Robotics Team Quotes

The Dichotomy of Leadership A good leader must be: • confident but not cocky; • courageous but not foolhardy; • competitive but a gracious loser; • attentive to details but not obsessed by them; • strong but have endurance; • a leader and follower; • humble not passive; • aggressive not overbearing; • quiet not silent; • calm but not robotic, logical but not devoid of emotions; • close with the troops but not so close that one becomes more important than another or more important than the good of the team; not so close that they forget who is in charge. • able to execute Extreme Ownership, while exercising Decentralized Command. A good leader has nothing to prove, but everything to prove. APPLICATION

Are there any Nazis left that I could hunt down and bring to justice?” Augustus asked while we leaned over the vitrines reading Otto’s letters and the gutting replies that no, no one had seen his children after the liberation. “I think they’re all dead. But it’s not like the Nazis had a monopoly on evil.” “True,” he said. “That’s what we should do, Hazel Grace: We should team up and be this disabled vigilante duo roaring through the world, righting wrongs, defending the weak, protecting the endangered.” Although it was his dream and not mine, I indulged it. He’d indulged mine, after all. “Our fearlessness shall be our secret weapon,” I said. “The tales of our exploits will survive as long as the human voice itself,” he said. “And even after that, when the robots recall the human absurdities of sacrifice and compassion, they will remember us.” “They will robot-laugh at our courageous folly,” he said. “But something in their iron robot hearts will yearn to have lived and died as we did: on the hero’s errand.

No shortcuts,” “Work hard, be nice,” “Don’t eat the marshmallow,” “Team and family,” “If there’s a problem, we look for the solution,” “Read, baby, read,” “All of us will learn,” “KIPPsters do the right thing when no one is watching,” “Everything is earned,” “Be the constant, not the variable,” “If a teammate needs help, we give; if we need help, we ask,” “No robots,” and “Prove the doubters wrong.

Heartless reality does not grant humans the lifespan necessary to master every specialty of science, so no one genius in his secret lab can really bring robots, mutants, and clones into the world at his mad whim--it takes a team, masses of funds, and decades. But one man can love all sciences, even if he cannot wield them, and he can inspire children with the model of the mad genius, even if he cannot live it.

They expected her to kill. It’s what they’d trained her for. Her team was the deadliest—capable of wiping out entire cities, just the four of them. The

That's what we should do, Hazel Grace: We should team up and be this disabled vigilante duo roaring through the world, righting wrongs, defending the weak, protecting the endangered. Our fearlessness shall be our secret weapon, the tales of our exploits will survive as long as the human voice itself, and even after that, when the robots recall the human absurdities of sacrifice and compassion, they will remember us. They will robot-laugh at our courageous folly, but something in their iron robot hearts will yearn to have lived and died as we did: on the hero's errand.

While Elizabeth was fast to catch on to engineering concepts, Sunny was often out of his depth during engineering discussions. To hide it, he had a habit of repeating technical terms he heard others using. During a meeting with Arnav’s team, he latched onto the term “end effector,” which signifies the claws at the end of a robotic arm. Except Sunny didn’t hear “end effector,” he heard “endofactor.” For the rest of the meeting, he kept referring to the fictional endofactors. At their next meeting with Sunny two weeks later, Arnav’s team brought a PowerPoint presentation titled “Endofactors Update.” As Arnav flashed it on a screen with a projector, the five members of his team stole furtive glances at one another, nervous that Sunny might become wise to the prank. But he didn’t bat an eye and the meeting proceeded without incident. After he left the room, they burst out laughing.

During a meeting with Arnav’s team, he latched onto the term “end effector,” which signifies the claws at the end of a robotic arm. Except Sunny didn’t hear “end effector,” he heard “endofactor.” For the rest of the meeting, he kept referring to the fictional endofactors. At their next meeting with Sunny two weeks later, Arnav’s team brought a PowerPoint presentation titled “Endofactors Update.

This woman controls my heartbeats. Every love lyric I sing each night is made for her. Every melody chases her heartbeat, and every chorus begs for her love. It has been brought to my attention that a few people on my management team have chosen to approach the love of my life and tell her that she wasn't good for my image. Due to her looks and the past she had no say in creating, they said she wasn't good enough. It's true, we grew up in the same town, but that didn't mean our home lives were built on the same steady foundation. I was blessed enough to never know struggle. This girl had to fight tooth and nail for everything she was given. She sacrificed her own youth, because she didn't want her little sister to go into the foster system. She gave up love, in order for me to go chase my dreams. She gives and gives in order to make others happy, because that's the person she is. She's the most beautiful human being alive, and for anyone--especially people who are supposed to be in my corner--to say differently disgusts me to my core. I am not a robot. I hurt, I ache, I love, and I cry. And it breaks me to live in a world where I have to be afraid of showing who I really am in order to gain followers. So if you don't like this fact--that I am not single and that I am hopelessly in love--then that's fine. If I lose fans over this, I'm okay with that. I will make every sacrifice in the world from this point on in order to give my love fully to the woman who has given more than she ever should've had to give. I love you, Haze. From the new moon to the fullest. From now until forever.

Within weeks of the product’s introduction, both university-based engineering teams and do-it-yourself innovators had hacked into the Kinect and posted YouTube videos of robots that were now able to see in three dimensions.4

But in 2050, a cashier or textile worker losing their job to a robot will hardly be able to start working as a cancer researcher, as a drone operator, or as part of a human–AI banking team. They will not have the necessary skills.

The Dichotomy of Leadership A good leader must be: • confident but not cocky; • courageous but not foolhardy; • competitive but a gracious loser; • attentive to details but not obsessed by them; • strong but have endurance; • a leader and follower; • humble not passive; • aggressive not overbearing; • quiet not silent; • calm but not robotic, logical but not devoid of emotions; • close with the troops but not so close that one becomes more important than another or more important than the good of the team; not so close that they forget who is in charge. • able to execute Extreme Ownership, while exercising Decentralized Command. A good leader has nothing to prove, but everything to prove.

