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#431412 3 Dangerous Ideas From Ray Kurzweil
Recently, I interviewed my friend Ray Kurzweil at the Googleplex for a 90-minute webinar on disruptive and dangerous ideas, a prelude to my fireside chat with Ray at Abundance 360 this January.
Ray is my friend and cofounder and chancellor of Singularity University. He is also an XPRIZE trustee, a director of engineering at Google, and one of the best predictors of our exponential future.
It’s my pleasure to share with you three compelling ideas that came from our conversation.
1. The nation-state will soon be irrelevant.
Historically, we humans don’t like change. We like waking up in the morning and knowing that the world is the same as the night before.
That’s one reason why government institutions exist: to stabilize society.
But how will this change in 20 or 30 years? What role will stabilizing institutions play in a world of continuous, accelerating change?
“Institutions stick around, but they change their role in our lives,” Ray explained. “They already have. The nation-state is not as profound as it was. Religion used to direct every aspect of your life, minute to minute. It’s still important in some ways, but it’s much less important, much less pervasive. [It] plays a much smaller role in most people’s lives than it did, and the same is true for governments.”
Ray continues: “We are fantastically interconnected already. Nation-states are not islands anymore. So we’re already much more of a global community. The generation growing up today really feels like world citizens much more than ever before, because they’re talking to people all over the world, and it’s not a novelty.”
I’ve previously shared my belief that national borders have become extremely porous, with ideas, people, capital, and technology rapidly flowing between nations. In decades past, your cultural identity was tied to your birthplace. In the decades ahead, your identify is more a function of many other external factors. If you love space, you’ll be connected with fellow space-cadets around the globe more than you’ll be tied to someone born next door.
2. We’ll hit longevity escape velocity before we realize we’ve hit it.
Ray and I share a passion for extending the healthy human lifespan.
I frequently discuss Ray’s concept of “longevity escape velocity”—the point at which, for every year that you’re alive, science is able to extend your life for more than a year.
Scientists are continually extending the human lifespan, helping us cure heart disease, cancer, and eventually, neurodegenerative disease. This will keep accelerating as technology improves.
During my discussion with Ray, I asked him when he expects we’ll reach “escape velocity…”
His answer? “I predict it’s likely just another 10 to 12 years before the general public will hit longevity escape velocity.”
“At that point, biotechnology is going to have taken over medicine,” Ray added. “The next decade is going to be a profound revolution.”
From there, Ray predicts that nanorobots will “basically finish the job of the immune system,” with the ability to seek and destroy cancerous cells and repair damaged organs.
As we head into this sci-fi-like future, your most important job for the next 15 years is to stay alive. “Wear your seatbelt until we get the self-driving cars going,” Ray jokes.
The implications to society will be profound. While the scarcity-minded in government will react saying, “Social Security will be destroyed,” the more abundance-minded will realize that extending a person’s productive earning life space from 65 to 75 or 85 years old would be a massive boon to GDP.
3. Technology will help us define and actualize human freedoms.
The third dangerous idea from my conversation with Ray is about how technology will enhance our humanity, not detract from it.
You may have heard critics complain that technology is making us less human and increasingly disconnected.
Ray and I share a slightly different viewpoint: that technology enables us to tap into the very essence of what it means to be human.
“I don’t think humans even have to be biological,” explained Ray. “I think humans are the species that changes who we are.”
Ray argues that this began when humans developed the earliest technologies—fire and stone tools. These tools gave people new capabilities and became extensions of our physical bodies.
At its base level, technology is the means by which we change our environment and change ourselves. This will continue, even as the technologies themselves evolve.
“People say, ‘Well, do I really want to become part machine?’ You’re not even going to notice it,” Ray says, “because it’s going to be a sensible thing to do at each point.”
Today, we take medicine to fight disease and maintain good health and would likely consider it irresponsible if someone refused to take a proven, life-saving medicine.
In the future, this will still happen—except the medicine might have nanobots that can target disease or will also improve your memory so you can recall things more easily.
And because this new medicine works so well for so many, public perception will change. Eventually, it will become the norm… as ubiquitous as penicillin and ibuprofen are today.
In this way, ingesting nanorobots, uploading your brain to the cloud, and using devices like smart contact lenses can help humans become, well, better at being human.
Ray sums it up: “We are the species that changes who we are to become smarter and more profound, more beautiful, more creative, more musical, funnier, sexier.”
Speaking of sexuality and beauty, Ray also sees technology expanding these concepts. “In virtual reality, you can be someone else. Right now, actually changing your gender in real reality is a pretty significant, profound process, but you could do it in virtual reality much more easily and you can be someone else. A couple could become each other and discover their relationship from the other’s perspective.”
