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Hold ’Em or Fold ’Em? This A.I. Bluffs With the Best

“One player will ask another, What would you have done if I had raised here instead of called?” Unlike systems that can master three-dimensional video games like Dota and StarCraft — systems that need weeks or even months to train to play against humans — Pluribus trained for only about eight days on a fairly ordinary computer at a cost of about $150.

“We can cope with hidden information in a very particular way.” In the end, Pluribus learned to apply complex strategies, including bluffing and random behavior, in real time.

This spring, the researchers tested the system in games in which a single human professional played against five separate instances of Pluribus.

The future of artificial intelligence

Sitting at his cluttered desk, located near an oft-used ping-pong table and prototypes of drones from his college days suspended overhead, Gyongyosi punches some keys on a laptop to pull up grainy video footage of a forklift driver operating his vehicle in a warehouse.

It was captured from overhead courtesy of a Onetrack.AI “forklift vision system.” Employing machine learning and computer vision for detection and classification of various “safety events,” the shoebox-sized device doesn’t see all, but it sees plenty.

The mere knowledge that one of IFM’s devices is watching, Gyongyosi claims, has had “a huge effect.” “If you think about a camera, it really is the richest sensor available to us today at a very interesting price point,” he says.

Here’s another: Tesla founder and tech titan Elon Musk recently donated $10 million to fund ongoing research at the non-profit research company OpenAI — a mere drop in the proverbial bucket if his $1 billion co-pledge in 2015 is any indication.

This, however, is not: After more than seven decades marked by hoopla and sporadic dormancy during a multi-wave evolutionary period that began with so-called “knowledge engineering,” progressed to model- and algorithm-based machine learning and is increasingly focused on perception, reasoning and generalization, AI has re-taken center stage as never before.

There’s virtually no major industry modern AI — more specifically, “narrow AI,” which performs objective functions using data-trained models and often falls into the categories of deep learning or machine learning — hasn’t already affected.

That’s especially true in the past few years, as data collection and analysis has ramped up considerably thanks to robust IoT connectivity, the proliferation of connected devices and ever-speedier computer processing.

With companies spending nearly $20 billion collective dollars on AI products and services annually, tech giants like Google, Apple, Microsoft and Amazon spending billions to create those products and services, universities making AI a more prominent part of their respective curricula (MIT alone is dropping $1 billion on a new college devoted solely to computing, with an AI focus), and the U.S. Department of Defense upping its AI game, big things are bound to happen.

Of the former, he warned: “The bottom 90 percent, especially the bottom 50 percent of the world in terms of income or education, will be badly hurt with job displacement…The simple question to ask is, ‘How routine is a job?’ And that is how likely [it is] a job will be replaced by AI, because AI can, within the routine task, learn to optimize itself.

And the more quantitative, the more objective the job is—separating things into bins, washing dishes, picking fruits and answering customer service calls—those are very much scripted tasks that are repetitive and routine in nature.

In the matter of five, 10 or 15 years, they will be displaced by AI.” In the warehouses of online giant and AI powerhouse Amazon, which buzz with more than 100,000 robots, picking and packing functions are still performed by humans — but that will change.

“One of the absolute prerequisites for AI to be successful in many [areas] is that we invest tremendously in education to retrain people for new jobs,” says Klara Nahrstedt, a computer science professor at the University of Illinois at Urbana–Champaign and director of the school’s Coordinated Science Laboratory.

In the future, if you don’t know coding, you don’t know programming, it’s only going to get more difficult.” And while many of those who are forced out of jobs by technology will find new ones, Vandegrift says, that won’t happen overnight.

“The transition between jobs going away and new ones [emerging],” Vandegrift says, “is not necessarily as painless as people like to think.”   'In the future, if you don’t know coding, you don’t know programming, it’s only going to get more difficult.” Mike Mendelson, a “learner experience designer” for NVIDIA, is a different kind of educator than Nahrstedt.

While some of these uses, like spam filters or suggested items for online shopping, may seem benign, others can have more serious repercussions and may even pose unprecedented threats to the right to privacy and the right to freedom of expression and information (‘freedom of expression’).

Speaking at London’s Westminster Abbey in late November of 2018, internationally renowned AI expert Stuart Russell joked (or not) about his “formal agreement with journalists that I won’t talk to them unless they agree not to put a Terminator robot in the article.” His quip revealed an obvious contempt for Hollywood representations of far-future AI, which tend toward the overwrought and apocalyptic.

Once we have that capability, you could then query all of human knowledge and it would be able to synthesize and integrate and answer questions that no human being has ever been able to answer because they haven't read and been able to put together and join the dots between things that have remained separate throughout history.” That’s a mouthful.