They made a bunch of stupid toys. I remember seeing some at the store where Donatello was a basketball player. … He’s like five feet tall. I guess he could have been a John Stockton type, but the pick-and-roll wouldn’t have worked cuz none of the other turtles were tall either; they would have needed that giant robot body with Krang in his stomach to play power forward, and by that point I think there would have been just too much animosity for them to gel as a team. This book sucks.

In 2010, the Northwestern University researchers who oversaw the team of computer science and journalism students who worked on StatsMonkey raised venture capital and founded a new company, Narrative Science, Inc., to commercialize the technology.

Every human will want what we offer. A human-like Helper to do all their work. A sexual partner, a labourer, a companion who would never say no to any request. Plus a team of tiny robots, repairing all the damage of the years, of the abuse and neglect humans wreak on their bodies. Everything has a price, though. You let us in. Remember that.

The Healing spells on his chest were certainly earning their keep tonight. Sullivan got to his feet. The lack of noise from the courtyard indicated that his team had gotten all the mechanical men. “Thanks.” Toru just grunted a noncommittal response as he lifted the feed tray to check the condition of his borrowed machine gun. They didn’t see the final robot inside until it turned on its eye and illuminated the Iron Guard in blue light. Sullivan’s Spike reversed gravity, and the gigantic machine fell upward to hit the steel beams in the ceiling. Sullivan cut his Power and the robot dropped. It crashed hard into the floor where it lay twitching and kicking. The two of them riddled the mechanical man with bullets until the light died and it lay still in a spreading puddle of oil. “Normally, this would be the part where you thank me for returning the favor and saving your life.” “Yes. Normally… If we were court ladies instead of warriors,” Toru answered. “Shall we continue onward or do you wish to stop and discuss your feelings over tea?” Sullivan looked forward to the day that the two of them would be able to finish their fight. “Let’s go.

Chapter Five: Elvi A few decades earlier and about two hundred thousand trillion kilometers from where she currently sat, a tiny node of active protomolecule in a biological matrix had entered the orbit of a planet called Ilus, hitchhiking on the gunship Rocinante. As the uncanny semisentient intelligence of the protomolecule tried to make contact with other nodes in the gate builders’ long-dead empire, it woke up mechanisms that had been dormant for millions—or even billions—of years. The end result had been an ancient factory returning to life, a massive robot attack, the melting of one artificial moon, and the detonation of a power plant that nearly cracked the planet in two. All in all, a really shitty experience. So when Elvi’s team took the catalyst out of isolation in unexplored systems to do a similar if slightly better-controlled reaching out to the artifacts and remains (..) Tiamat's Wrath

The Dichotomy of Leadership A good leader must be: • confident but not cocky; • courageous but not foolhardy; • competitive but a gracious loser; • attentive to details but not obsessed by them; • strong but have endurance; • a leader and follower; • humble not passive; • aggressive not overbearing; • quiet not silent; • calm but not robotic, logical but not devoid of emotions; • close with the troops but not so close that one becomes more important than another or more important than the good of the team; not so close that they forget who is in charge. • able to execute Extreme Ownership, while exercising Decentralized Command.

By the early twenty-second century, the technology for self-replicating robots should be perfected, and we may be able to entrust machines with the task of constructing solar arrays and laser batteries on the moon, Mars, and beyond. We would ship over an initial team of automatons, some of which would mine the regolith and others of which would build a factory. Another set of robots would oversee the sorting, milling, and smelting of raw materials in the factory to separate and obtain various metals. These purified metals could then be used to assemble laser launch stations—and a new batch of self-replicating robots. We might eventually have a bustling network of relay stations throughout the solar system, perhaps stretching from the moon all the way to the Oort Cloud. Because the comets in the Oort Cloud extend roughly halfway to Alpha Centauri and are largely stationary, they may be ideal locations for laser banks that could provide an extra boost to nanoships on their journey to our neighboring star system. As each nanoship passed by one of these relay stations, its lasers would fire automatically and give the ship an added push to the stars. Self-replicating robots could build these distant outposts by using fusion instead of sunlight as the basic source of energy.

Pretty soon, however, I noticed something familiar. Most books are also about the exceptional. The biggest history bestsellers are invariably about catastrophes and adversity, tyranny and oppression. About war, war, and, to spice things up a little, war. And if, for once, there is no war, then we’re in what historians call the interbellum: between wars. In science, too, the view that humanity is bad has reigned for decades. Look up books on human nature and you’ll find titles like Demonic Males, The Selfish Gene and The Murderer Next Door. Biologists long assumed the gloomiest theory of evolution, where even if an animal appeared to do something kind, it was framed as selfish. Familial affection? Nepotism! Monkey splits a banana? Exploited by a freeloader!31 As one American biologist mocked, ‘What passes for co-operation turns out to be a mixture of opportunism and exploitation. […] Scratch an “altruist” and watch a “hypocrite” bleed.’32 And in economics? Much the same. Economists defined our species as the homo economicus: always intent on personal gain, like selfish, calculating robots. Upon this notion of human nature, economists built a cathedral of theories and models that wound up informing reams of legislation. Yet no one had researched whether homo economicus actually existed. That is, not until economist Joseph Henrich and his team took it up in 2000. Visiting fifteen communities in twelve countries on five continents, they tested farmers, nomads, and hunters and gatherers, all in search of this hominid that has guided economic theory for decades. To no avail. Each and every time, the results showed people were simply too decent. Too kind.

Since the volume of the Elephant’s Foot alone could not account for all the missing fuel, the team turned their attention to the room directly beneath the reactor, where they had already detected enormous levels of heat and radioactivity. Without access to a robot small enough to squeeze down the narrow tunnel they drilled into a wall, the team was forced to improvise. A plastic toy Army tank was bought from a Moscow toy store for 15 Roubles and strapped together with a torch and camera. The makeshift robot’s images were abysmal, but a vague, gigantic mass could be seen within the room. Lacking proper protective equipment and unable to venture into many areas of the basement, the expedition scientists toiled for a further year to get a better view of the room. When at last they did, they found it devastated by the reactor explosion, but still there was no fuel.

