--- Steve Richfield <[EMAIL PROTECTED]> wrote: > On 4/17/08, Mark Waser <[EMAIL PROTECTED]> wrote: > > > > That's true as of now, but let's think one or two steps further: Do > > > you really think a mature AGI's (say with 3-6 year-old human > > > intelligence) KB can reside in RAM, entirely? > > > > > > > Yes. RAM is *HUGE*. Intelligence is *NOT*. > > > Hmm, thinking on the keyboard... > ~100E9 computing cells with ~50K inputs each, of which ~200 are active. > One theory is that you would only have to carry the active inputs, plus some > fraction of the inactive inputs while you watched for things to happen to > make them active. Let's say that we must track ~1E3 inputs, for a total > of 100E12 or one hundred trillion inputs. We could use fractal means to > generate the original configuration (as biological brains probably do), very > low precision arithmetic with statistical rounding, etc., which would reduce > each input to just a few bytes to maintain, say ~10. This makes a total of > 1E15 or one quadrillion bytes to represent a simulated human's instantaneous > state of construction. An entire checkpoint would take little more, because > it would only include in addition the electrical state of each of the 100E9 > cells. > > Note however, that the *FUNCTIONAL* state would only be 1/5 of this estimate > because 4/5 of the represented inputs are presently inactive, for a total of > "only" 100 terabytes. > > Note that ~90% of those 100E9 cells are slow-responding glial cells, so > while the state is large, the computational requirements may be well short > of a petaflop. > > Of course, this makes a LOT of assumptions that no one has yet bothered to > confirm in the laboratory, and I do NOT want to ignite an "estimates war", > so I invite constructive comments from anyone with more recent data than I > have.
The Blue Brain project estimates 8000 synapses per neuron in mouse cortex. I haven't seen a more accurate estimate for humans, so your numbers are probably as good as mine. I estimate 10^11 neurons, 10^15 synapses (1 bit each) and a response time of 100 ms, or 10^16 OPS to replicate the processing of a human brain. The memory requirement is considerably higher than the information content of long term memory estimated by Landauer [1], about 10^9 bits. This may be due to the constraints of slow neurons, parallelism, and the pulsed binary nature of nerve transmission. For example, the lower levels of visual processing in the brain involve massive replication of nearly identical spot filters which could be simulated in a machine by scanning a small filter coefficient array across the retina. It also takes large numbers of nerves to represent a continuous signal with any accuracy, e.g. fine motor control or distinguishing nearly identical perceptions. However my work with text compression suggests that the cost of modeling 1 GB of text (about one human lifetime's worth) is considerably more than a few GB of memory. My guess is at least 10^12 bits just for ungrounded language modeling. If the model is represented as a set of (sparse) graphs, matrices, or neural networks, that's about 10^13 OPS. Remember that the goal of AGI is not to duplicate the human brain, but to do the work that humans are now paid to do. It still requires solving hard problems like language, vision, and robotics, which consume a significant fraction of the brain's computing power. But what matters is that the cost of AGI be less than human labor, currently US $10K per year worldwide and growing at 3-4% (5% GDP growth - 1.5% population growth). If my guess is right and Moore's law continues (halving costs every 1.5 to 2 years), then AGI is at least 10-15 years away. If it actually turns out there are no shortcuts to simulating the brain, then it is 30 years away. 1. Landauer, Tom, "How much do people remember? Some estimates of the quantity of learned information in long term memory", Cognitive Science (10) pp. 477-493, 1986. -- Matt Mahoney, [EMAIL PROTECTED] ------------------------------------------- agi Archives: http://www.listbox.com/member/archive/303/=now RSS Feed: http://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: http://www.listbox.com/member/?member_id=8660244&id_secret=101455710-f059c4 Powered by Listbox: http://www.listbox.com
