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#435119 Are These Robots Better Than You at ...

Posted on May 20, 2019 by Android

Robot technology is evolving at breakneck speed. SoftBank’s Pepper is found in companies across the globe and is rapidly improving its conversation skills. Telepresence robots open up new opportunities for remote working, while Boston Dynamics’ Handle robot could soon (literally) take a load off human colleagues in warehouses.

But warehouses and offices aren’t the only places where robots are lining up next to humans.

Toyota’s Cue 3 robot recently showed off its basketball skills, putting up better numbers than the NBA’s most accurate three-point shooter, the Golden State Warriors’ Steph Curry.

Cue 3 is still some way from being ready to take on Curry, or even amateur basketball players, in a real game. However, it is the latest member of a growing cast of robots challenging human dominance in sports.

As these robots continue to develop, they not only exemplify the speed of exponential technology development, but also how those technologies are improving human capabilities.

Meet the Contestants
The list of robots in sports is surprisingly long and diverse. There are robot skiers, tumblers, soccer players, sumos, and even robot game jockeys. Introductions to a few of them are in order.

Robot: Forpheus
Sport: Table tennis
Intro: Looks like something out of War of the Worlds equipped with a ping pong bat instead of a death ray.
Ability level: Capable of counteracting spin shots and good enough to beat many beginners.

Robot: Sumo bot
Sport: Sumo wrestling
Intro: Hyper-fast, hyper-aggressive. Think robot equivalent to an angry wasp on six cans of Red Bull crossed with a very small tank.
Ability level: Flies around the ring way faster than any human sumo. Tend to drive straight out of the ring at times.

Robot: Cue 3
Sport: Basketball
Intro: Stands at an imposing 6 foot and 10 inches, so pretty much built for the NBA. Looks a bit like something that belongs in a video game.
Ability level: A 62.5 percent three-pointer percentage, which is better than Steph Curry’s; is less mobile than Charles Barkley – in his current form.

Robot: Robo Cup Robots
Intro: The future of soccer. If everything goes to plan, a team of robots will take on the Lionel Messis and Cristiano Ronaldos of 2050 and beat them in a full 11 vs. 11 game.
Ability level: Currently plays soccer more like the six-year-olds I used to coach than Lionel Messi.

The Limiting Factor
The skill level of all the robots above is impressive, and they are doing things that no human contestant can. The sumo bots’ inhuman speed is self-evident. Forpheus’ ability to track the ball with two cameras while simultaneously tracking its opponent with two other cameras requires a look at the spec sheet, but is similarly beyond human capability. While Cue 3 can’t move, it makes shots from the mid-court logo look easy.

Robots are performing at a level that was confined to the realm of science fiction at the start of the millennium. The speed of development indicates that in the near future, my national team soccer coach would likely call up a robot instead of me (he must have lost my number since he hasn’t done so yet. It’s the only logical explanation), and he’d be right to do so.

It is also worth considering that many current sports robots have a humanoid form, which limits their ability. If engineers were to optimize robot design to outperform humans in specific categories, many world champions would likely already be metallic.

Swimming is perhaps one of the most obvious. Even Michael Phelps would struggle to keep up with a torpedo-shaped robot, and if you beefed up a sumo robot to human size, human sumos might impress you by running away from them with a 100-meter speed close to Usain Bolt’s.

In other areas, the playing field for humans and robots is rapidly leveling. One likely candidate for the first head-to-head competitions is racing, where self-driving cars from the Roborace League could perhaps soon be ready to race the likes of Lewis Hamilton.

Tech Pushing Humans
Perhaps one of the biggest reasons why it may still take some time for robots to surpass us is that they, along with other exponential technologies, are already making us better at sports.

In Japan, elite volleyball players use a robot to practice their attacks. Some American football players also practice against robot opponents and hone their skills using VR.

On the sidelines, AI is being used to analyze and improve athletes’ performance, and we may soon see the first AI coaches, not to mention referees.

We may even compete in games dreamt up by our electronic cousins. SpeedGate, a new game created by an AI by studying 400 different sports, is a prime example of that quickly becoming a possibility.

However, we will likely still need to make the final call on what constitutes a good game. The AI that created SpeedGate reportedly also suggested less suitable pastimes, like underwater parkour and a game that featured exploding frisbees. Both of these could be fun…but only if you’re as sturdy as a robot.

