Electric Turnip
  • Blog
  • Stories
    • Story 000
    • Story 001
    • Story 002
    • Story 004
    • Story 007 - Unfinished
    • Story 008
    • Story 010 - BattleWagon
    • Story 012
  • Images
    • Adventure Caddie concept gallery
    • Page Design Gallery
    • Older Work
  • 5FEAT Video
  • Videos
  • Game Experiments
    • Climb
    • Super Shapetoy
    • TurboGarbageTruck
    • 031 - Best Games - Enchanter
    • 033 - Shader Test
  • Contact

404

7/27/2020

0 Comments

 
I sort of want to talk about machine learning and intelligence. 
I spent a bunch of time over the last few weeks messing around with Unity’s machine learning tools. I won’t be putting together any kind of tutorial or forwarding any real actionable info here, because honestly I don’t think I am in any position to offer any. I have a better idea how ML works and what sort of problems it seems to be good at, but I think that there are some very harsh limits to what machine learning is capable of. I also think that there are a lot of people out there who are quick to overlook those limits. There is this commonly held belief that machine learning will be the thing that makes computers smarter than humans. Let me tell you, Skynet, this ain’t. 
If you aren’t familiar, machine learning or neural net computing or tensorflow ai or evolutionary algorithms, or any of a million other names, are ways of getting a computer to solve problems by iteratively teaching itself. Rather than getting a programmer to study the problem and come up with a generalized solution, machine learning is a method of showing the system the problem, giving it a desired goal, or goals, and then leaving the actual problem solving up to the software. It just sort of fumbles forward until it comes up with a solution that gets to the goal in as efficient a way as it can. It might not be the best solution, but it will be fairly efficient and all it will have cost is computer time. 
If they were to read that last paragraph there would, no doubt, be a bunch of machine learning researchers tripping over themselves to tell me what I got wrong. There would also be another gang of researchers behind them eager to point out what the first group got wrong. It seems to be that sort of field. Everyone is pretty sure that it’s great, but none of them really know how it works. When they tell you they know how it works they are usually wrong. What they probably won’t say is that machine learning solutions are ‘smarter’ than humans.
Let me rephrase some of  that. They know how machine learning works, like technically how it functions. Maybe it would be better to say that they disagree on how to make it work. Or how to make it work well. Those are really just nuances. Academic inconsistencies. 
I used machine learning to teach a marble how to not fall off a track. Not how to get anywhere. Not what anything in their environment is. Nope. Just how to not fall. They don’t even avoid the edge of the track very well. They like getting right up beside the edge and not falling off. Many hours of training over a few weeks, and they will try their damndest to not fall off a track. At this point they usually succeed.
I made a machine learning agent reproduce a certain behavior that I was looking for in a variety of situations, but I don’t know thing one about machine learning. I do know this. It’s not smarter than a human. 
The human brain is a massively parallel, analog, electro-chemical, comparative decision making system that never, ever stops running. Sleeping, still running. Chemically unbalanced, still running. Physically compromised, still running. Nothing short of death stops an animal brain from running. What’s more, human societies have developed high density communication systems that transfer information from one individual’s brain to another. These communication systems developed over hundreds of thousands of years. The amount of information conveyed in a simple interaction between people is absolutely staggering, but of course we take it for granted, because we are humans and we are uniquely equipped to be able to decipher that much data presented in that specific way. Tone of voice, cadence of speech, flutters of the eyelids, physical gestures of all types. Communication as dense and varied as there are groups of people to engage in them. Nothing in the realm of machine learning systems even comes close.
A computer beat several top level players at Go. That doesn’t prove that machines are smarter than humans. It proves that humans built a tool. If I use a wrench to turn a nut, that doesn’t mean that the wrench is better than my hand. It means that people have created a tool that solves the problem of enhancing grip and leverage. Wrenches are crap at shuffling cards. I can’t use a wrench to solve a rubik's cube or type this post. It is a tool that enhances human ability. The machine that is good at playing Go is just that. A machine that is good at playing Go, because people wanted to make a tool that was good at playing Go. It can’t tell me if the milk in the back of my fridge has gone bad. That would require a different tool. Maybe machine learning could be used to make it. That would not and will not make that machine smarter than the human who wanted to know about the state of their milk. 
Let me also be clear here, this is not because I think that there is some intangible, fundamental, superiority of humans over the machines they create. Not even close. This is just a matter of time. Human brains run constantly and have run constantly for hundreds of thousands of years. Animal brains for hundreds of millions before that. And those brains don’t run slower than computer circuits, just different. All brains have done for over 500 million years, is figure out how to solve problems. You could throw all the Nvidia GTX cards you want into the machine learning arena, they just can’t compete with that much iteration time.
I think what a lot of folks who tout the idea of a generalized AI that’s smarter than people forget is that people created Go. It was people who created a game with such a wide possibility space that they themselves couldn’t competently calculate it. They created a problem they couldn’t solve and then hammered away on it for a couple thousand years because it was fun. 
This isn’t the sort of species that you just surpass because you built a machine that can do multiplication real good. When it comes to being clever, humans are certifiable badasses. Problem solving, Iteration, intuitive lateral thinking. Really nothing tops us. We’ve just been doing it longer.