In the 2030s, when Ray predicts sensor-laden nanorobots will be able to go inside the nervous system, virtual or augmented reality will become exceptionally realistic, enabling us to “be someone else and have other kinds of experiences.”
Why Dangerous Ideas Matter
Why is it so important to discuss dangerous ideas?
I often say that the day before something is a breakthrough, it’s a crazy idea.
By consuming and considering a steady diet of “crazy ideas,” you train yourself to think bigger and bolder, a critical requirement for making impact.
As humans, we are linear and scarcity-minded.
As entrepreneurs, we must think exponentially and abundantly.
At the end of the day, the formula for a true breakthrough is equal to “having a crazy idea” you believe in, plus the passion to pursue that idea against all naysayers and obstacles.
Image Credit: Tithi Luadthong / Shutterstock.com Continue reading
Posted in Human Robots
#431371 Amazon Is Quietly Building the Robots of ...
Science fiction is the siren song of hard science. How many innocent young students have been lured into complex, abstract science, technology, engineering, or mathematics because of a reckless and irresponsible exposure to Arthur C. Clarke at a tender age? Yet Arthur C. Clarke has a very famous quote: “Any sufficiently advanced technology is indistinguishable from magic.”
It’s the prospect of making that… ahem… magic leap that entices so many people into STEM in the first place. A magic leap that would change the world. How about, for example, having humanoid robots? They could match us in dexterity and speed, perceive the world around them as we do, and be programmed to do, well, more or less anything we can do.
Such a technology would change the world forever.
But how will it arrive? While true sci-fi robots won’t get here right away—the pieces are coming together, and the company best developing them at the moment is Amazon. Where others have struggled to succeed, Amazon has been quietly progressing. Notably, Amazon has more than just a dream, it has the most practical of reasons driving it into robotics.
This practicality matters. Technological development rarely proceeds by magic; it’s a process filled with twists, turns, dead-ends, and financial constraints. New technologies often have to answer questions like “What is this good for, are you being realistic?” A good strategy, then, can be to build something more limited than your initial ambition, but useful for a niche market. That way, you can produce a prototype, have a reasonable business plan, and turn a profit within a decade. You might call these “stepping stone” applications that allow for new technologies to be developed in an economically viable way.
You need something you can sell to someone, soon: that’s how you get investment in your idea. It’s this model that iRobot, developers of the Roomba, used: migrating from military prototypes to robotic vacuum cleaners to become the “boring, successful robot company.” Compare this to Willow Garage, a genius factory if ever there was one: they clearly had ambitions towards a general-purpose, multi-functional robot. They built an impressive device—PR2—and programmed the operating system, ROS, that is still the industry and academic standard to this day.
But since they were unable to sell their robot for much less than $250,000, it was never likely to be a profitable business. This is why Willow Garage is no more, and many workers at the company went into telepresence robotics. Telepresence is essentially videoconferencing with a fancy robot attached to move the camera around. It uses some of the same software (for example, navigation and mapping) without requiring you to solve difficult problems of full autonomy for the robot, or manipulating its environment. It’s certainly one of the stepping-stone areas that various companies are investigating.
Another approach is to go to the people with very high research budgets: the military.
This was the Boston Dynamics approach, and their incredible achievements in bipedal locomotion saw them getting snapped up by Google. There was a great deal of excitement and speculation about Google’s “nightmare factory” whenever a new slick video of a futuristic militarized robot surfaced. But Google broadly backed away from Replicant, their robotics program, and Boston Dynamics was sold. This was partly due to PR concerns over the Terminator-esque designs, but partly because they didn’t see the robotics division turning a profit. They hadn’t found their stepping stones.
This is where Amazon comes in. Why Amazon? First off, they just announced that their profits are up by 30 percent, and yet the company is well-known for their constantly-moving Day One philosophy where a great deal of the profits are reinvested back into the business. But lots of companies have ambition.
One thing Amazon has that few other corporations have, as well as big financial resources, is viable stepping stones for developing the technologies needed for this sort of robotics to become a reality. They already employ 100,000 robots: these are of the “pragmatic, boring, useful” kind that we’ve profiled, which move around the shelves in warehouses. These robots are allowing Amazon to develop localization and mapping software for robots that can autonomously navigate in the simple warehouse environment.
But their ambitions don’t end there. The Amazon Robotics Challenge is a multi-million dollar competition, open to university teams, to produce a robot that can pick and package items in warehouses. The problem of grasping and manipulating a range of objects is not a solved one in robotics, so this work is still done by humans—yet it’s absolutely fundamental for any sci-fi dream robot.
