AI News, AI: More than Human

The billion-dollar bet to reach human-level AI

Late last month, it raised $1bn from Microsoft to speed its pursuit of the Holy Grail of AI: a computer capable of so-called artificial general intelligence, a level of cognition that would match its makers, and which is seen as the final step before the advent of computers with superhuman intelligence.

But, speaking of the vast computing power that OpenAI and Microsoft hope to put at the service of its AI ambitions within five years, he added: “At that point, I think there’s a chance that will be enough.”

Deep learning systems, which use artificial neural networks modelled on one idea of how the human brain works, have provided most of the breakthroughs that have put AI back at the centre of the tech world.

believe that teaching computers new types of reasoning and symbolic logic will be needed to complement the neural networks, rather than just building bigger computers.

Asked whether bigger computers alone will deliver human-level AI, Stuart Russell, a computer science professor at the University of California, Berkeley, points to the verdict in his forthcoming book on the subject: “Focusing on raw computing power misses the point entirely . . . We don’t know how to make a machine really intelligent —

Even the possibility that OpenAI may be on the right track, though, has been enough to attract a huge cash injection from the world’s most valuable company, setting up a race to build far more advanced hardware systems for AI.

OpenAI’s bet is that, as computer hardware gets more powerful, the learning algorithms used in deep learning systems will evolve, developing capabilities that today’s coders could never hope to program into them directly.

far bigger language system released this year, called GPT-2, went a step further, said Mr Brockman, developing a degree of semantic understanding from applying the same kind of huge statistical analysis.

Most of the $1bn investment will return to the software company in the form of payments to use its Azure cloud computing platform, with Microsoft working on developing new supercomputing capabilities to throw at the effort.

If OpenAI’s work ever produces the kind of huge wealth that Mr Brockman predicts, most of it will flow to the group’s non-profit arm, reflecting its promise to use the fruits of advanced computer intelligence for the benefit of all humanity.

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.

Golems, masks, and artificial intelligence: a conversation with Dr. Suzanne Livingston

Justin Manley: When I saw AI: More than Human, I was expecting an art-museum kind of show, with white walls and oceans of space in between the artworks.

Art is part of the exploration of AI — there’s a huge conversation right now about whether AI can be creative, for example — but it really matters to me that people leave the show having a much stronger sense of what AI actually is.

Especially in this part of the world those stories — of a woman and a gay man in computing — need to be pulled up right to the fore.

The design brief was about creating a space which literally had breath, so it was very much our intention to bring this space to life.

We’re working subtly with the lighting throughout, which means it’s not constant — it has a kind of pulse of its own, whether you notice it or not.

And the plinths are actually based on the golem form — they’re coming from an ancient reference.

These forms drawn from ancient mythologies of AI which appear at the beginning of the show become the physical supports for displaying cutting-edge contemporary AI research later in the exhibition.

The Curve sweeps around the performance hall at the Barbican — it’s a long, narrow, curving exhibition space.

A great space to work with, but it does mean we’re not offering the artists beautiful, pristine environments for their work.

Freud was fundamental in developing the idea of the uncanny — a feeling of uncomfortable familiarity we experience when we look at lifelike dolls and wax sculptures.

As I stood in front of the robot, I felt almost…a kind of pity, because I couldn’t make sense of its movements.

The old model of it being a butler, doing the ironing — I’m grateful that as a society, that we’re moving beyond thinking that.

That vision of AI as a butler reflects an old master-slave narrative which is full of problems — because then we start having an antagonistic relationship with AI.

That way, we actually see what it can give us, and it’s much more like a dance between us and it, rather than imposing ourselves upon the technology, putting it to use, getting it to do our basic tasks.

JM: There’s an anthropologist named Sherry Turkle who argues that the ubiquity of the rational machine (in the form of the computer) has forced us to relinquish rationality as a defining quality of what it means to be human.

SL: I don’t know if it’s right for us to term these abilities or qualities within technology using our own language.

I don’t think we can control it — or at least we have to think hard about what we mean by “control.” The question is: how do we lead in relationship to it?

So it’s crucial to maintain an attentive, playful awareness of AI, in addition to participating in the big debates of today.

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