Robot Makes Scientific Discovery (Mostly) On Its Own
Hugh Pickens writes "A science-savvy robot called Adam has successfully developed and tested its first scientific hypothesis, discovering that certain genes in baker's yeast code for specific enzymes which encourage biochemical reactions in yeast, then ran an experiment with its lab hardware to test its predictions, and analyzed the results, all without human intervention. Adam was equipped with a database on genes that are known to be present in bacteria, mice and people, so it knew roughly where it should search in the genetic material for the lysine gene in baker's yeast, Saccharomyces cerevisiae. Ross King, a computer scientist and biologist at Aberystwyth University, first created a computer that could generate hypotheses and perform experiments five years ago. 'This is one of the first systems to get [artificial intelligence] to try and control laboratory automation,' King says. '[Current robots] tend to do one thing or a sequence of things. The complexity of Adam is that it has cycles.' Adam has cost roughly $1 million to develop and the software that drives Adam's thought process sits on three computers, allowing Adam to investigate a thousand experiments a day and still keep track of all the results better than humans can. King's group has also created another robot scientist called Eve dedicated to screening chemical compounds for new pharmaceutical drugs that could combat diseases such as malaria.
If I ever do cutting edge research on robot AI, please punch me if I try to name my new robots "Adam" or "Eve".
... it starts experimenting with inter-dimensional portal guns.
Oh, sure, it's neat-o. But you could probably afford hundreds of grad students to do the work for the same price.
No kidding. Let's get Ron Moore to pilot it and himself into the sun.
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'[Current robots] tend to do one thing or a sequence of things. The complexity of Adam is that it has cycles.'
I think this is called "flow control". This was invented before electricity. It was around before the term "science" existed.
So this is the first time it's applied to *this specific* operation. It's been around in robotics ever since there were "robots".
Here's a good example.
Entomologically speaking, the spider is not a bug, it's a feature.
"...the software that drives Adam's thought process sits on three computers, allowing Adam to investigate a thousand experiments a day and still keep track of all the results better than humans can."
There is no 'thought process'. 1's & 0's...that's it. Anthropomorphising the over priced little key-puncher isn't fooling anyone.
Give me $1 mil and I'll put a scare into Adam that he won't soon forget. I can read 3k WPM as well as raw postscript, palms, tarot cards and bar codes with the naked eye. I can intuit nearly 30 spoken languages on body english alone and smell phony money at the bottom of a sweaty pocket. I don't need no stink'n badges and I know when to cross to the other side of the street. Adam might get better press, but until it can order at a drive thru and sort used car parts based on cross-over and eBay thru-put, I'm comfortable sleeping in.
I knew that Ross was up to something bigger than protein secondary structure prediction when I met him 15 years ago at ICRF. He was a great Prolog fan then. Now he has probably bunch of graduate students coding for him.
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The complexity of Adam is that it has cycles.
No, no, no -- the complexity of *Eve* is that it has cycles.
If you open yourself to the foo, You and foo become one.
See, what people fail to see is this requires not only Strong AI but also a programmed Malicious intent.
People keep assuming that if we build a robot that can emulate some of our thought, it will emulate our motives also
Since we program it, it will only emulate the motives we give it. Emulating motives that are abstract enough to eventually lead back to our demise are quite complex
Isn't the first requirement for a singularity be that it's able to improve itself, thus leading to an accelerating growth that ends in the subjugation of humanity? If so, wouldn't it be prudent to withhold knowledge of the scientific method as long as possible?
This probably isn't the most helpful commentary, but it's a slight rant on semantics.
I used to work with Motoman K6's a few years back. Using these robots, we performed plasma cutting, arc welding, material handling, etc... Just looking at the K6, you knew it was a robot. Watching a robot work in a cell after you've trained it to do it's job is a very rewarding experience. Of course we also had other machines that were also very complex in their tasks, but we didn't consider them robots. CNC mills and lathes, pipe benders, other machines that ran autonomously that also had to be programmed and synchronized with the flow of production. Sometimes the line resembled a kind of demented Rube Goldberg contraption, but we were somewhat strict to define only the articulated manipulators themselves as robots.
So when I saw this pile of servos in a glass cleanroom set to the over-dramatic theme of "Bonanza Reloaded", I thought, "Yeah, that's nice, but... It just doesn't strike me as a 'robot' so much as it does an automated bio lab."
And yes, I realize there were clearly robots within the cell, but calling the unit as a whole a "robot" just irks me a little.
Of course in the spirit of all the other bad jokes I've seen posted, do you think this "robot" will use it's genetic findings with the yeast cells to perfect the most delicious and moist cake recipe ever?
Blessed with all the brains that God gave a duck's ass, and twice the charisma.
We could always build them with OFF switches as well.
God: An invisible friend for grown-ups.
This reminds me of the Automated Mathematician (AM) program I read about in an AI course (or was it an old Byte magazine?). This program was programmed with a bunch of axioms, and basic strategies. It looked for "interesting things", like what happens when you apply identical arguments to a two argument function. As I recall, it discovered for itself the concept of prime numbers. It applied what it learned and came up with the theorem that all angles can be expressed as the sum of two prime angles (or something like that).
This seems to be doing the same thing: mixing and matching patterns, looking for interesting coincidences, and then testing for them. The only difference is that this is doing it with real world biological samples, and not abstract mathematical constructs.
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Not necessarily. The least elegant way to create strong AI is probably to brute force simulate a whole brain down to nearly every neurotransmitter molecule, something which futurists argue will be doable by supercomputers around 2020.
This is a worst case solution since it would imply that the brain is not understood yet and instead of having a simpler model that can provide the same level of strong AI we just throw raw power at it.
In this case, the AI would theoritically emerge out of the complexity of the system and although malicious intent wouldn't be programmed in (neither would anything else) the system might learn it by himself.
This is terrible.
No experimenter bias to worry about.
Programmable for effective randomization.
Truly double blind capable.
Can counteract the Placebo effect.
No ego to bruise.
It's the end of science as we know it.
I didn't desert Windows; Windows deserted me: BSOD
So, our future AI overlords begin their research with the Lysine Contingency? Should we be worried?
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What's far more fascinating and promising is the development of hardware neural nets. To put it into perspective:
Since the neurons are so small, the system runs 100,000 times faster than the biological equivalent and 10 million times faster than a software simulation. "We can simulate a day in one second," Meier notes.
10 million times faster than software? That's like jumping from an abacus to a Pentium.
I just hope these folks continue to receive the funding they need.