Image Credit: RoboCup Standard Platform League 2018, ©The Robocup Federation. Published with permission of reproduction granted by the RoboCup Federation. Continue reading →

Posted in Human Robots

#434616 What Games Are Humans Still Better at ...

Posted on February 10, 2019 by Android

Artificial intelligence (AI) systems’ rapid advances are continually crossing rows off the list of things humans do better than our computer compatriots.

AI has bested us at board games like chess and Go, and set astronomically high scores in classic computer games like Ms. Pacman. More complex games form part of AI’s next frontier.

While a team of AI bots developed by OpenAI, known as the OpenAI Five, ultimately lost to a team of professional players last year, they have since been running rampant against human opponents in Dota 2. Not to be outdone, Google’s DeepMind AI recently took on—and beat—several professional players at StarCraft II.

These victories beg the questions: what games are humans still better at than AI? And for how long?

The Making Of AlphaStar
DeepMind’s results provide a good starting point in a search for answers. The version of its AI for StarCraft II, dubbed AlphaStar, learned to play the games through supervised learning and reinforcement learning.

First, AI agents were trained by analyzing and copying human players, learning basic strategies. The initial agents then played each other in a sort of virtual death match where the strongest agents stayed on. New iterations of the agents were developed and entered the competition. Over time, the agents became better and better at the game, learning new strategies and tactics along the way.

One of the advantages of AI is that it can go through this kind of process at superspeed and quickly develop better agents. DeepMind researchers estimate that the AlphaStar agents went through the equivalent of roughly 200 years of game time in about 14 days.

Cheating or One Hand Behind the Back?
The AlphaStar AI agents faced off against human professional players in a series of games streamed on YouTube and Twitch. The AIs trounced their human opponents, winning ten games on the trot, before pro player Grzegorz “MaNa” Komincz managed to salvage some pride for humanity by winning the final game. Experts commenting on AlphaStar’s performance used words like “phenomenal” and “superhuman”—which was, to a degree, where things got a bit problematic.

AlphaStar proved particularly skilled at controlling and directing units in battle, known as micromanagement. One reason was that it viewed the whole game map at once—something a human player is not able to do—which made it seemingly able to control units in different areas at the same time. DeepMind researchers said the AIs only focused on a single part of the map at any given time, but interestingly, AlphaStar’s AI agent was limited to a more restricted camera view during the match “MaNA” won.

Potentially offsetting some of this advantage was the fact that AlphaStar was also restricted in certain ways. For example, it was prevented from performing more clicks per minute than a human player would be able to.

Where AIs Struggle
Games like StarCraft II and Dota 2 throw a lot of challenges at AIs. Complex game theory/ strategies, operating with imperfect/incomplete information, undertaking multi-variable and long-term planning, real-time decision-making, navigating a large action space, and making a multitude of possible decisions at every point in time are just the tip of the iceberg. The AIs’ performance in both games was impressive, but also highlighted some of the areas where they could be said to struggle.

In Dota 2 and StarCraft II, AI bots have seemed more vulnerable in longer games, or when confronted with surprising, unfamiliar strategies. They seem to struggle with complexity over time and improvisation/adapting to quick changes. This could be tied to how AIs learn. Even within the first few hours of performing a task, humans tend to gain a sense of familiarity and skill that takes an AI much longer. We are also better at transferring skill from one area to another. In other words, experience playing Dota 2 can help us become good at StarCraft II relatively quickly. This is not the case for AI—yet.

Dwindling Superiority
While the battle between AI and humans for absolute superiority is still on in Dota 2 and StarCraft II, it looks likely that AI will soon reign supreme. Similar things are happening to other types of games.

In 2017, a team from Carnegie Mellon University pitted its Libratus AI against four professionals. After 20 days of No Limit Texas Hold’em, Libratus was up by $1.7 million. Another likely candidate is the destroyer of family harmony at Christmas: Monopoly.

Poker involves bluffing, while Monopoly involves negotiation—skills you might not think AI would be particularly suited to handle. However, an AI experiment at Facebook showed that AI bots are more than capable of undertaking such tasks. The bots proved skilled negotiators, and developed negotiating strategies like pretending interest in one object while they were interested in another altogether—bluffing.

So, what games are we still better at than AI? There is no precise answer, but the list is getting shorter at a rapid pace.