Google, for example, attempted to solve this problem by hooking up 14 robot hands to machine learning algorithms and having them grasp thousands of objects. Although results were promising, the 10 to 20 percent failure rate for grasps is too high for warehouse use. This is a perfect stepping stone for Amazon; should they crack the problem, they will likely save millions in logistics.
Another area where humanoid robotics—especially bipedal locomotion, or walking, has been seriously suggested—is in the last mile delivery problem. Amazon has shown willingness to be creative in this department with their notorious drone delivery service. In other words, it’s all very well to have your self-driving car or van deliver packages to people’s doors, but who puts the package on the doorstep? It’s difficult for wheeled robots to navigate the full range of built environments that exist. That’s why bipedal robots like CASSIE, developed by Oregon State, may one day be used to deliver parcels.
Again: no one more than Amazon stands to profit from cracking this technology. The line from robotics research to profit is very clear.
So, perhaps one day Amazon will have robots that can move around and manipulate their environments. But they’re also working on intelligence that will guide those robots and make them truly useful for a variety of tasks. Amazon has an AI, or at least the framework for an AI: it’s called Alexa, and it’s in tens of millions of homes. The Alexa Prize, another multi-million-dollar competition, is attempting to make Alexa more social.
To develop a conversational AI, at least using the current methods of machine learning, you need data on tens of millions of conversations. You need to understand how people will try to interact with the AI. Amazon has access to this in Alexa, and they’re using it. As owners of the leading voice-activated personal assistant, they have an ecosystem of developers creating apps for Alexa. It will be integrated with the smart home and the Internet of Things. It is a very marketable product, a stepping stone for robot intelligence.
What’s more, the company can benefit from its huge sales infrastructure. For Amazon, having an AI in your home is ideal, because it can persuade you to buy more products through its website. Unlike companies like Google, Amazon has an easy way to make a direct profit from IoT devices, which could fuel funding.
For a humanoid robot to be truly useful, though, it will need vision and intelligence. It will have to understand and interpret its environment, and react accordingly. The way humans learn about our environment is by getting out and seeing it. This is something that, for example, an Alexa coupled to smart glasses would be very capable of doing. There are rumors that Alexa’s AI will soon be used in security cameras, which is an ideal stepping stone task to train an AI to process images from its environment, truly perceiving the world and any threats it might contain.
It’s a slight exaggeration to say that Amazon is in the process of building a secret robot army. The gulf between our sci-fi vision of robots that can intelligently serve us, rather than mindlessly assemble cars, is still vast. But in quietly assembling many of the technologies needed for intelligent, multi-purpose robotics—and with the unique stepping stones they have along the way—Amazon might just be poised to leap that gulf. As if by magic.
Image Credit: Denis Starostin / Shutterstock.com Continue reading
Posted in Human Robots
#430743 Teaching Machines to Understand, and ...
We humans are swamped with text. It’s not just news and other timely information: Regular people are drowning in legal documents. The problem is so bad we mostly ignore it. Every time a person uses a store’s loyalty rewards card or connects to an online service, his or her activities are governed by the equivalent of hundreds of pages of legalese. Most people pay no attention to these massive documents, often labeled “terms of service,” “user agreement,” or “privacy policy.”
These are just part of a much wider societal problem of information overload. There is so much data stored—exabytes of it, as much stored as has ever been spoken by people in all of human history—that it’s humanly impossible to read and interpret everything. Often, we narrow down our pool of information by choosing particular topics or issues to pay attention to. But it’s important to actually know the meaning and contents of the legal documents that govern how our data is stored and who can see it.
As computer science researchers, we are working on ways artificial intelligence algorithms could digest these massive texts and extract their meaning, presenting it in terms regular people can understand.
Can computers understand text?
Computers store data as 0s and 1s—data that cannot be directly understood by humans. They interpret these data as instructions for displaying text, sound, images, or videos that are meaningful to people. But can computers actually understand the language, not only presenting the words but also their meaning?
One way to find out is to ask computers to summarize their knowledge in ways that people can understand and find useful. It would be best if AI systems could process text quickly enough to help people make decisions as they are needed—for example, when you’re signing up for a new online service and are asked to agree with the site’s privacy policy.
What if a computerized assistant could digest all that legal jargon in a few seconds and highlight key points? Perhaps a user could even tell the automated assistant to pay particular attention to certain issues, like when an email address is shared, or whether search engines can index personal posts. Companies could use this capability, too, to analyze contracts or other lengthy documents.
To do this sort of work, we need to combine a range of AI technologies, including machine learning algorithms that take in large amounts of data and independently identify connections among them; knowledge representation techniques to express and interpret facts and rules about the world; speech recognition systems to convert spoken language to text; and human language comprehension programs that process the text and its context to determine what the user is telling the system to do.
