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Mordhaus (Member Profile)

World’s Largest Optical Lens

newtboy says...

Edison was a well known patent and credit thief.

I find it ridiculously suspicious that he "invented" the phonograph shortly after the invention of the exceptionally similar paleophone. Charles Cros submitted a sealed envelope containing a letter to the Academy of Sciences on April 30, 1877 detailing the design of the paleophone, the first device capable of recording and playing the recording back as sound, later that year an account of his invention was published on October 10, 1877 a month before Edison claimed credit, then Edison patented it the next year..
Suspicious to say the least if you consider how many other inventions he "invented" after someone else had already done so....like the light bulb.

Edison always seemed like the Trump of late 1800's inventors imo, constantly taking credit for other people's work, patenting their inventions without even crediting them, and was a total shady but successful business man thanks to a total lack of ethics.

Wizard of Menlo Park? Please. Just another backstabbing rat from New Jersy if you ask me.

I'm team Tesla all day long. ;-)

BSR said:

Fun Fact: Menlo Park, NJ (not CA)

In November 1877, one of Edison’s first major inventions at Menlo Park was the phonograph, which was a basic machine that allowed a person to speak into a diaphragm that was attached to a pin that made indentations on a paper wrapped around wood. The first words Edison successfully recorded on the phonograph were “Mary had a Little Lamb”. By 1878, this invention was known all around the world and Edison soon earned the title of “The Wizard of Menlo Park.

Dad was a big fan Edison.

Multi-Agent Hide and Seek

L0cky says...

This isn't really true though and greatly understates how amazing this demo, and current AI actually is.

Saying the agents are obeying a set of human defined rules / freedoms / constraints and objective functions would lead one to imagine something more like video game AI.

Typically video game AI works on a set of weighted decisions and actions, where the weights, decisions and actions are defined by the developer; a more complex variation of:

if my health is low, move towards the health pack,
otherwise, move towards the opponent

In this demo, no such rules exist. It's not given any weights (health), rules (if health is low), nor any instructions (move towards health pack). I guess you could apply neural networks to traditional game AI to determine the weights for decision making (which are typically hard coded by the developer); but that would be far less interesting than what's actually happening here.

Instead, the agent is given a set of inputs, a set of available outputs, and a goal.

4 Inputs:
- Position of the agent itself
- Position and type (other agent, box, ramp) of objects within a limited forward facing conical view
- Position (but not type) of objects within a small radius around the agent
- Reward: Whether they are doing a good job or not

Note the agent is given no information about each type of object, or what they mean, or how they behave. You may as well call them A, B, C rather than agent, box, ramp.

3 Outputs:
- Move
- Grab
- Lock

Again, the agent knows nothing about what these mean, only that they can enable and disable each at any time. A good analogy is someone giving you a game controller for a game you've never played. The controller has a stick and two buttons and you figure out what they do by using them. It'd be accurate to call the outputs: stick, A, B rather than move, grab, lock.

Goal:
- Do a good job.

The goal is simply for the reward input to be maximised. A good analogy is saying 'good girl' or giving a treat to a dog that you are training when they do the right thing. It's up to the dog to figure out what it is that they're doing that's good.

The reward is entirely separate from the agent, and agent behaviour can be completely changed just by changing when the reward is given. The demo is about hide and seek, where the agents are rewarded for not being seen / seeing their opponent (and not leaving the play area). The agents also succeeded at other games, where the only difference to the agent was when the reward was given.

It isn't really different from physically building the same play space, dropping some rats in it, and rewarding them with cheese when they are hidden from their opponents - except rats are unlikely to figure out how to maximise their reward in such a 'complex' game.

Given this description of how the AI actually works, the fact they came up with complex strategies like blocking doors, ramp surfing, taking the ramp to stop their opponents from ramp surfing, and just the general cooperation with other agents, without any code describing any of those things - is pretty amazing.

You can find out more about how the agents were trained, and other exercises they performed here:

https://openai.com/blog/emergent-tool-use/

bremnet said:

Another entrant in the incredibly long line of adaptation / adaptive learning / intelligent systems / artificial intelligence demonstrations that aren't. The agents act based on a set of rules / freedoms/constraints prescribed by a human. The agents "learn" based on the objective functions defined by the human. With enough iterations (how many times did the narrator say "millions" in the video) . Sure, it is a good demonstration of how adaptive learning works, but the hype-fog is getting a big thick and sickening folks. This is a very complex optimization problem being solved with impressive and current technologies, but it is certainly not behavioural intelligence.

Center fielder first position player to ever record a save

cloudballoon says...

That's why it's called The USA's National Pass-out...er... I mean Pastime. I jest, I jest!

But hey, I spent my two-minute in this video looking for rats... and I failed to see any... how can this be?!

notarobot said:

"the game took six hours and eighteen minutes"

And here I am having trouble getting through a two-minute highlight reel...

Kid hides from police in Bend

Rat infestation eradicated by mink and dogs

AeroMechanical says...

Yeah, this doesn't seem very practical. The mink in particular I can't see killing enough to make a difference the way they're deploying it. The dogs might, though, if they live on the farm and kill rats all day.

lurgee (Member Profile)

The Mouse Utopia Experiments | Down the Rabbit Hole

The Mouse Utopia Experiments | Down the Rabbit Hole

Snake Attacks Man From Doorway

Payback says...

Ya, just watched the first flight episode again. Drogon chowed down and ripped a Son of the Harpy in two like a terrier with a rat.

Good times.

Holy crap S8 ep 5 made 0 fucking sense. I hate when writers run out of ideas. Awesome effects, but no narrative fucks were given.

Payback said:

I'm pretty sure Drogon munched down on one or two of the slave masters right before Daenarys did her first flight. Hes chewed up a couple kids off camera too iirc.

'Ninja' kangaroo rats kick rattlesnakes in the head fast...

Ninja rat spin kicks a rattlesnake

'Ninja' kangaroo rats kick rattlesnakes in the head fast...

Mordhaus (Member Profile)

Mouse Cleans Up Garden Shed



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