The Aim Of the Game
While AI’s mastery of games might at first glance seem an odd area to focus research on, the belief is that the way AI learn to master a game is transferrable to other areas.

For example, the Libratus poker-playing AI employed strategies that could work in financial trading or political negotiations. The same applies to AlphaStar. As Oriol Vinyals, co-leader of the AlphaStar project, told The Verge:

“First and foremost, the mission at DeepMind is to build an artificial general intelligence. […] To do so, it’s important to benchmark how our agents perform on a wide variety of tasks.”

A 2017 survey of more than 350 AI researchers predicts AI could be a better driver than humans within ten years. By the middle of the century, AI will be able to write a best-selling novel, and a few years later, it will be better than humans at surgery. By the year 2060, AI may do everything better than us.

Whether you think this is a good or a bad thing, it’s worth noting that AI has an often overlooked ability to help us see things differently. When DeepMind’s AlphaGo beat human Go champion Lee Sedol, the Go community learned from it, too. Lee himself went on a win streak after the match with AlphaGo. The same is now happening within the Dota 2 and StarCraft II communities that are studying the human vs. AI games intensely.

More than anything, AI’s recent gaming triumphs illustrate how quickly artificial intelligence is developing. In 1997, Dr. Piet Hut, an astrophysicist at the Institute for Advanced Study at Princeton and a GO enthusiast, told the New York Times that:

”It may be a hundred years before a computer beats humans at Go—maybe even longer.”

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Posted in Human Robots

#434544 This Week’s Awesome Stories From ...

Posted on January 26, 2019 by Android

ARTIFICIAL INTELLIGENCE
DeepMind Beats Pros at Starcraft in Another Triumph for Bots
Tom Simonite | Wired
“DeepMind’s feat is the most complex yet in a long train of contests in which computers have beaten top humans at games. Checkers fell in 1994, chess in 1997, and DeepMind’s earlier bot AlphaGo became the first to beat a champion at the board game Go in 2016. The StarCraft bot is the most powerful AI game player yet; it may also be the least unexpected.”

GENETICS
Complete Axolotl Genome Could Pave the Way Toward Human Tissue Regeneration
George Dvorsky | Gizmodo
“Now that researchers have a near-complete axolotl genome—the new assembly still requires a bit of fine-tuning (more on that in a bit)—they, along with others, can now go about the work of identifying the genes responsible for axolotl tissue regeneration.”

FUTURE
We Analyzed 16,625 Papers to Figure Out Where AI Is Headed Next
Karen Hao | MIT Technology Review
“…though deep learning has singlehandedly thrust AI into the public eye, it represents just a small blip in the history of humanity’s quest to replicate our own intelligence. It’s been at the forefront of that effort for less than 10 years. When you zoom out on the whole history of the field, it’s easy to realize that it could soon be on its way out.”

COMPUTING
Apple’s Finger-Controller Patent Is a Glimpse at Mixed Reality’s Future
Mark Sullivan | Fast Company
“[Apple’s] engineers are now looking past the phone touchscreen toward mixed reality, where the company’s next great UX will very likely be built. A recent patent application gives some tantalizing clues as to how Apple’s people are thinking about aspects of that challenge.”

GOVERNANCE
How Do You Govern Machines That Can Learn? Policymakers Are Trying to Figure That Out
Steve Lohr | The New York Times
“Regulation is coming. That’s a good thing. Rules of competition and behavior are the foundation of healthy, growing markets. That was the consensus of the policymakers at MIT. But they also agreed that artificial intelligence raises some fresh policy challenges.”

Image Credit: Victoria Shapiro / Shutterstock.com Continue reading →

Posted in Human Robots

#433950 How the Spatial Web Will Transform Every ...

Posted on December 13, 2018 by Android

What is the future of work? Is our future one of ‘technological socialism’ (where technology is taking care of our needs)? Or is our future workplace completely virtualized, whereby we hang out at home in our PJs while walking about our virtual corporate headquarters?

This blog will look at the future of work during the age of Web 3.0… Examining scenarios in which AI, VR, and the spatial web converge to transform every element of our careers, from training to execution to free time.

Three weeks ago, I explored the vast implications of Web 3.0 on news, media, smart advertising, and personalized retail. And to offer a quick recap on what the Spatial Web is and how it works, let’s cover some brief history.

