waves his hand in front of a sensor and he’s good to go.
Evolved from radio frequency identification (RFID)—an old and widely distributed technology—NFC chips are activated by another chip, and small amounts of data can be transferred back and forth. No wireless connection is necessary. Sjoblad sees his NFC implant as a personal key to the Internet of Things, a simple way for him to talk to the smart, connected devices around him.
Sjoblad isn’t the only person who feels a need for connection.

When British science writer Frank Swain realized he was going to go deaf, he decided to hack his hearing to be able to hear Wi-Fi. Swain developed software that tunes into wireless communication fields and uses an inbuilt Wi-Fi sensor to pick up router name, encryption modes and distance from the device. This data is translated into an audio stream where distant signals click or pop, and strong signals sound their network ID in a looped melody. Swain hears it all through an upgraded hearing aid.
Global datastreams can also become sensory experiences. Spanish artist Moon Ribas developed and implanted a chip in her elbow that is connected to the global monitoring system for seismographic sensors; each time there’s an earthquake, she feels it through vibrations in her arm.
You can feel connected to our planet, too: North Sense makes a “standalone artificial sensory organ” that connects to your body and vibrates whenever you’re facing north. It’s a built-in compass; you’ll never get lost again.
Biohacking applications are likely to proliferate in the coming years, some of them more useful than others. But there are serious ethical questions that can’t be ignored during development and use of this technology. To what extent is it wise to tamper with nature, and who gets to decide?
Most of us are probably ok with waiting in line an extra 10 minutes or occasionally having to pull up a maps app on our phone if it means we don’t need to implant computer chips into our forearms. If it’s frightening to think of criminals stealing our wallets, imagine them cutting a chunk of our skin out to have instant access to and control over our personal data. The physical invasiveness and potential for something to go wrong seems to far outweigh the benefits the average person could derive from this technology.
But that may not always be the case. It’s worth noting the miniaturization of technology continues at a quick rate, and the smaller things get, the less invasive (and hopefully more useful) they’ll be. Even today, there are people already sensibly benefiting from biohacking. If you look closely enough, you’ll spot at least a couple cyborgs on your commute tomorrow morning.
Image Credit:Movement Control Laboratory/University of Washington – Deep Dream Generator Continue reading

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#430761 How Robots Are Getting Better at Making ...