Examining privacy policies
A modern internet-enabled life today more or less requires trusting for-profit companies with private information (like physical and email addresses, credit card numbers and bank account details) and personal data (photos and videos, email messages and location information).
These companies’ cloud-based systems typically keep multiple copies of users’ data as part of backup plans to prevent service outages. That means there are more potential targets—each data center must be securely protected both physically and electronically. Of course, internet companies recognize customers’ concerns and employ security teams to protect users’ data. But the specific and detailed legal obligations they undertake to do that are found in their impenetrable privacy policies. No regular human—and perhaps even no single attorney—can truly understand them.
In our study, we ask computers to summarize the terms and conditions regular users say they agree to when they click “Accept” or “Agree” buttons for online services. We downloaded the publicly available privacy policies of various internet companies, including Amazon AWS, Facebook, Google, HP, Oracle, PayPal, Salesforce, Snapchat, Twitter, and WhatsApp.
Summarizing meaning
Our software examines the text and uses information extraction techniques to identify key information specifying the legal rights, obligations and prohibitions identified in the document. It also uses linguistic analysis to identify whether each rule applies to the service provider, the user or a third-party entity, such as advertisers and marketing companies. Then it presents that information in clear, direct, human-readable statements.
For example, our system identified one aspect of Amazon’s privacy policy as telling a user, “You can choose not to provide certain information, but then you might not be able to take advantage of many of our features.” Another aspect of that policy was described as “We may also collect technical information to help us identify your device for fraud prevention and diagnostic purposes.”
We also found, with the help of the summarizing system, that privacy policies often include rules for third parties—companies that aren’t the service provider or the user—that people might not even know are involved in data storage and retrieval.
The largest number of rules in privacy policies—43 percent—apply to the company providing the service. Just under a quarter of the rules—24 percent—create obligations for users and customers. The rest of the rules govern behavior by third-party services or corporate partners, or could not be categorized by our system.
The next time you click the “I Agree” button, be aware that you may be agreeing to share your data with other hidden companies who will be analyzing it.
We are continuing to improve our ability to succinctly and accurately summarize complex privacy policy documents in ways that people can understand and use to access the risks associated with using a service.
This article was originally published on The Conversation. Read the original article. Continue reading
Posted in Human Robots
#428173 Next-Gen Robotics & Automation: ...
PRESS RELEASE:
The fall in price of next-generation robots from hundreds to tens of thousands of pounds means that the business case just became stronger for automotive vehicle and parts manufacturers to implement robotic solutions across individual manufacturing lines.
Challenges and pitfalls remain though, with nearly 76% of the target audience lacking clarity on robotic capabilities and implementation best practice. From how to prepare process for automation, to the individual capabilities of each type of robot for individual production lines, OEMs need to know the next best step.
This year’s must attend Next-Generation Robotics & Automation: Automotive Manufacturing Europe 2016 Summit will be the only event focused on robotic upgrade and innovation, specifically for the automotive industry.
Co-located with our UK flagship Joining, Forming & Manufacturing Technologies Summit, on 29th-30th November, at the VOX in Birmingham, this must attend event addresses how to retain cutting edge in automotive manufacturing and the tactics needed to get next-generation robots right, first time.
Reasons To Attend:
The Only European Robotics Event Dedicated To The Automotive Industry
Discuss selection and implementation challenges specific to your sector:
8+ Robotic Capabilities Case Studies – Comprehensive access to exclusive manufacturer perspectives on Next-Generation Robotic applications – direct from the plant
5 Process Specific Breakout Groups – Grapple with application, maintenance & selection considerations particular to your production process: Body Shop, Paint Shop, Power Train & Final Assembly
4 Robot-Type Deep Dive Discussion Groups – Discuss with peers the capabilities and attributes of each specific next-generation robot type to address their relevance to your needs: Zero Speed Monitoring, Power & Force Limited, Speed & Separation & Hand Guided Robots
Strategic & Technical Focus – A blended programme offers access to business case and strategic considerations, as well as tactical robotic application techniques
Speakers Include:
Willem Grobler, Technology Project Leader, BMW
Rich McDonnell, Senior Manufacturing Manager TS-22,
Jaguar XE & F-Pace Body Construction, Jaguar Land Rover
Dan Lämkull , Methods Developer, Volvo Car Corporation
Ali Ackay, Control Technologies & Robotics – Manufacturing Engineering Development, Daimler AG & Mercedes-Benz Trucks
Register today to profit from the Super Early Bird Discount, and reserve your place at the innovation hub of the European Automotive sector in time!
The post Next-Gen Robotics & Automation: Automotive Manufacturing Europe 2016 appeared first on Roboticmagazine. Continue reading
Posted in Human Robots