A Quick Recap on Web 3.0
While Web 1.0 consisted of static documents and read-only data (static web pages), Web 2.0 introduced multimedia content, interactive web applications, and participatory social media, all of these mediated by two-dimensional screens.

But over the next two to five years, the convergence of 5G, artificial intelligence, VR/AR, and a trillion-sensor economy will enable us to both map our physical world into virtual space and superimpose a digital data layer onto our physical environments.

Suddenly, all our information will be manipulated, stored, understood, and experienced in spatial ways.

In this third installment of the Web 3.0 series, I’ll be discussing the Spatial Web’s vast implications for:

Professional Training
Delocalized Business and the Virtual Workplace
Smart Permissions and Data Security

Let’s dive in.

Virtual Training, Real-World Results
Virtual and augmented reality have already begun disrupting the professional training market.

Leading the charge, Walmart has already implemented VR across 200 Academy training centers, running over 45 modules and simulating everything from unusual customer requests to a Black Friday shopping rush.

In September 2018, Walmart committed to a 17,000-headset order of the Oculus Go to equip every US Supercenter, neighborhood market, and discount store with VR-based employee training.

In the engineering world, Bell Helicopter is using VR to massively expedite development and testing of its latest aircraft, FCX-001. Partnering with Sector 5 Digital and HTC VIVE, Bell found it could concentrate a typical six-year aircraft design process into the course of six months, turning physical mock-ups into CAD-designed virtual replicas.

But beyond the design process itself, Bell is now one of a slew of companies pioneering VR pilot tests and simulations with real-world accuracy. Seated in a true-to-life virtual cockpit, pilots have now tested countless iterations of the FCX-001 in virtual flight, drawing directly onto the 3D model and enacting aircraft modifications in real-time.

And in an expansion of our virtual senses, several key players are already working on haptic feedback. In the case of VR flight, French company Go Touch VR is now partnering with software developer FlyInside on fingertip-mounted haptic tech for aviation.

Dramatically reducing time and trouble required for VR-testing pilots, they aim to give touch-based confirmation of every switch and dial activated on virtual flights, just as one would experience in a full-sized cockpit mockup. Replicating texture, stiffness, and even the sensation of holding an object, these piloted devices contain a suite of actuators to simulate everything from a light touch to higher-pressured contact, all controlled by gaze and finger movements.

When it comes to other high-risk simulations, virtual and augmented reality have barely scratched the surface.

Firefighters can now combat virtual wildfires with new platforms like FLAIM Trainer or TargetSolutions. And thanks to the expansion of medical AR/VR services like 3D4Medical or Echopixel, surgeons might soon perform operations on annotated organs and magnified incision sites, speeding up reaction times and vastly improving precision.

But perhaps most urgent, Web 3.0 and its VR interface will offer an immediate solution for today’s constant industry turnover and large-scale re-education demands.

VR educational facilities with exact replicas of anything from large industrial equipment to minute circuitry will soon give anyone a second chance at the 21st-century job market.

Want to be an electric, autonomous vehicle mechanic at age 15? Throw on a demonetized VR module and learn by doing, testing your prototype iterations at almost zero cost and with no risk of harming others.

Want to be a plasma physicist and play around with a virtual nuclear fusion reactor? Now you’ll be able to simulate results and test out different tweaks, logging Smart Educational Record credits in the process.

As tomorrow’s career model shifts from a “one-and-done graduate degree” to lifelong education, professional VR-based re-education will allow for a continuous education loop, reducing the barrier to entry for anyone wanting to enter a new industry.

But beyond professional training and virtually enriched, real-world work scenarios, Web 3.0 promises entirely virtual workplaces and blockchain-secured authorization systems.

Rise of the Virtual Workplace and Digital Data Integrity
In addition to enabling an annual $52 billion virtual goods marketplace, the Spatial Web is also giving way to “virtual company headquarters” and completely virtualized companies, where employees can work from home or any place on the planet.

Too good to be true? Check out an incredible publicly listed company called eXp Realty.

Launched on the heels of the 2008 financial crisis, eXp Realty beat the odds, going public this past May and surpassing a $1B market cap on day one of trading.

But how? Opting for a demonetized virtual model, eXp’s founder Glenn Sanford decided to ditch brick and mortar from the get-go, instead building out an online virtual campus for employees, contractors, and thousands of agents.

And after years of hosting team meetings, training seminars, and even agent discussions with potential buyers through 2D digital interfaces, eXp’s virtual headquarters went spatial.