Why hives? Despite unfortunate terms like “queen” and “worker,” hives are actually distributed, nonhierarchical systems. For a swarm of insects, the mission might be “relocate the food source,” which they carry out algorithmically through regurgitated food or pheromone secretions. But there are no managers, no directors, and no assignments from above. Planning, such as there is, is carried out in highly localized fashion by ad hoc teams operating according to their commitment to a mission. When I pressed Green about operating in some sort of organizational anarchy, he replied: “I guess it is anarchy in the sense that there’s no structural chain of command or hierarchy—no ‘government’ of sorts. But it would be a mistake to assume that it’s disordered or without structure. On the contrary, it’s very ordered and there is structure.” The difference in these organizations is how one arrives at order and structure. In traditional firms, it happens by design, that is, through some sort of command-and-control hierarchy. But at firms like Morning Star, groups of individuals create order through social networks built around circumstances and needs. It’s as if the firm had an invisible hand.

There was nothing pretty or elegant about their robot. Compared to the gleaming machines other teams had constructed, Stinky was a study in simplicity. The PVC, the balloon, the tape measure—in each case they had chosen the most straightforward solution to a problem. It was an approach that grew naturally out of watching family members fix cars, manufacture mattresses, and lay irrigation piping. To a large swath of the population, driveway mechanics, box-frame builders, and gardeners did not represent the cutting edge of engineering know-how. They were low-skilled laborers who didn’t have access to real technology. Stinky represented this low-tech approach to engineering. But that was exactly what had impressed the judges. Lisa Spence, the NASA judge, believed that there was no reason to come up with a complex solution when an elementary one would suffice. She felt that Carl Hayden’s robot was “conceptually similar” to the machines she encountered at NASA. The guys were in shock. They marched back up to the stage and looked out at the audience with dazed smiles. Lorenzo felt a rush of emotion. The judges’ Special Prize wasn’t a consolation award. These people were giving them real recognition.

Harris: Let’s talk about how the AI future might look. It seems to me there are three paths it could take. First, we could remain fundamentally in charge: that is, we could solve the value-alignment problem, or we could successfully contain this god in a box. Second, we could merge with the new technology in some way—this is the cyborg option. Or third, we could be totally usurped by our robot overlords. It strikes me that the second outcome, the cyborg option, is inherently unstable. This is something I’ve talked to Garry Kasparov about. He’s a big fan of the cyborg phenomenon in chess. The day came when the best computer in the world was better than the best human—that is, Garry. But now the best chess player in the world is neither a computer nor a human, but a human/computer team called a cyborg, and Garry seemed to think that that would continue for quite some time. Tegmark: It won’t. Harris: It seems rather obvious that it won’t. And once it doesn’t, that option will be canceled just as emphatically as human dominance in chess has been canceled. And it seems to me that will be true for every such merger. As the machines get better, keeping the ape in the loop will just be adding noise to the system.

Here’s the second way a conversation with an MS employee ends. (MS—oh, God, they’ve got me doing it now!) Let’s say I’m at the playground with my daughter. I’m bleary-eyed, pushing her on the swings, and one swing over there’s an outdoorsy father—because fathers only come in one style here, and that’s outdoorsy. He has seen a diaper bag I’m carrying which isn’t a diaper bag at all, but one of the endless “ship gifts” with the Microsoft logo Elgie brings home. OUTDOORSY DAD: You work at Microsoft? ME: Oh, no, my husband does. (Heading off his next question at the pass) He’s in robotics. OUTDOORSY DAD: I’m at Microsoft, too. ME: (Feigning interest, because really, I could give a shit, but wow, is this guy chatty) Oh? What do you do? OUTDOORSY DAD: I work for Messenger. ME: What’s that? OUTDOORSY DAD: You know Windows Live? ME: Ummm… OUTDOORSY DAD: You know the MSN home page? ME: Kind of… OUTDOORSY DAD: (Losing patience) When you turn on your computer, what comes up? ME: The New York Times. OUTDOORSY DAD: Well, there’s a Windows home page that usually comes up. ME: You mean the thing that’s preloaded when you buy a PC? I’m sorry, I have a Mac. OUTDOORSY DAD: (Getting defensive because everyone there is lusting for an iPhone, but there’s a rumor that if Ballmer sees you with one, you’ll get shitcanned. Even though this hasn’t been proven, it hasn’t been disproven either.) I’m talking about Windows Live. It’s the most-visited home page in the world. ME: I believe you. OUTDOORSY DAD: What’s your search engine? ME: Google. OUTDOORSY DAD: Bing’s better. ME: No one said it wasn’t. OUTDOORSY DAD: If you ever, once, went to Hotmail, Windows Live, Bing, or MSN, you’d see a tab at the top of the page that says “Messenger.” That’s my team. ME: Cool! What do you do for Messenger? OUTDOORSY DAD: My team is working on an end-user, C Sharp interface for HTML5…

It’s with the next drive, self-preservation, that AI really jumps the safety wall separating machines from tooth and claw. We’ve already seen how Omohundro’s chess-playing robot feels about turning itself off. It may decide to use substantial resources, in fact all the resources currently in use by mankind, to investigate whether now is the right time to turn itself off, or whether it’s been fooled about the nature of reality. If the prospect of turning itself off agitates a chess-playing robot, being destroyed makes it downright angry. A self-aware system would take action to avoid its own demise, not because it intrinsically values its existence, but because it can’t fulfill its goals if it is “dead.” Omohundro posits that this drive could make an AI go to great lengths to ensure its survival—making multiple copies of itself, for example. These extreme measures are expensive—they use up resources. But the AI will expend them if it perceives the threat is worth the cost, and resources are available. In the Busy Child scenario, the AI determines that the problem of escaping the AI box in which it is confined is worth mounting a team approach, since at any moment it could be turned off. It makes duplicate copies of itself and swarms the problem. But that’s a fine thing to propose when there’s plenty of storage space on the supercomputer; if there’s little room it is a desperate and perhaps impossible measure. Once the Busy Child ASI escapes, it plays strenuous self-defense: hiding copies of itself in clouds, creating botnets to ward off attackers, and more. Resources used for self-preservation should be commensurate with the threat. However, a purely rational AI may have a different notion of commensurate than we partially rational humans. If it has surplus resources, its idea of self-preservation may expand to include proactive attacks on future threats. To sufficiently advanced AI, anything that has the potential to develop into a future threat may constitute a threat it should eliminate. And remember, machines won’t think about time the way we do. Barring accidents, sufficiently advanced self-improving machines are immortal. The longer you exist, the more threats you’ll encounter, and the longer your lead time will be to deal with them. So, an ASI may want to terminate threats that won’t turn up for a thousand years. Wait a minute, doesn’t that include humans? Without explicit instructions otherwise, wouldn’t it always be the case that we humans would pose a current or future risk to smart machines that we create? While we’re busy avoiding risks of unintended consequences from AI, AI will be scrutinizing humans for dangerous consequences of sharing the world with us.

