We all have our favorite capacity/organ that we fail modern-day AI for not having, and that we think it needs to have to get truly intelligent machines. For some it’s consciousness, for others it is common sense, emotion, heart, or soul. What if it came down to a gut? That we need to make our AI have the capacity to get hungry, and slake that hunger with food, for the next real breakthrough? There’s some new information on the role of gut microbes in brain development that’s worth some mental mastication in this regard (PNAS via PhysOrg).
At night in the rivers of the Amazon Basin there buzzes an entire electric civilization of fish that “see” and communicate by discharging weak electric fields. These odd characters, swimming batteries which go by the name of “weakly electric fish,” have been the focus of research in my lab and those of many others for quite a while now, because they are a model system for understanding how the brain works. (While their brains are a bit different, we can learn a great deal about ours from them, just as we’ve learned much of what we know about genetics from fruit flies.) There are now well over 3,000 scientific papers on how the brains of these fish work.
Recently, my collaborators and I built a robotic version of these animals, focusing on one in particular: the black ghost knifefish. (The name is apparently derived from a native South American belief that the souls of ancestors inhabit these fish. For the sake of my karmic health, I’m hoping that this is apocryphal.) My university, Northwestern, did a press release with a video about our “GhostBot” last week, and I’ve been astonished at its popularity (nearly 30,000 views as I write this, thanks to coverage by places like io9, Fast Company, PC World, and msnbc). Given this unexpected interest, I thought I’d post a bit of the story behind the ghost.
The Singularity seems to be getting less and less near. One of the big goals of Singularity hopefuls is to be able to put a human mind onto (into? not sure on the proper preposition here) a non-biological substrate. Most of the debates have revolved around computer analogies. The brain is hardware, the mind is software. Therefore, to run the mind on different hardware, it just has to be “ported” or “emulated” the way a computer program might be. Timothy B. Lee (not the internet inventing one) counters Robin Hanson’s claim that we will be able to upload a human mind onto a computer within the next couple decades by dissecting the computer=mind analogy:
You can’t emulate a natural system because natural systems don’t have designers, and therefore weren’t built to conform to any particular mathematical model. Modeling natural systems is much more difficult—indeed, so difficult that we use a different word, “simulation” to describe the process. Creating a simulation of a natural system inherently means means making judgment calls about which aspects of a physical system are the most important. And because there’s no underlying blueprint, these guesses are never perfect: it will always be necessary to leave out some details that affect the behavior of the overall system, which means that simulations are never more than approximately right. Weather simulations, for example, are never going to be able to predict precisely where each raindrop will fall, they only predict general large-scale trends, and only for a limited period of time. This is different than an emulator, which (if implemented well) can be expected to behave exactly like the system it is emulating, for as long as you care to run it.
In short: we know how software is written, we can see the code and rules that govern the system–not true for the mind, so we guess at the unknowns and test the guesses with simulations. Lee’s post is very much worth the full read, so give it a perusal.
Lee got me thinking with his point that “natural systems don’t have designers.” Evolutionary processes have resulted in the brain we have today, but there was no intention or design behind those process. Our minds are undesigned.
I find that fascinating. In the first place, because it means that simulation will be exceedingly difficult. How do you reverse-engineer something with no engineer? Second, even if a simulation is successful, it by no means a guarantees that we can change the substrate of an existing mind. If the mind is an emergent property of the physical brain, then one can no more move a mind than one could move a hurricane from one system to another. The mind, it may turn out, is fundamentally and essentially related to the substrate in which it is embodied. Read More
Independence Day has one of my most favorite hero duos of all time: Will Smith and Jeff Goldblum. Brawn and brains, flyboy and nerd, working together to take out the baddies. It all comes down to one flash of insight on behalf of a drunk Goldblum after being chastised by his father. Cliché eureka! moments like Goldblum’s realization that he can give the mothership a “cold” are great until you realize one thing: if Goldblum hadn’t been as smart as he was, the movie would have ended much differently. No one in the film was even close to figuring out how to defeat the aliens. Will Smith was in a distant second place and he had only discovered that they are vulnerable to face punches. The hillbilly who flew his jet fighter into the alien destruct-o-beam doesn’t count, because he needed a force-field-free spaceship for his trick to work. If Jeff Goldblum hadn’t been a super-genius, humanity would have been annihilated.
