We’re still pretending that we’re inventing a brain when all we’ve come up with is a giant mash-up of real brains. We don’t yet understand how brains work, so we can’t build one.
We bolded that last sentence because it pretty much explains the predicament for AI. Until we more fundamentally understand that which we’re trying to clone, everything else is an impressive attempt up Everest that never totally summits.
This jibes with a sentiment that renowned author and cognitive scientist Douglas Hofstadter posed earlier this year. He calls current prominent pursuits in the artificial intelligence arena “vacuous”
[IBM’s “Jeopardy!”-winning supercomputer] Watson is basically a text search algorithm connected to a database just like Google search. It doesn’t understand what it’s reading. In fact, “read” is the wrong word. It’s not reading anything because it’s not comprehending anything. Watson is finding text without having a clue as to what the text means. In that sense, there’s no intelligence there. It’s clever, it’s impressive, but it’s absolutely vacuous.
We’ve got a ways to go before machines are truly smart.
SOURCE: Why We Can’t Yet Build True Artificial Intelligence, Explained In One Sentence – Yahoo Finance.
I seem to come across a lot of talk lately about how machines will eventually rule the world and the humans will become obsolete. Having lived a big part of my life in the software development area maybe I understand a little more than most how this worry is very much unfounded. We have nothing to worry about for probably centuries. We simply can’t simulate something we really don’t even understand in the first place. Plainly speaking artificial intelligence is not even yet on technology’s radar screen.
When I first become interested in computer things back in the 1970s I purchased a TRS-80 personal computer and spent hours of my free time learning to program it. It costs a whopping $500 (that’s about $3,000 in today’s dollar). It had 16 kbytes of Ram and a 85k floppy disk (today’s computers have about a million times more memory and storage). But even this gargantuan increase is still not even close to what the human mind is capable of doing.
Even when the hardware finally comes in the neighborhood of our minds we still have to write the programs to simulate our mental processes. That is something we still don’t begin to understand. We got a long way to go before we have to be concerned with machines becoming smarter than their inventors if that is even possible….