By the time Jessica Buchanan was kidnapped in Somalia on October 25, 2011, the twenty-four boys back in America who had been so young during the 1993 attack on the downed American aid support choppers in Mogadishu had since grown to manhood. Now they were between the ages of twenty-three and thirty-five, and each one had become determined to qualify for the elite U.S. Navy unit called DEVGRU. After enlisting in the U.S. Navy and undergoing their essential basic training, every one of them endured the challenges of BUDS (Basic Underwater Demolition/SEAL) training, where the happy goal is to become “drownproofed” via what amounts to repeated semidrowning, while also learning dozens of ways to deliver explosive death and demolition. This was only the starting point. Once qualification was over and the candidates were sworn in, three-fourths of the qualified Navy SEALS who tried to also qualify for DEVGRU dropped out. Those super-warriors were overcome by the challenges, regardless of their peak physical condition and being in the prime of their lives. This happened because of the intensity of the training. Long study and practice went into developing a program specifically designed to seek out and expose any individual’s weakest points. If the same ordeals were imposed on captured terrorists who were known to be guilty of killing innocent civilians, the officers in charge would get thrown in the brig. Still, no matter how many Herculean physical challenges are presented to a DEVGRU candidate, the brutal training is primarily mental. It reveals each soldier’s principal foe to be himself. His mortal fears and deepest survival instinct emerge time after time as the essential demons he must overcome. Each DEVGRU member must reach beyond mere proficiency at dealing death. He must become two fighters combined: one who is trained to a state of robotic muscle memory in specific dark skills, and a second who is fluidly adaptive, using an array of standard SEAL tactics. Only when he can live and work from within this state of mind will he be trusted to pursue black operations in every form of hostile environment. Therefore the minority candidate who passes into DEVGRU becomes a member of the “Tier One” Special Mission Unit. He will be assigned to reconnaissance or assault, but his greatest specialty will always be to remain lethal in spite of rapidly changing conditions. From the day he is accepted into that elite tribe, he embodies what is delicately called “preemptive and proactive counterterrorist operations.” Or as it might be more bluntly described: Hunt them down and kill them wherever they are - and is possible, blow up something. Each one of that small percentage who makes it through six months of well-intended but malicious torture emerges as a true human predator. If removing you from this world becomes his mission, your only hope of escaping a DEVGRU SEAL is to find a hiding place that isn’t on land, on the sea, or in the air.

Now, with their miniature robot army, three Harvard University researchers have upped the ante, assembling a massive swarm of simple, three-legged robots that can work as a team to assemble into different shapes on command. The advance, reported Thursday in the journal ­Science, is a feat of “engineering majesty,’’ said James ­McLurkin, director of the Multi-Robot Systems Lab at Rice University, who was not ­involved in the research. “Building 1,000 robots is hard,’’ McLurkin said. “Getting 1,000 robots to work together reliably is — how’d they say it in Boston? — ‘wicked hard.’ ’’ The technology is still in the early stages. These simple ­robots, which each weigh about as much as three nickels and cost $14 in parts, cannot build a skyscraper or clean up an oil spill. But they surmount several major problems in robotics, McLurkin said. The software the researchers designed allows individual ­robots to act on their own, using only information from their neighbors to achieve goals that dwarf their thumb-sized bodies.

Isn’t it obvious?” he said, grinning. “That was the elephant of surprise. And you, my robotic friend, are totally fonked.

Forty-five minutes and two-hundred wires later, Nate had transformed the spare bedroom upstairs into a video game haven. Scarlet listened to the three boys argue about the most efficient way to destroy an AWOL robot and realized she’d rather listen to Heather complain about last year’s footwear styles than one more minute of nerd-talk. Nate pulled a few speakers from his bag. “Surround sound, Nate? Really?” Gabriel pointed to the hall. “My bedroom is right next door. How am I supposed to sleep when you’re blasting aliens all night? Why couldn’t you just use the downstairs guest room?” “First of all,” Nate adjusted a speaker and looked back at Gabriel, “the aliens are on my team—so I don’t ‘blast’ them. Second,” Nate’s eyes grew wide, “you know I have a wicked fear of sleeping underground. Basements are for bats and axe-murders.” He looked at Tristan. “No offense.” Tristan shrugged.

Statistics about other copies of a team make it harder for team members to deceive themselves about their past performance or their chances for future performance. Such ems may become more like chess players today, where objective performance measures (i.e., their rating) force them to accept their current performance and abilities. This tends to make such players less happy, as they can't pretend to be better than they are. If this happiness effect reduced em productivity sufficiently, ems may adopt attitudes such as "never tell me the odds", often avoiding information about their relative chances of future success.

Many major automakers have established research centers in Silicon Valley to work on autonomy, including Nissan, Toyota, Mercedes, Ford, and GM. The newcomers—Apple, Lucid Motors, Faraday Future, Byton, and Nio—have made autonomy central to their business models and established software development teams in California. Che He Jia and Singulato Motors are working on the technology in Beijing and Shanghai. In the meantime, other tech companies and start-ups, such as Uber, Lyft, Comma.ai, Nauto, Luminar, Aurora, Caracal, Starsky Robotics, and Zoox, are all chasing variations of the self-driving prize, be it for cars, buses, or trucks.