The multiverse of science fiction is populated by robots that are indistinguishable from humans. They are usually smarter, faster, and stronger than us. They seem capable of doing any job imaginable, from piloting a starship and battling alien invaders to taking out the trash and cooking a gourmet meal.
The reality, of course, is far from fantasy. Aside from industrial settings, robots have yet to meet The Jetsons. The robots the public are exposed to seem little more than over-sized plastic toys, pre-programmed to perform a set of tasks without the ability to interact meaningfully with their environment or their creators.
To paraphrase PayPal co-founder and tech entrepreneur Peter Thiel, we wanted cool robots, instead we got 140 characters and Flippy the burger bot. But scientists are making progress to empower robots with the ability to see and respond to their surroundings just like humans.
Some of the latest developments in that arena were presented this month at the annual Robotics: Science and Systems Conference in Cambridge, Massachusetts. The papers drilled down into topics that ranged from how to make robots more conversational and help them understand language ambiguities to helping them see and navigate through complex spaces.
Improved Vision
Ben Burchfiel, a graduate student at Duke University, and his thesis advisor George Konidaris, an assistant professor of computer science at Brown University, developed an algorithm to enable machines to see the world more like humans.
In the paper, Burchfiel and Konidaris demonstrate how they can teach robots to identify and possibly manipulate three-dimensional objects even when they might be obscured or sitting in unfamiliar positions, such as a teapot that has been tipped over.
The researchers trained their algorithm by feeding it 3D scans of about 4,000 common household items such as beds, chairs, tables, and even toilets. They then tested its ability to identify about 900 new 3D objects just from a bird’s eye view. The algorithm made the right guess 75 percent of the time versus a success rate of about 50 percent for other computer vision techniques.
In an email interview with Singularity Hub, Burchfiel notes his research is not the first to train machines on 3D object classification. How their approach differs is that they confine the space in which the robot learns to classify the objects.
“Imagine the space of all possible objects,” Burchfiel explains. “That is to say, imagine you had tiny Legos, and I told you [that] you could stick them together any way you wanted, just build me an object. You have a huge number of objects you could make!”
The infinite possibilities could result in an object no human or machine might recognize.
To address that problem, the researchers had their algorithm find a more restricted space that would host the objects it wants to classify. “By working in this restricted space—mathematically we call it a subspace—we greatly simplify our task of classification. It is the finding of this space that sets us apart from previous approaches.”
Following Directions
Meanwhile, a pair of undergraduate students at Brown University figured out a way to teach robots to understand directions better, even at varying degrees of abstraction.
The research, led by Dilip Arumugam and Siddharth Karamcheti, addressed how to train a robot to understand nuances of natural language and then follow instructions correctly and efficiently.
“The problem is that commands can have different levels of abstraction, and that can cause a robot to plan its actions inefficiently or fail to complete the task at all,” says Arumugam in a press release.
In this project, the young researchers crowdsourced instructions for moving a virtual robot through an online domain. The space consisted of several rooms and a chair, which the robot was told to manipulate from one place to another. The volunteers gave various commands to the robot, ranging from general (“take the chair to the blue room”) to step-by-step instructions.
The researchers then used the database of spoken instructions to teach their system to understand the kinds of words used in different levels of language. The machine learned to not only follow instructions but to recognize the level of abstraction. That was key to kickstart its problem-solving abilities to tackle the job in the most appropriate way.
The research eventually moved from virtual pixels to a real place, using a Roomba-like robot that was able to respond to instructions within one second 90 percent of the time. Conversely, when unable to identify the specificity of the task, it took the robot 20 or more seconds to plan a task about 50 percent of the time.
One application of this new machine-learning technique referenced in the paper is a robot worker in a warehouse setting, but there are many fields that could benefit from a more versatile machine capable of moving seamlessly between small-scale operations and generalized tasks.
“Other areas that could possibly benefit from such a system include things from autonomous vehicles… to assistive robotics, all the way to medical robotics,” says Karamcheti, responding to a question by email from Singularity Hub.
More to Come
These achievements are yet another step toward creating robots that see, listen, and act more like humans. But don’t expect Disney to build a real-life Westworld next to Toon Town anytime soon.
“I think we’re a long way off from human-level communication,” Karamcheti says. “There are so many problems preventing our learning models from getting to that point, from seemingly simple questions like how to deal with words never seen before, to harder, more complicated questions like how to resolve the ambiguities inherent in language, including idiomatic or metaphorical speech.”
Even relatively verbose chatbots can run out of things to say, Karamcheti notes, as the conversation becomes more complex.
The same goes for human vision, according to Burchfiel.
While deep learning techniques have dramatically improved pattern matching—Google can find just about any picture of a cat—there’s more to human eyesight than, well, meets the eye.
“There are two big areas where I think perception has a long way to go: inductive bias and formal reasoning,” Burchfiel says.
The former is essentially all of the contextual knowledge people use to help them reason, he explains. Burchfiel uses the example of a puddle in the street. People are conditioned or biased to assume it’s a puddle of water rather than a patch of glass, for instance.
“This sort of bias is why we see faces in clouds; we have strong inductive bias helping us identify faces,” he says. “While it sounds simple at first, it powers much of what we do. Humans have a very intuitive understanding of what they expect to see, [and] it makes perception much easier.”
Formal reasoning is equally important. A machine can use deep learning, in Burchfiel’s example, to figure out the direction any river flows once it understands that water runs downhill. But it’s not yet capable of applying the sort of human reasoning that would allow us to transfer that knowledge to an alien setting, such as figuring out how water moves through a plumbing system on Mars.
“Much work was done in decades past on this sort of formal reasoning… but we have yet to figure out how to merge it with standard machine-learning methods to create a seamless system that is useful in the actual physical world.”
Robots still have a lot to learn about being human, which should make us feel good that we’re still by far the most complex machines on the planet.
Image Credit: Alex Knight via Unsplash Continue reading

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#430734 Why XPRIZE Is Asking Writers to Take Us ...