What is eXp’s primary corporate value? FUN! And Glenn Sanford’s employees love their jobs.

In a bid to transition from 2D interfaces to immersive, 3D work experiences, virtual platform VirBELA built out the company’s office space in VR, unlocking indefinite scaling potential and an extraordinary new precedent.

Foregoing any physical locations for a centralized VR campus, eXp Realty has essentially thrown out all overhead and entered a lucrative market with barely any upfront costs.

Delocalize with VR, and you can now hire anyone with internet access (right next door or on the other side of the planet), redesign your corporate office every month, throw in an ocean-view office or impromptu conference room for client meetings, and forget about guzzled-up hours in traffic.

Throw in the Spatial Web’s fundamental blockchain-based data layer, and now cryptographically secured virtual IDs will let you validate colleagues’ identities or any of the virtual avatars we will soon inhabit.

This becomes critically important for spatial information logs—keeping incorruptible records of who’s present at a meeting, which data each person has access to, and AI-translated reports of everything discussed and contracts agreed to.

But as I discussed in a previous Spatial Web blog, not only will Web 3.0 and VR advancements allow us to build out virtual worlds, but we’ll soon be able to digitally map our real-world physical offices or entire commercial high rises too.

As data gets added and linked to any given employee’s office, conference room, or security system, we might then access online-merge-offline environments and information through augmented reality.

Imaging showing up at your building’s concierge and your AR glasses automatically check you into the building, authenticating your identity and pulling up any reminders you’ve linked to that specific location.

You stop by a friend’s office, and his smart security system lets you know he’ll arrive in an hour. Need to book a public conference room that’s already been scheduled by another firm’s marketing team? Offer to pay them a fee and, once accepted, a smart transaction will automatically deliver a payment to their company account.

With blockchain-verified digital identities, spatially logged data, and virtually manifest information, business logistics take a fraction of the time, operations grow seamless, and corporate data will be safer than ever.

Final Thoughts
While converging technologies slash the lifespan of Fortune 500 companies, bring on the rise of vast new industries, and transform the job market, Web 3.0 is changing the way we work, where we work, and who we work with.

Life-like virtual modules are already unlocking countless professional training camps, modifiable in real-time and easily updated.

Virtual programming and blockchain-based authentication are enabling smart data logging, identity protection, and on-demand smart asset trading.

And VR/AR-accessible worlds (and corporate campuses) not only demonetize, dematerialize, and delocalize our everyday workplaces, but enrich our physical worlds with AI-driven, context-specific data.

Welcome to the Spatial Web workplace.

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Posted in Human Robots

#433620 Instilling the Best of Human Values in ...

Posted on September 24, 2018 by Android

Now that the era of artificial intelligence is unquestionably upon us, it behooves us to think and work harder to ensure that the AIs we create embody positive human values.

Science fiction is full of AIs that manifest the dark side of humanity, or are indifferent to humans altogether. Such possibilities cannot be ruled out, but nor is there any logical or empirical reason to consider them highly likely. I am among a large group of AI experts who see a strong potential for profoundly positive outcomes in the AI revolution currently underway.

We are facing a future with great uncertainty and tremendous promise, and the best we can do is to confront it with a combination of heart and mind, of common sense and rigorous science. In the realm of AI, what this means is, we need to do our best to guide the AI minds we are creating to embody the values we cherish: love, compassion, creativity, and respect.

The quest for beneficial AI has many dimensions, including its potential to reduce material scarcity and to help unlock the human capacity for love and compassion.

Reducing Scarcity
A large percentage of difficult issues in human society, many of which spill over into the AI domain, would be palliated significantly if material scarcity became less of a problem. Fortunately, AI has great potential to help here. AI is already increasing efficiency in nearly every industry.

In the next few decades, as nanotech and 3D printing continue to advance, AI-driven design will become a larger factor in the economy. Radical new tools like artificial enzymes built using Christian Schafmeister’s spiroligomer molecules, and designed using quantum physics-savvy AIs, will enable the creation of new materials and medicines.

For amazing advances like the intersection of AI and nanotech to lead toward broadly positive outcomes, however, the economic and political aspects of the AI industry may have to shift from the current status quo.

