In this thought experiment, I take a look into how the brain uses input and output from its body.
Let's imagine we have a brain in a body, and is stationed in a large laboratory that enhances its research and exploration. The reason it is not stationed in a normal home is because technological advances come from experiments and data processing, not sleeping eating and sitting on home furniture. The lab and body won't intelligently move on its own, so let's direct focus to the brain now. The brain cannot make any non-random output decisions yet, as it has had no input experiences yet. To do better output it needs input first. So the first thing we can do is either feed it lots of diverse image/text data, or let it try to walk forward and receive data about which motor actions got motion. So far so good, we just made it store its first experiences. Up to now the brain has only received random input data (note the real world data isn't random but the source is) from all sorts of sources. It didn't decide where to collect data from, as it couldn't output any non-random decisions. Now our brain can decide to tweak its walking skills to further improve its speed, or can decide to collect text/image data from certain sources such as particular websites or particular real life experiments. For example it may be trying to invent better storage devices and wants to see if it's predictions are correct or may want to collect data from there simply. Testing it's predictions is also data collection because it boosts it's already existing beliefs's probabilities. The trend here seems to show that as it collects data, it is getting more precise where to collect it from. Without output from the brain, the brain could never collect data from specific areas. The brain is learning where to collect data from. The 2 uses the brain has for output is 1) specific data collection, and 2) implementing solutions ex. a new product to market and seeing their mission completed (this is also data collection). Our brain, if it had a solution to a big problem on Earth will all road-bumps covered, could just tell us it of course. It wouldn't absolutely require a body to implement a "plan". The "coming up with a *new* plan" is done in the brain, it needs a lot of on topic data also. The output of the brain to the body is just to collect more desired data. What is most interesting is when you have a lot of data, you can make a lot of connections in it and generate new data by using a method called Induction. So what do yous think about the idea that we could make a powerful AGI without a body? I mean it still would have output to talk to us and input from various websites and experiments it asks us to do, but it wouldn't need a LOT of real life experiments if it has a lot of data because it can mostly generate its own data at that point and fill in gaps. So most of its output in that case would be either a solution to a problem or a few requests of where to collect new data from if its solution isn't ready yet. Other than than it would be mostly doing induction internally using huge amounts of data. After all, experiments are only to collect data, we can give it lots even if not from precise tests. My point here is AGI creates new data and is an induction engine, and works better with huge amounts of diverse data and on-topic data as well. That's all its input does - is provide data. The output is to collect certain data. But AGI *needs to generate *new data using all this data and/or find part of its solutions in data. For example finding a device in nature or an advanced civilization would be a solution that eliminates many sub goals. It could read about it in data too, if it trusts that data. In that sense, AGI is about re-sorting existing features/data into new data/ devices or skills. To do that it needs a lot of data. AGI generates the future using a Lot of context. What do yous think? Can we sort of get away without a body and just make AGI in the computer and talk to us using its text/vision thoughts? And can we get way with doing lots of specific experiments from the right locations and times and just use the slightly-more random big data? To me it appears to be yes we can. The AGI could still extract/form new answers from the large data. Like you know how Prediction works right? You can answer unseen questions or image hole fill in? So AGI can just 'know' answers to things using related data. And, what if it can just watch microscopic data and do all sorts of random experiments to see what "happens" and build a better model!? It is true though brute force is not computable in our case, but it's an idea. ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tf81a0714b774beb2-M69e9def5bc1db5a088058c2d Delivery options: https://agi.topicbox.com/groups/agi/subscription