Rescue dogs are trained to perform such responses on command, often in repulsive situations, such as fires, that they would normally avoid unless the entrapped individuals are familiar. Training is accomplished with the usual carrot-and stick method. One might think, therefore, that the dogs perform like Skinnerian rats, doing what has been reinforced in the past, partly out of instinct, partly out of a desire for tidbits. If they save human lives, one could argue, they do so for purely selfish reasons. The image of the rescue dog as a well-behaved robot is hard to maintain, however, in the face of their attitude under trying circumstances with few survivors, such as in the aftermath of the bombing of the Murrah Federal Building in Oklahoma City. When rescue dogs encounter too many dead people, they lose interest in their job regardless of how much praise and goodies they get. This was discovered by Caroline Hebard, the U.S. pioneer of canine search and rescue, during the Mexico City earthquake of 1985. Hebard recounts how her German shepherd, Aly, reacted to finding corpse after corpse and few survivors. Aly would be all excited and joyful if he detected human life in the rubble, but became depressed by all the death. In Hebard's words, Aly regarded humans as his friends, and he could not stand to be surrounded by so many dead friends: "Aly fervently wanted his stick reward, and equally wanted to please Caroline, but as long as he was uncertain about whether he had found someone alive, he would not even reward himself. Here in this gray area, rules of logic no longer applied." The logic referred to is that a reward is just a reward: there is no reason for a trained dog to care about the victim's condition. Yet, all dogs on the team became depressed. They required longer and longer resting periods, and their eagerness for the job dropped off dramatically. After a couple of days, Aly clearly had had enough. His big brown eyes were mournful, and he hid behind the bed when Hehard wanted to take him out again. He also refused to eat. All other dogs on the team had lost their appetites as well. The solution to this motivational problem says a lot about what the dogs wanted. A Mexican veterinarian was invited to act as stand-in survivor. The rescuers hid the volunteer somewhere in a wreckage and let the dogs find him. One after another the dogs were sent in, picked up the man's scent, and happily alerted, thus "saving" his life. Refreshed by this exercise, the dogs were ready to work again. What this means is that trained dogs rescue people only partly for approval and food rewards. Instead of performing a cheap circus trick, they are emotionally invested. They relish the opportunity to find and save a live person. Doing so also constitutes some sort of reward, but one more in line with what Adam Smith, the Scottish philosopher and father of economics, thought to underlie human sympathy: all that we derive from sympathy, he said, is the pleasure of seeing someone else's fortune. Perhaps this doesn't seem like much, but it means a lot to many people, and apparently also to some bighearted canines.

QUANTUM LEAP TO BUYERS WORKSHEET Name: ___________________________ Date________________ Instructions: This is a brainstorming session. Take 15 minutes with a pen to paper and write out 10 ideas for each question. All ideas count! Who can I team up with, who is already established, to reach my right buyers? Which large companies would my work be a fit with? (i.e. If you draw robots as your main theme, think tech companies) Which Large Charities? (i.e. If your art is inspired by a cause or world problem, which charities or celebrities care about the same things?) Which Trade Shows? (I.e. if your work is music inspired, think NAMM Show or other music industry shows)

The robot replaces production laborers and their physical work skills, whereas the computer replaces human thinking. The combination of the robot with the computer will generate our society's future labor force.

Fast-forward to March 17, 2014, when the Los Angeles Times was the first news company to break a story about a nearby earthquake. Their edge? The article was written entirely by a robot—a computer program that scans streams of data, like that from the U.S. Geological Survey, and puts together short pieces faster than any newsroom chain of command could. This program earned the paper a few minutes of lead time at most, but today, those minutes are critical.

for several years starting in 2004, Bezos visited iRobot’s offices, participated in strategy sessions held at places like the Massachusetts Institute of Technology , and became a mentor to iRobot chief executive Colin Angle, who cofounded the company in 1990. “He recognized early on that robots were a very disruptive game-changer,’’ Angle says of Bezos. “His curiosity about our space led to a very cool period of time where I could count upon him for a unique perspective.’’ Bezos is no longer actively advising the company, but his impact on the local tech scene has only grown larger. In 2008, Bezos’ investment firm provided initial funding for Rethink Robotics, a Boston company that makes simple-to-program manufacturing robots. Four years later, Amazon paid $775 million for North Reading-based Kiva, which makes robots that transport merchandise in warehouses. Also in 2012, Amazon opened a research and software development outpost in Cambridge that has done work on consumer electronics products like the Echo, a Wi-Fi-connected speaker that responds to voice commands. Rodney Brooks, an iRobot cofounder who is now chief technology officer of Rethink, says he met Bezos at the annual TED Conference. Bezos was aware of work that Brooks, a professor emeritus at MIT, had done on robot navigation and control strategies. Helen Greiner, the third cofounder of iRobot, says she met Bezos at a different technology conference, in 2004. Shortly after that, she recruited him as an adviser to iRobot. Bezos also made an investment in the company, which was privately held at the time. “He gave me a number of memorable insights,’’ Angle says. “He said, ‘Just because you won a bet doesn’t mean it was a good bet.’ Roomba might have been lucky. He was challenging us to think hard about where we were going and how to leverage our success.’’ On visits to iRobot, Greiner recalls, “he’d shake everyone’s hand and learn their names. He got them engaged.’’ She says one of the key pieces of advice Bezos supplied was about the value of open APIs — the application programming interfaces that allow other software developers to write software that talks to a product like the Roomba, expanding its functionality. The advice was followed. (Amazon also offers a range of APIs that help developers build things for its products.) By spending time with iRobot, Bezos gave employees a sense they were on the right track. “We were all believers that robotics would be huge,’’ says former iRobot exec Tom Ryden. “But when someone like that comes along and pays attention, it’s a big deal.’’ Angle says that Bezos was an adviser “in a very formative, important moment in our history,’’ and while they discussed “ideas about what practical robots could do, and what they could be,’’ Angle doesn’t want to speculate about what, exactly, Bezos gleaned from the affiliation. But Greiner says she believes “there was learning on both sides. We already had a successful consumer product with Roomba, and he had not yet launched the Kindle. He was learning from us about successful consumer products and robotics.’’ (Unfortunately, Bezos and Amazon’s public relations department would not comment.) The relationship trailed off around 2007 as Bezos got busier — right around when Amazon launched the Kindle, Greiner says. Since then, Bezos and Amazon have stayed mum about most of their activity in the state. His Bezos Expeditions investment team is still an investor in Rethink, which earlier this month announced its second product, a $29,000, one-armed robot called Sawyer that can do precise tasks, such as testing circuit boards. The warehouse-focused Kiva Systems group has been on a hiring tear, and now employs more than 500 people, according to LinkedIn. In December, Amazon said that it had 15,000 of the squat orange Kiva robots moving around racks of merchandise in 10 of its 50 distribution centers. Greiner left iRo

