Tag Archives: artificial-intelligence

Wintermute vs. Rachel Rosen

aiHere is a fine exploration of the differences and similarities in the use of artificial intelligences in Philip K. Dick and William Gibson’s writing:

Turing, whose purpose is to prevent AIs from developing too far, mirror the bounty hunters in Androids — the sole purpose of each is to control and destroy rogue intelligences, although in both novels their roles are shown from very different perspectives. In Neuromancer Turing are genuinely afraid of AIs: “You have no care for your species,” one Turing agent says to Case, “for thousands of years men dreamed of pacts with demons”.

Both Do Androids Dream of Electric Sheep? and Neuromancer portray artificial intelligences as lacking in empathy, but in different ways and for different reasons.

But would a human equivalent AI necessarily be lacking in empathy? Are humans as empathetic as we’d like to believe?

[via this tweet from SciFi Rules][image from agroni on flickr]

Bacterial computers to solve complex mathematics problems

bacteriaWe’ve seen viruses used to help treat cancer, and help building electrical components, now bacteria are being used to solve hitherto intractable mathematics problems:

Imagine you want to tour the 10 biggest cities in the UK, starting in London (number 1) and finishing in Bristol (number 10). The solution to the Hamiltonian Path Problem is the the shortest possible route you can take.

This simple problem is surprisingly difficult to solve. There are over 3.5 million possible routes to choose from, and a regular computer must try them out one at a time to find the shortest. Alternatively, a computer made from millions of bacteria can look at every route simultaneously. The biological world also has other advantages. As time goes by, a bacterial computer will actually increase in power as the bacteria reproduce.

These developments in synthetic biology are really amazing: it is just another example of how researchers are looking at pre-existing biological structures to solve problems (albeit somewhat abstract problems in this case) instead of building technologies from scratch.

[from the Guardian][image from kaibara87 on flickr]

Silicon mindslice: artificial brains (still) “ten years away”

There’s been a rash of coverage on Dr Markram and the IBM-supported Blue Brain project, one of the experiments designed to move us closer to creating a silicon simulation of the animal brain. Blue Brain is currently based on a silicon recreation of a slice of rat cortex, and Markram’s team have observed spontaneous emergent interaction between their artificial neurons which suggest to them that they’re on the right track… though not everyone is quite so sure.

“We’re building the brain from the bottom up, but in silicon,” says Dr. Markram, the leader of Blue Brain, which is powered by a supercomputer provided by International Business Machines Corp. “We want to understand how the brain learns, how it perceives things, how intelligence emerges.”

Blue Brain is controversial, and its success is far from assured. Christof Koch of the California Institute of Technology, a scientist who studies consciousness, says the Swiss project provides vital data about how part of the brain works. But he says that Dr. Markram’s approach is still missing algorithms, the biological programming that yields higher-level functions.

“You need to have a theory about how a particular circuit in the brain” can trigger complex, higher-order properties, Dr. Koch argues. “You can’t assemble ever larger data fields and shake it and say, ‘Ah, that’s how consciousness emerges.'”

The possibility of simulating consciousness by building a model of the brain is one of those frustrating quandaries that will seemingly only ever be answered by someone succeeding at doing it; the proof is quite literally in the pudding. Still, Markram is pretty convinced he’s on the right track, going so far as to announce in his TED talk that he’ll have built a model human brain within the next decade… which is something that AI researchers have been saying since the sixties, I believe. I’d love to see it happen, but you’ll forgive me if I don’t hold my breath or place any bets just yet.

Memristors – is the “missing” fourth electronic component the key to AI?

I guess I never got far enough with my failed degree in electronics to discover that there’s a fundamental component missing from the metaphorical toolbox.

But apparently there is… or there was. Now, though, the memristor is more than just a concept, and realising it may provide a key to building artificial intelligences… with a little help from slime molds:

Four interconnected things, mathematics says, can be related in six ways. Charge and current, and magnetic flux and voltage, are connected through their definitions. That’s two. Three more associations correspond to the three traditional circuit elements. A resistor is any device that, when you pass current through it, creates a voltage. For a given voltage a capacitor will store a certain amount of charge. Pass a current through an inductor, and you create a magnetic flux. That makes five. Something missing?

Indeed. Where was the device that connected charge and magnetic flux? The short answer was there wasn’t one. But there should have been.

It’s a fairly lengthy article that covers a lot of ground, so it’s hard to summarize with a quote or two. Go read the whole thing; not only is the science itself quite intriguing, it’s also an example of the better sort of journalism that New Scientist puts out.