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We first need to understand how the brain works if we want true AI

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We first need to understand how the brain works if we want true AI


Next, this sensory input gets taken up by tens of thousands of cortical columns, each with a partial picture of the world. They compete and combine via a sort of voting system to build up an overall viewpoint. That’s the thousand brains idea. In an AI system, this could involve a machine controlling different sensors—vision, touch, radar and so on—to get a more complete model of the world. Although, there will typically be many cortical columns for each sense, such as vision. 

Then there’s continuous learning, where you learn new things without forgetting previous stuff. Today’s AI systems can’t do this. And finally, we structure knowledge using reference frames, which means that our knowledge of the world is relative to our point of view. If I slide my finger up the edge of my coffee cup, I can predict that I’ll feel its rim, because I know where my hand is in relation to the cup.

Your lab has recently shifted from neuroscience to AI. Does that correspond to your thousand brains theory coming together?

Pretty much. Up until two years ago, if you walked into our office, it was all neuroscience. Then we made the transition. We felt we’d learned enough about the brain to start applying it to AI.

What kinds of AI work are you doing?

One of the first things we looked at was sparsity. At any one time, only 2% of our neurons are firing; the activity is sparse. We’ve been applying this idea to deep-learning networks and we’re getting dramatic results, like 50 times speed-ups on existing networks. Sparsity also gives you more robust networks, lower power consumption. Now we’re working on continuous learning.

It’s interesting that you include movement as a baseline for intelligence. Does that mean an AI needs a body? Does it need to be a robot?

In the future I think the distinction between AI and robotics will disappear. But right now I prefer the word “embodiment,” because when you talk about robots it conjures up images of humanlike robots, which isn’t what I’m talking about. The key thing is that the AI will have to have sensors and be able to move them relative to itself and the things it’s modeling. But you could also have a virtual AI that moves in the internet.

This idea is quite different from a lot of popular ideas about intelligence, of a disembodied brain.

Movement is really interesting. The brain uses the same mechanisms to move my finger over a coffee cup, or move my eyes, or even when you’re thinking about a conceptual problem. Your brain moves through reference frames to recall facts that it has stored in different locations.

The key thing is that any intelligent system, no matter what its physical form, learns a model of the world by sensing different parts of it, by moving in it. That’s bedrock; you can’t get away from that. Whether it looks like a humanoid robot, a snake robot, a car, an airplane, or, you know, just a computer sitting on your desk scooting around the internet—they’re all the same.

How do most AI researchers feel about these ideas?

The vast majority of AI researchers don’t really embrace the idea that the brain is important. I mean, yes, people figured out neural networks a while ago, and they’re kind of inspired by the brain. But most people aren’t trying to replicate the brain. It’s just whatever works, works. And today’s neural networks are working well enough.

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The Download: sleeping in VR, and promising clean energy projects

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The Download: sleeping in VR, and promising clean energy projects


People are gathering in virtual spaces to relax, and even sleep, with their headsets on. VR sleep rooms are becoming popular among people who suffer from insomnia or loneliness, offering cozy enclaves where strangers can safely find relaxation and company—most of the time.

Each VR sleep room is created to induce calm. Some imitate beaches and campsites with bonfires, while others re-create hotel rooms or cabins. Soundtracks vary from relaxing beats to nature sounds to absolute silence, while lighting can range from neon disco balls to pitch-black darkness. 

The opportunity to sleep in groups can be particularly appealing to isolated or lonely people who want to feel less alone, and safe enough to fall asleep. The trouble is, what if the experience doesn’t make you feel that way? Read the full story.

—Tanya Basu

Inside the conference where researchers are solving the clean-energy puzzle

There are plenty of tried-and-true solutions that can begin to address climate change right now: wind and solar power are being deployed at massive scales, electric vehicles are coming to the mainstream, and new technologies are helping companies make even fossil-fuel production less polluting. 

But as we knock out the easy climate wins, we’ll also need to get creative to tackle harder-to-solve sectors and reach net-zero emissions. 