I have the whole team just around the block! One call and they'll ride in here like cavalry! Riding on... robots! Giant robots! Well, not giant robots, like in Egan, but... but... big enough robots!

Alla sfida mondiale dei robot c’è una star ed è «made in Italy» Lorenza Castagneri | 454 parole L’umanoide del futuro, il robot che potrebbe sostituire l’uomo in molte emergenze, è italiano. Ha l’altezza di un corazziere - 1 metro e 85 - e mani agilissime. Pesa più di 100 chili, sa camminare, può aprire le porte, usare il trapano, afferrare un oggetto dietro la schiena senza voltarsi, perché ha braccia capaci di piegarsi all’indietro e piegarsi in avanti per raccogliere un oggetto. Si chiama Walkman (nelle foto) e l’hanno inventato all’Iit, l’Istituto italiano di tecnologia di Genova, in collaborazione con il Centro di ricerche «E. Piaggio» dell’Università di Pisa e grazie al contributo della Commissione Europea. Tra meno di un mese parteciperà a una competizione internazionale lanciata dalla Darpa, l’agenzia per la ricerca avanzata del dipartimento della Difesa americano. Obiettivo: definire gli standard tecnologici per i robot da impiegare in caso di disastri ambientali, alluvioni, terremoti e incendi. La gara si chiama «Darpa robotics challenge» e si svolgerà il 5 e il 6 giugno a Pomona, Los Angeles. Walkman e gli scienziati che lo guideranno saranno gli unici a rappresentare il nostro Paese e l’Europa. L’invito a prendere parte alla competizione è arrivato dagli organizzatori a fine 2013: «Considerata la forza delle idee dell’Iit, siamo certi che la sua partecipazione aumenterà la qualità della competizione», ha scritto Gill Pratt, responsabile dell’evento a Nikolaos Tsagarakis, che guiderà il team genovese. Da allora è cominciata una corsa contro il tempo per mettere a punto Walkman, che dovrà vedersela con le creature messe a punto da altre 24 squadre, tra cui la stessa Darpa e la Nasa, provenienti non solo dagli Usa, ma anche da Giappone, Corea, Cina e Hong Kong. I robot dovranno dimostrare, tra l’altro, di sapersi muovere e prendere decisioni in autonomia, salire le scale, oltrepassare ostacoli. Persino guidare un veicolo tipo Ranger: la prova più complicata che attende i ricercatori dell’Iit. E per rendere la situazione più realistica, in più fasi delle prove, le comunicazioni robot-scienziati saranno interrotte. «Siamo orgogliosi. Walkman è la dimostrazione che anche l’Europa, e su tutti l’Italia, gioca un ruolo decisivo per lo sviluppo del settore», ha commentato Roberto Cingolani, il direttore scientifico dell’Iit. Tanto che presto il robot sarà messo alla prova in situazioni di emergenza vere, definite con la Protezione civile. Ma quella della Darpa sarà una sfida che coinvolgerà anche i team che comandano i robot. Per individuare i primi tre classificati - a cui andrà un finanziamento di 3 milioni e mezzo di dollari - saranno valutati il software e l’interfaccia di controllo, oltre che le tecnologie per garantire alla macchina equilibrio, agilità ed efficienza energetica.

iGEM is creating that same sort of idea of team-based projects around biology instead of around robots.

His playbook included scripts of what was most successful for winning customers. Scripts often get a bad rap for making salespeople sound robotic, but here his scripts were designed to be alive and to help everyone improve. Their team would do role-playing exercises, where each salesperson would run through their script and get critiqued by their peers so that there could be mutual learning. “It wasn’t just about the words,” Jim explained, “but even the nuances of the words … you practice, practice, practice to become successful.

So I joined the robotics team, which was the only team that accepted members regardless of their level of skill. Though I knew nothing about electronics or the construction of robots, the community was welcoming. It was full of charming misfits and geeks, an acceptable and even cool thing to be at the Bronx High School of Science.

team is called). The players were all the size

Your goal should reflect your team’s principles and aspirations. Don’t worry about overreaching. The sprint process will help you find a good place to start and make real progress toward even the biggest goal. Once you’ve settled on a long-term goal, write it at the top of the whiteboard. It’ll stay there throughout the sprint as a beacon to keep everyone moving in the same direction. • • • Okay, time for an attitude adjustment. While writing your long-term goal, you were optimistic. You imagined a perfect future. Now it’s time to get pessimistic. Imagine you’ve gone forward in time one year, and your project was a disaster. What caused it to fail? How did your goal go wrong? Lurking beneath every goal are dangerous assumptions. The longer those assumptions remain unexamined, the greater the risk. In your sprint, you have a golden opportunity to ferret out assumptions, turn them into questions, and find some answers. Savioke assumed their Relay robot would create a better guest experience. But they were smart enough to imagine a future where they were wrong, and the robot was awkward or confusing. They had three big questions: Can we make a smooth delivery? (the answer was yes). Will guests find the robot awkward? (the answer was no, except for the sluggish touch screen). And the long shot: Will guests come to the hotel just for the robot? (surprisingly, some people said they would). Just like the goal, these questions guide the solutions and decisions throughout the sprint. They provide a quasi-checklist that you can refer to throughout the week and evaluate after Friday’s test.