In a world of accelerating change, educating the public about the implications of technological advancements is extremely important. We can continue to write informative articles and speculate about the kind of future that lies ahead. Or instead, we can take readers on an immersive journey by using science fiction to paint vivid images of the future for society.
The XPRIZE Foundation recently announced a science fiction storytelling competition. In recent years, the organization has backed and launched a range of competitions to propel innovation in science and technology. These have been aimed at a variety of challenges, such as transforming the lives of low-literacy adults, tackling climate change, and creating water from thin air.
Their sci-fi writing competition asks participants to envision a groundbreaking future for humanity. The initiative, in partnership with Japanese airline ANA, features 22 sci-fi stories from noteworthy authors that are now live on the website. Each of these stories is from the perspective of a different passenger on a plane that travels 20 years into the future through a wormhole. Contestants will compete to tell the story of the passenger in Seat 14C.
In addition to the competition, XPRIZE has brought together a science fiction advisory council to work with the organization and imagine what the future will look like. According to Peter Diamandis, founder and executive chairman, “As the future becomes harder and harder to predict, we look forward to engaging some of the world’s most visionary storytellers to help us imagine what’s just beyond the horizon and chart a path toward a future of abundance.”
The Importance of Science Fiction
Why is an organization like XPRIZE placing just as much importance on fiction as it does on reality? As Isaac Asimov has pointed out, “Modern science fiction is the only form of literature that consistently considers the nature of the changes that face us.” While the rest of the world reports on a new invention, sci-fi authors examine how these advancements affect the human condition.
True science fiction is distinguished from pure fantasy in that everything that happens is within the bounds of the physical laws of the universe. We’ve already seen how sci-fi can inspire generations and shape the future. 3D printers, wearable technology, and smartphones were first seen in Star Trek. Targeted advertising and air touch technology was first seen in Philip K. Dick’s 1958 story “The Minority Report.” Tanning beds, robot vacuums, and flatscreen TVs were seen in The Jetsons. The internet and a world of global instant communication was predicted by Arthur C. Clarke in his work long before it became reality.
Sci-fi shows like Black Mirror or Star Trek aren’t just entertainment. They allow us to imagine and explore the influence of technology on humanity. For instance, how will artificial intelligence impact human relationships? How will social media affect privacy? What if we encounter alien life? Good sci-fi stories take us on journeys that force us to think critically about the societal impacts of technological advancements.
As sci-fi author Yaasha Moriah points out, the genre is universal because “it tackles hard questions about human nature, morality, and the evolution of society, all through the narrative of speculation about the future. If we continue to do A, will it necessarily lead to problems B and C? What implicit lessons are being taught when we insist on a particular policy? When we elevate the importance of one thing over another—say, security over privacy—what could be the potential benefits and dangers of that mentality? That’s why science fiction has such an enduring appeal. We want to explore deep questions, without being preached at. We want to see the principles in action, and observe their results.”
An Extension of STEAM Education
At its core, this genre is a harmonious symbiosis between two distinct disciplines: science and literature. It is an extension of STEAM education, an educational approach that combines science, technology, engineering, the arts, and mathematics. Story-telling with science fiction allows us to use the arts in order to educate and engage the public about scientific advancements and its implications.
According to the National Science Foundation, research on art-based learning of STEM, including the use of narrative writing, works “beyond expectation.” It has been shown to have a powerful impact on creative thinking, collaborative behavior and application skills.
What does it feel like to travel through a wormhole? What are some ethical challenges of AI? How could we terraform Mars? For decades, science fiction writers and producers have answered these questions through the art of storytelling.
What better way to engage more people with science and technology than through sparking their imaginations? The method makes academic subject areas many traditionally perceived as boring or dry far more inspiring and engaging.
A Form of Time Travel
XPRIZE’s competition theme of traveling 20 years into the future through a wormhole is an appropriate beacon for the genre. In many ways, sci-fi is a precautionary form of time travel. Before we put a certain technology, scientific invention, or policy to use, we can envision and explore what our world would be like if we were to do so.
Sci-fi lets us explore different scenarios for the future of humanity before deciding which ones are more desirable. Some of these scenarios may be radically beyond our comfort zone. Yet when we’re faced with the seemingly impossible, we must remind ourselves that if something is within the domain of the physical laws of the universe, then it’s absolutely possible.
Stock Media provided by NASA_images / Pond5 Continue reading

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#430667 Welcome to a More Discoverable ...

This week we’ve rolled out our first major round of improvements to Singularity Hub since our ground-up redesign last December. If we did it right, you’ll find that discovering the technological goodies you come here for is much easier, and so too are other Singularity University offerings you might be interested in.
The first and most major change is in the way Hub’s navigation is structured.
The previous categories in our header (Tech, Future, Health, Science) have been replaced by a single page, Topics, which profiles the most popular tech topics across our site. The featured topics in this menu will be updated regularly based on article performance, so you can keep up with what’s trending in AI, biotech, neuroscience, robotics, or whatever is making the biggest splash most recently.
Rolling our hottest topic category tags into one header dropdown allowed us to create greater focus on some of our newest and best offerings.
Our header now prominently features In Focus, which includes articles on how leaders can make the most of today’s accelerating pace of change by learning to think like futurists, innovators, technologists, and humanitarians. We’ve always been technological optimists, and we want to to make it easy for leaders to find the stories that help make hopeful problem-solvers of us all.
We’ve added a section for Experts, which features leaders in the Singularity University community and showcases their thought leadership including interviews and books. In Events, we highlight Singularity University’s global library of local happenings and summits.
Lastly, we’re excited that our growing original video efforts—from our Ray Kurzweil series to our weekly tech news roundup posts—now live under a central Videos section on Hub. This also gives us a place to highlight our favorite video posts from around the web, including the sci-fi shorts we love so much.
Cruising through the rest of Hub, particularly our homepage, you’ll find a much greater variety of content options, including new stories, top stories, event coverage, and videos. In short, it’s everything a homepage should be. On posts, we’ve tried to keep things as clean as possible, and we put a lot of hours into laboriously streamlining our content tagging structure, making it much easier for you to click through category tags into other stories you might like.

Here’s what @singularityhub looked like 2 years ago, 2 weeks ago, & today. Check it out: https://t.co/7cmlTJwc7d pic.twitter.com/jDayIEIFNv
— Singularity Hub (@singularityhub) July 13, 2017

You’ll also see greater visibility into Singularity University events, along with clearer ways to keep up with Hub and SU both, from simple email newsletter signups to callouts for the SingularityU Hub iOS app and events like SU’s Experts on Air series.
We hope you enjoy the ever-evolving, ever-improving Singularity Hub, and we’d love to hear your feedback. Feel free to tweet us, and let us know your thoughts. You can also pitch us or email us. And as always, thank you for your support. Continue reading

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