Every apocalyptic film seems to trade on the idea that there will be some lone super-genius to figure out the problem. In The Day The Earth Stood Still (both versions) Professor Barnhardt manages to convince Klaatu to give humanity a second look. Cleese’s version of the character had a particularly moving “this is our moment” speech. Though it’s eventually the love between a mother and child that triggers Klaatu’s mercy, Barnhardt is the one who opens Klaatu to the possibility. Over and over we see the lone super-genius helping to save the world.
Shouldn’t we want, oh, I don’t know, at least more than one super-genius per global catastrophe? I’d like to think so. And where might we get some more geniuses? you may ask. We make them.
As part of DISCOVER’s 30th anniversary celebration, the magazine invited 11 eminent scientists to look forward and share their predictions and hopes for the next three decades. But we also want to turn this over to Science Not Fiction’s readers: How do you think science will improve the world by 2040?
Below are short excerpts of the guest scientists’ responses, with links to the full versions:
Engineer, inventor, and Singularity true-believer Ray Kurzweil thinks we can reverse-engineer the brain in a couple decades. After Gizmodo mis-reported Kurzweil’s Singularity Summit prediction that we’d reverse-engineer the brain by 2020 (he predicted 2030), the blogosphere caught fire. PZ Myers’ trademark incendiary arguments kick-started the debate when he described Kurzweil as the “Deepak Chopra for the computer science cognoscenti.” Of course, Kurzweil responded, to which Myers retorted. Hardly a new topic, the Singularity has already taken some healthy blows from Jaron Lanier, John Pavlus and John Horgan. The fundamental failure of Kurzweil’s argument is summarized by Myers:
My complaint isn’t that he has set a date by which we’ll understand the brain, but that he has provided no baseline value for his exponential growth claim, and has no way to measure how much we know now, how much we need to know, and how rapidly we will acquire that knowledge.
Think of the most complicated thing you’ve written. Maybe it was a report for your employer, or an essay while in college. It could even be a computer program. Whatever it was, think of all the stuff you packed into it. Now, pause for a moment to imagine creating all that without using a word processor or a paper and pen, or really anything at all to externalize thought to something outside of your head. It seems impossible. What we get with this technology–ancient as it is–is an amplification of our brain power. Besides their gorgeous techy looks, do interactive holographics like that shown in Iron Man 2, reminiscent of interfaces shown in Minority Report, offer up some of the same brain amping?
The neurons of a patient suffering from Alzheimer’s.
You may not be consciously aware of it, but at any given time your brain is playing host to billions of simultaneous conversations (and no, I’m not talking about those voices). I speak, of course, of the conversations between your neurons—the incessant neural jabbering that makes it possible for you to move your limbs, learn, remember, and feel pain. Every time we experience a new sensation or form a memory, millions of electrical and chemical signals are propagated across dense networks of axons and jump from one synapse to the next, building new neuronal connections or strengthening existing ones. And they are constantly changing—forming and reforming associations with other neurons in response to how the brain perceives and processes new bits of information.
Despite being central to our understanding of how the brain functions, these neural chats remain largely a mystery to scientists. What exactly are the individual neurons “saying” to each other? And how do these electrical and chemical “messages” become translated into actions, memories, or a range of other complex behaviors? To help decipher these discussions, a team of researchers from the University of Calgary led by bioengineer Naweed Syed have built a silicon microchip embedded with large networks of brain cells. The idea is to get the brain cells to “talk” to the millimeter-square chip—and then have the chip talk to the scientists through a computer interface.
Christopher Nolan’s Inception is a film about a time when we have the power to enter into each other’s dreams, and actively steer the dream’s course to implant an idea in the dreamer.
The film raises the issue of how much we understand about the neuroscience of dreams. Due to its need for invasive experiments, neuroscience typically works with non-human animals, which raises a significant difficulty: how do you know that a rat is dreaming? You can’t wake it up from REM sleep and ask. (Well, you can, but don’t expect a cogent response.) There’s no accepted objective indicator that a person or animal is having a dream, as opposed to sleeping. But, we can still learn something useful by looking at the neuroscience of sleep.
You’ve been running for hours, chased by a crazed grizzly bear. Suddenly you lose your footing, and you’re balancing on the edge of a cliff. Your stomach lurches as gravity pulls you down. Instantly you’re jolted awake and find yourself teetering precariously over the edge of your bed in your New York apartment. You’ve been asleep for just 5 minutes.
Like me (or whoever I stole that bizarre-o dream about the crazed grizzly from), everyone has dreams that strangely intertwine with reality. That’s what makes Chris Nolan’s newest thriller, Inception, so fun to watch. It plays with ideas we’ve all experienced—how dreams can reveal our most guarded memories, feel like days when only hours have passed, or affect our emotions when we wake up.