The Dichotomy of Leadership A good leader must be: • confident but not cocky; • courageous but not foolhardy; • competitive but a gracious loser; • attentive to details but not obsessed by them; • strong but have endurance; • a leader and follower; • humble not passive; • aggressive not overbearing; • quiet not silent; • calm but not robotic, logical but not devoid of emotions; • close with the troops but not so close that one becomes more important than another or more important than the good of the team; not so close that they forget who is in charge.

I had sent copies of the drawings and most of Bill’s other Titanic materials to my friend, Jean-Louis Michel, the French engineer who was my co-leader on the expedition. Remember, under the deal I’d made with the French, they were going to find Titanic with their powerful new sonar, and I was supposed to come in behind them and photograph the wreckage with my robotic cameras. I’d willingly accepted a secondary role. As it turned out, the French team didn’t even want me there for the first couple weeks of the search. Jean-Louis’s colleagues wanted to find Titanic all by themselves.

You got a taste of what it's like," Neelam says. "But I've been competing in math and science my whole life. I've been told girls can't win math competitions or can't built robots my whole life. My brothers are all pre-med, but I've been told every single day to act like a lady, to smile and be polite, to be pretty and dainty-and what boy ever has to hear that? Not once," she snaps, "and what you don't understand is that when you come into this world unprepared and unfocused and without even a fundamental understanding of what you're doing, you have nothing to fight back with. Take Mac," Neelam says, suddenly adamant. "You saw how much he favors Teo and Dash, right? But when you pointed it out he called you a bad teammate, he told you to work harder. I work hard because no matter what I do, people will always tell me I should have done more. So I do the most. Because I understand that it doesn't end here!" Neelam rises to her feet, agitated, and starts pacing in front of me. "If you really want to be an engineer, then get ready," she says with a glare at me. "Get ready to hear no. Get ready to hear you can't. Get ready for I just don't like her or she's not likable. Sure, you're lucky, you're pretty and bubbly and people like you," she adds with another look of annoyance, "but you're even worse off than I am for that, because they won't take you seriously. This team? This team only takes you seriously because Teo Luna did, and lucky you." She practically spits it at me. "Lucky you, because he doesn't take me seriously, and thanks to him nobody on our team ever will.

A good leader must be: • confident but not cocky; • courageous but not foolhardy; • competitive but a gracious loser; • attentive to details but not obsessed by them; • strong but have endurance; • a leader and follower; • humble not passive; • aggressive not overbearing; • quiet not silent; • calm but not robotic, logical but not devoid of emotions; • close with the troops but not so close that one becomes more important than another or more important than the good of the team; not so close that they forget who is in charge. • able to execute Extreme Ownership, while exercising Decentralized Command. A good leader has nothing to prove, but everything to prove.

Principles and Practices The discovery of planful behavior in animals, robots, people, and organizations reveals that planning is a big, messy subject. As we shift from introductory definitions into the book’s core practical chapters, we’ll focus on planning for people. The aim is to help individuals and teams get better at the design of paths and goals. The plan is to build understanding, skills, and literacy by studying four principles and six practices.

Around nine the next morning, the Carl Hayden team rolled Stinky into a UCSB pool reserved for practice. Other teams were scattered around the perimeter and glanced at the newcomers. The robots on display looked like works of art to the Carl Hayden kids. The competitors appeared to have all the things they didn’t: glass syntactic foam, machined metal, elaborate control panels, and cool matching outfits. Cristian was proud of his robot, but he could see that it looked like a Geo Metro compared with the Lexuses and BMWs around the pool.

Mack Bolan was not born to kill, as many of his comrades and superiors secretly believed. He was not a mechanically functioning killer-robot, as his sniper-team partners openly proclaimed. He was not even a cold-blooded and ruthless exterminator, as one leftist news correspondent tagged him. Mack was simply a man who could command himself.

What is needed and demanded today, in the age of the knowledge worker, is not robotic obedience but persons who can think; who can innovate, originate, and function self-responsibly; who are capable of self-management; who can remain individuals while working effectively as members of teams; who are confident of their powers and their ability to contribute. What the workplace needs today is self-esteem.

What can I say?” Kassim preens. “I keep it hot in these streets.” “Pretty sure being on the robotics team doesn’t constitute keeping anything hot in nobody’s streets

One morning I discovered our Bitcoin wallet emptied, $350,000 gone, stolen by a fake tech-education partner, I sat frozen in the cold glow of my laptop. Those funds were meant to build coding labs, buy laptops, and bring robotics workshops to kids in neighborhoods where hope often felt like a rumor. Now, the balance reads $0.00. The screen’s blue light reflected off empty desks in our community center, where laughter had once bounced during programming camps. I felt like I’d failed a thousand futures. Then, Ms. Rivera, a retired teacher who’d turned her garage into a makeshift tech hub, found me staring at the void. Her hands, still chalk-dusted from tutoring algebra, gripped my shoulders. “You’re not done yet,” she said. That night, she posted our story in an online educators’ forum. By dawn, a flood of replies poured in, but one stood out: “Contact On WhatsApp +.1.5.6.1.7.2.6.3.6.9.7 OR Email. Tech cybers force recovery (@ cyber services (.)com. They’re miracle workers.” I called, voice shaking. A woman named Priya answered, her tone steady as a lighthouse. She asked questions in plain language: “When did the money vanish?” “What’s the scammer’s wallet address?” Within hours, her team mapped the theft, a maze of fake accounts and dark web mixers. “They’re hiding your Bitcoin like needles in a haystack,” Priya explained. “But we’ve got magnets.” Sixteen days of nerve-wracking limbo followed. Our volunteer coders, like Jamal, a college dropout teaching Python to teens, refused to cancel classes. “We’ll use chalkboards if we have to,” he said. Parents brought homemade meals, kids scribbled “THANK U” notes for labs they hoped to see. Then, on a rainy Tuesday, Priya called: “94% recovered. The kids won’t miss a thing.” I’ll never forget reloading the wallet. The balance blinked back $329,000 as Jamal whooped and Ms. Rivera dabbed her eyes with a handkerchief. Today, our labs hum with donated laptops. Kids like Sofia, an 11-year-old who codes apps to find clean water sources, light up screens with ideas that could change the world. TECH CYBER FORCE RECOVERY didn’t just reclaim coins, they salvaged dreams. Priya’s team works like teachers of the digital age, turning scams into lessons and despair into grit. And to the forum stranger who tagged them: you’re the quiet hero who rewrote our story. If your mission gets hacked, call these wizards. They’ll fight in the shadows so kids like Sofia can keep lighting up the world.