More than a few leading AI figures subscribe (some more hyperbolically than others) to a nightmare scenario that involves what’s known as “singularity,” whereby superintelligent machines take over and permanently alter human existence through enslavement or eradication.

The late theoretical physicist Stephen Hawking famously postulated that if AI itself begins designing better AI than human programmers, the result could be “machines whose intelligence exceeds ours by more than ours exceeds that of snails.” Elon Musk believes and has for years warned that AGI is humanity’s biggest existential threat.

“I think that maybe five or ten years from now, I’ll have to reevaluate that statement because we’ll have different methods available and different ways to go about these things.” While murderous machines may well remain fodder for fiction, many believe they’ll supplant humans in various ways.

As MIT physics professors and leading AI researcher Max Tegmark put it in a 2018 TED Talk, “The real threat from AI isn’t malice, like in silly Hollywood movies, but competence — AI accomplishing goals that just aren’t aligned with ours.” That’s Laird’s take, too.

“I think that’s science fiction and not the way it’s going to play out.” What Laird worries most about isn’t evil AI, per se, but “evil humans using AI as a sort of false force multiplier” for things like bank robbery and credit card fraud, among many other crimes.

Referencing the rapid transformational effect of nuclear fission (atom splitting) by British physicist Ernest Rutherford in 1917, he added, “It’s very, very hard to predict when these conceptual breakthroughs are going to happen.” But whenever they do, if they do, he emphasized the importance of preparation.

I welcomed our new robot overlords at Amazon’s first AI conference

There’s a certain oversized quality to a Las Vegas conference center that makes you feel like a child monarch: simultaneously powerful and helpless.

As Amazon exec Dave Limp explains during the opening keynote, we’re all builders and dreamers, and we’ve been summoned to this hideously carpeted conference center to “envision the future.” It’s actually a fine speech by the standard of tech keynotes: lighthearted, inspirational, unfocused.

But it’s only when I’m slumped on a “party bus” three days later, driving back from the event’s final night festivities at the Las Vegas Motor Speedway, when I begin to understand what Limp was talking about — what re:MARS is really about — and it’s not, strictly speaking, the future of the world.

Amazon chose to sell books because they’re “pure commodities,” according to Brad Stone’s 2013 history, The Everything Store, so the customer always knows what they’re getting.

It launched in 2006 as a “data storage service,” but it has since become indispensable to modern tech companies — as necessary as paper clips once were but a damn sight more profitable.

It’s a way to encourage engineers to scale up their ambitions, says the company, with anyone able to enter an AI driver on a USB flash drive.

“These things are usually one big advertisement,” one attendee told me as we watched the self-driving model cars veer out of reach of their handlers like rabbits at a petting zoo.

“It seems like they’re trying to get the smartest people in the same building and get them to talk to one another,” said Michael Bell, a PhD candidate and research fellow at Harvard’s School of Engineering who was demoing the university’s latest work with soft robotic grippers.

Last month, Bezos unveiled plans for a Moon lander built by his company Blue Origin before outlining a Panglossian vision of space colonization, with a trillion souls living in space in huge, forest-filled rotating colonies.

There was the new Prime Air delivery drone, which is due to start dropping packages in “the coming months.” There was the six-wheeled Scout robot, which is currently being put through its paces in a digital simulacrum of suburbia.

Most of the robots that companies use now are big, dumb, and strong — the type you see lifting car doors and making spot welds in factories.

They use AI and sensors to see us coming and adapt to unplanned challenges, and the thought of giving machines even basic brains is what justifies every headline you see about automation threatening jobs.

At re:MARS, it also showed off how its infrastructure will make it easier to have robots in the home, with Alexa acting as a hub to control iRobot’s new mopping, vacuuming, and lawn-mowing machines.

Executives say the robots are taking over boring tasks and freeing up employees to do “more satisfying jobs.” But employees say that looking after the robots — which frequently break down or malfunction — is becoming a full job, reported The Washington Post this month.

At the same time, employees say their work has become more mechanical, like the humans Amazon employs as “pickers” in its warehouses who stay in one place putting items in boxes while machines dance around them with shelves of products.

Midway through Bezos’ Q&A during the final keynote speeches, a protestor from animal welfare group Direct Action Everywhere burst onto the stage, demanding that the CEO do something about the treatment of chickens in farms that sell to his companies.

It’s simply a matter of focusing on the right qualities — faster shipping, cheaper prices — and grinding away until you achieve your goal.

This might explain why so many tech luminaries are scared of a runaway AI scenario, in which a super intelligent machine fixates on a single task (like building paper clips) and accidentally destroys humanity in the process.

One told me that space colonization was the 21st century’s new religion, a higher purpose that would only become more important after robots robbed us of the meaning provided by work.

thought that sounded about right as I stood in a crowd watching a huge exoskeleton robot tow a vintage 13,000-pound fire truck.


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