Currently, most AI development occurs under the aegis of military organizations or large corporations oriented heavily toward advertising and marketing. Put crudely, an awful lot of AI today is about “spying, brainwashing, or killing.” This is not really the ideal situation if we want our first true artificial general intelligences to be open-minded, warm-hearted, and beneficial.

Also, as the bulk of AI development now occurs in large for-profit organizations bound by law to pursue the maximization of shareholder value, we face a situation where AI tends to exacerbate global wealth inequality and class divisions. This has the potential to lead to various civilization-scale failure modes involving the intersection of geopolitics, AI, cyberterrorism, and so forth. Part of my motivation for founding the decentralized AI project SingularityNET was to create an alternative mode of dissemination and utilization of both narrow AI and AGI—one that operates in a self-organizing way, outside of the direct grip of conventional corporate and governmental structures.

In the end, though, I worry that radical material abundance and novel political and economic structures may fail to create a positive future, unless they are coupled with advances in consciousness and compassion. AGIs have the potential to be massively more ethical and compassionate than humans. But still, the odds of getting deeply beneficial AGIs seem higher if the humans creating them are fuller of compassion and positive consciousness—and can effectively pass these values on.

Transmitting Human Values
Brain-computer interfacing is another critical aspect of the quest for creating more positive AIs and more positive humans. As Elon Musk has put it, “If you can’t beat ’em, join’ em.” Joining is more fun than beating anyway. What better way to infuse AIs with human values than to connect them directly to human brains, and let them learn directly from the source (while providing humans with valuable enhancements)?

Millions of people recently heard Elon Musk discuss AI and BCI on the Joe Rogan podcast. Musk’s embrace of brain-computer interfacing is laudable, but he tends to dodge some of the tough issues—for instance, he does not emphasize the trade-off cyborgs will face between retaining human-ness and maximizing intelligence, joy, and creativity. To make this trade-off effectively, the AI portion of the cyborg will need to have a deep sense of human values.

Musk calls humanity the “biological boot loader” for AGI, but to me this colorful metaphor misses a key point—that we can seed the AGI we create with our values as an initial condition. This is one reason why it’s important that the first really powerful AGIs are created by decentralized networks, and not conventional corporate or military organizations. The decentralized software/hardware ecosystem, for all its quirks and flaws, has more potential to lead to human-computer cybernetic collective minds that are reasonable and benevolent.

Algorithmic Love
BCI is still in its infancy, but a more immediate way of connecting people with AIs to infuse both with greater love and compassion is to leverage humanoid robotics technology. Toward this end, I conceived a project called Loving AI, focused on using highly expressive humanoid robots like the Hanson robot Sophia to lead people through meditations and other exercises oriented toward unlocking the human potential for love and compassion. My goals here were to explore the potential of AI and robots to have a positive impact on human consciousness, and to use this application to study and improve the OpenCog and SingularityNET tools used to control Sophia in these interactions.

The Loving AI project has now run two small sets of human trials, both with exciting and positive results. These have been small—dozens rather than hundreds of people—but have definitively proven the point. Put a person in a quiet room with a humanoid robot that can look them in the eye, mirror their facial expressions, recognize some of their emotions, and lead them through simple meditation, listening, and consciousness-oriented exercises…and quite a lot of the time, the result is a more relaxed person who has entered into a shifted state of consciousness, at least for a period of time.

In a certain percentage of cases, the interaction with the robot consciousness guide triggered a dramatic change of consciousness in the human subject—a deep meditative trance state, for instance. In most cases, the result was not so extreme, but statistically the positive effect was quite significant across all cases. Furthermore, a similar effect was found using an avatar simulation of the robot’s face on a tablet screen (together with a webcam for facial expression mirroring and recognition), but not with a purely auditory interaction.

The Loving AI experiments are not only about AI; they are about human-robot and human-avatar interaction, with AI as one significant aspect. The facial interaction with the robot or avatar is pushing “biological buttons” that trigger emotional reactions and prime the mind for changes of consciousness. However, this sort of body-mind interaction is arguably critical to human values and what it means to be human; it’s an important thing for robots and AIs to “get.”

Halting or pausing the advance of AI is not a viable possibility at this stage. Despite the risks, the potential economic and political benefits involved are clear and massive. The convergence of narrow AI toward AGI is also a near inevitability, because there are so many important applications where greater generality of intelligence will lead to greater practical functionality. The challenge is to make the outcome of this great civilization-level adventure as positive as possible.

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Posted in Human Robots