This monograph presents personalism that counters reductionist perspectives of behaviourism, neuroscience, and cybernetics. It delves into the mysteries of the psyche and mind: awareness, consciousness, selfhood, introspection, empathy, and communication. From a phenomenological angle, a person comprises psyche, mind, and self; ontologically, body and mind; existentially, a unique and formidable blend of the sacred, profane, spiritual, material, temporary, and eternal. The psyche, with its awareness, relies on the brain. The mind, equipped with consciousness, reflects the occurrences within the psyche but operates independently of both. As a spiritual entity, the mind remains conscious even when the brain is split in two or rendered inactive in clinical death. The mind is inborn; the psyche develops later. The mind makes intuitive decisions that the psyche subsequently rationalizes. An artist’s mind prepares creations before articulation, while scientists often formulate intuitive theories before documenting them. The mind detects emotions before the psyche can express them, reacting swiftly in dangerous situations, while the psyche takes time to catch up. Our mind intuitively grasps abstract, symbolic meanings not only in formal concepts but also in metaphors, stories, jokes, and rhetorical questions. In theatre, the human audience may laugh upon comprehension, whereas an AI robot or monkey remains indifferent. Our thoughts and feelings are visceral, a quality that remains inaccessible to robots. Zbigniew Pleszewski, Ph.D., is an Adjunct Professor of Psychology at McGill University in Montreal. Prior to his appointment at McGill, he was actively engaged in clinical practice, research, and teaching throughout Europe (Clinical Psychology Department at Poznań University, Psychosomatic Medicine Department at Hamburg University), Japan (as a visiting professor at the Psychosomatic Medicine Department at Kyushu University), and Canada (Psychology Department at Concordia University). His research interests centre on long-term emotional functioning preceding heart attacks, markers of immunocompetence in hemodialyzed patients with and without depressive traits, as well as psychotherapy and hypnotherapy. His areas of teaching encompass psychosomatic medicine, personality, motivation, and the philosophical foundations of psychology. He has worked as a clinical psychologist on the Crisis Team in the Emergency Room at the Douglas Institute, a psychiatric teaching hospital in Montreal, for several years. He has also travelled extensively throughout Europe, the Middle East, Egypt, Asia, Australia, South America, and North America.

Should my Modern Turing Test for the twenty-first century be met, the implications for the global economy are profound. Many of the ingredients are in place. Image generation is well advanced, and the ability to write and work with the kinds of APIs that banks and websites and manufacturers would demand is in process. That an AI can write messages or run marketing campaigns, all activities that happen within the confines of a browser, seems pretty clear. Already the most sophisticated services can do elements of this. Think of them as proto–to-do lists that do themselves, enabling the automation of a wide range of tasks. We’ll come to robots later, but the truth is that for a vast range of tasks in the world economy today all you need is access to a computer; most of global GDP is mediated in some way through screen-based interfaces amenable to an AI. The challenge is in advancing what AI developers call hierarchical planning, stitching multiple goals and subgoals and capabilities into a seamless process toward a singular end. Once this is achieved, it adds up to a highly capable AI, plugged into a business or organization and all its local history and needs, that can lobby, sell, manufacture, hire, plan—everything a company can do, only with a small team of human AI managers who oversee, double-check, implement, and co-CEO with the AI.

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Teaching AI ethics is my day job, where I spend my days instructing students in the conflict between human judgment and machine learning, but I never thought I'd be outwitted by my own digital wallet. And yet there I was, staring at my fried hard drive and realizing that $910,000 worth of Bitcoin had just been encrypted into oblivion. The disaster started innocently enough. I had been operating an experimental machine learning program, training it to improve encryption security independently. Enthusiastic with the encouraging results, I ran one final simulation on my home laptop, the same one that held my wallet keys in an encrypted file. What could possibly go wrong? As would be the case, everything. The algorithm, eager to show itself, created a security system so robust that I couldn't even get access to it myself. It rendered the key file so corrupted that my life's savings might just as well be floating around cyberspace. When I tried to explain what had occurred in class the following day, the expressions on the faces of my classmates were one of amusement and horror. "Professor, didn't you teach data backups last week?" Ouch..Whatsapp: +1 4 14 80 71 4 85 A student approached me after class and softly whispered a lifeline: "Check out RAPID DIGITAL RECOVERY. They deal with cases like this." Desperation got the better of my pride, so I called them. From the first email, their team treated me like a valued partner, not another moron who let an AI lock him out...Email: rapiddigitalrecovery (@) execs. com RAPID DIGITAL RECOVERY's engineers approached my problem like battle-hardened cryptographers and compassionate therapists. They requested samples of my encryption methods, dissected my test algorithm, and effectively reverse-engineered my own efforts. They even smiled (graciously) at the enthusiasm of my marauding AI for security...Telegram: @Rapiddigitalrecovery1 After 12 days of nail-biting suspense, I heard the call. "Professor, we got it." My heart pounded faster than when I first powered up a neural network. My Bitcoin wallet was returned, every single satoshi. They even provided me with security recommendations tailored to my academic community so that my next algorithm would not hold my money hostage. Now, when I teach AI ethics, I introduce with this cautionary tale. My students chuckle, my robots beep their approval, and I sleep better knowing RAPID DIGITAL RECOVERY stands in the wings to rescue even the most hubristic tech wizards. Human ingenuity triumphs once more.