​
0 Comments



Leave a Reply.

    Archives

    December 2022
    November 2022
    October 2022
    September 2022
    August 2022
    July 2022
    June 2022
    May 2022
    April 2022
    March 2022
    February 2022
    January 2022
    December 2021
    November 2021
    October 2021
    September 2021
    August 2021
    July 2021
    June 2021
    May 2021
    April 2021
    March 2021
    February 2021
    January 2021
    December 2020
    November 2020
    October 2020
    September 2020
    August 2020
    July 2020
    June 2020
    May 2020
    April 2020
    March 2020
    February 2020
    January 2020
    December 2019
    November 2019
    October 2019
    September 2019
    August 2019
    July 2019
    June 2019
    May 2019
    April 2019
    March 2019
    February 2019
    January 2019
    December 2018
    November 2018
    October 2018
    September 2018
    August 2018
    July 2018
    June 2018
    May 2018
    April 2018
    March 2018
    February 2018
    January 2018
    December 2017
    November 2017
    October 2017
    September 2017
    August 2017
    July 2017
    June 2017
    May 2017
    April 2017
    March 2017
    February 2017
    January 2017
    December 2016
    November 2016
    October 2016
    September 2016
    August 2016
    July 2016
    June 2016
    May 2016
    April 2016
    March 2016
    February 2016
    January 2016
    December 2015
    November 2015
    October 2015
    September 2015
    August 2015
    July 2015
    June 2015
    May 2015
    April 2015
    March 2015
    February 2015
    January 2015
    December 2014
    November 2014
    October 2014
    September 2014
    August 2014
    July 2014
    June 2014
    May 2014
    April 2014
    March 2014
    February 2014
    January 2014
    December 2013
    November 2013
    October 2013
    September 2013
    August 2013
    July 2013
    June 2013
    May 2013
    April 2013
    March 2013
    February 2013
    January 2013
    December 2012
    November 2012
    June 2012
    October 2011
    July 2011
    June 2011
    May 2011
    April 2011
    March 2011
    November 2010
    October 2010
    August 2010
    July 2010
    June 2010
    May 2010
    April 2010

    Categories

    All
    Adventure Caddie
    Best Games

    RSS Feed

Owen McManus
  • Blog
  • Stories
    • Story 000
    • Story 001
    • Story 002
    • Story 004
    • Story 007 - Unfinished
    • Story 008
    • Story 010 - BattleWagon
    • Story 012
  • Images
    • Adventure Caddie concept gallery
    • Page Design Gallery
    • Older Work
  • 5FEAT Video
  • Videos
  • Game Experiments
    • Climb
    • Super Shapetoy
    • TurboGarbageTruck
    • 031 - Best Games - Enchanter
    • 033 - Shader Test
  • Contact