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Inside the conference where researchers are solving the clean-energy puzzle

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Inside the conference where researchers are solving the clean-energy puzzle


The Advanced Research Projects Agency for Energy (ARPA-E) funds high-risk, high-reward energy research projects, and each year the agency hosts a summit where funding recipients and other researchers and companies in energy can gather to talk about what’s new in the field.

As I listened to presentations, met with researchers, and—especially—wandered around the showcase, I often had a vague feeling of whiplash. Standing at one booth trying to wrap my head around how we might measure carbon stored by plants, I would look over and see another group focused on making nuclear fusion a more practical way to power the world. 

There are plenty of tried-and-true solutions that can begin to address climate change right now: wind and solar power are being deployed at massive scales, electric vehicles are coming to the mainstream, and new technologies are helping companies make even fossil-fuel production less polluting. But as we knock out the easy wins, we’ll also need to get creative to tackle harder-to-solve sectors and reach net-zero emissions. Here are a few intriguing projects from the ARPA-E showcase that caught my eye.

Vaporized rocks

“I heard you have rocks here!” I exclaimed as I approached the Quaise Energy station. 

Quaise’s booth featured a screen flashing through some fast facts and demonstration videos. And sure enough, laid out on the table were two slabs of rock. They looked a bit worse for wear, each sporting a hole about the size of a quarter in the middle, singed around the edges. 

These rocks earned their scorch marks in service of a big goal: making geothermal power possible anywhere. Today, the high temperatures needed to generate electricity using heat from the Earth are only accessible close to the surface in certain places on the planet, like Iceland or the western US. 

Geothermal power could in theory be deployed anywhere, if we could drill deep enough. Getting there won’t be easy, though, and could require drilling 20 kilometers (12 miles) beneath the surface. That’s deeper than any oil and gas drilling done today. 

Rather than grinding through layers of granite with conventional drilling technology, Quaise plans to get through the more obstinate parts of the Earth’s crust by using high-powered millimeter waves to vaporize rock. (It’s sort of like lasers, but not quite.)

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The emergent industrial metaverse

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The emergent industrial metaverse


Annika Hauptvogel, head of technology and innovation management at Siemens, describes the industrial metaverse as “immersive, making users feel as if they’re in a real environment; collaborative in real time; open enough for different applications to seamlessly interact; and trusted by the individuals and businesses that participate”—far more than simply a digital world. 

The industrial metaverse will revolutionize the way work is done, but it will also unlock significant new value for business and societies. By allowing businesses to model, prototype, and test dozens, hundreds, or millions of design iterations in real time and in an immersive, physics-based environment before committing physical and human resources to a project, industrial metaverse tools will usher in a new era of solving real-world problems digitally. 

“The real world is very messy, noisy, and sometimes hard to really understand,” says Danny Lange, senior vice president of artificial intelligence at Unity Technologies, a leading platform for creating and growing real-time 3-D content. “The idea of the industrial metaverse is to create a cleaner connection between the real world and the virtual world, because the virtual world is so much easier and cheaper to work with.” 

While real-life applications of the consumer metaverse are still developing, industrial metaverse use cases are purpose-driven, well aligned with real-world problems and business imperatives. The resource efficiencies enabled by industrial metaverse solutions may increase business competitiveness while also continually driving progress toward the sustainability, resilience, decarbonization, and dematerialization goals that are essential to human flourishing. 

This report explores what it will take to create the industrial metaverse, its potential impacts on business and society, the challenges ahead, and innovative use cases that will shape the future. Its key findings are as follows: 

• The industrial metaverse will bring together the digital and real worlds. It will enable a constant exchange of information, data, and decisions and empower industries to solve extraordinarily complex real-world problems digitally, changing how organizations operate and unlocking significant societal benefits. 

• The digital twin is a core metaverse building block. These virtual models simulate real-world objects in detail. The next generation of digital twins will be photorealistic, physics-based, AI-enabled, and linked in metaverse ecosystems. 

• The industrial metaverse will transform every industry. Currently existing digital twins illustrate the power and potential of the industrial metaverse to revolutionize design and engineering, testing, operations, and training. 

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