Really cool concept of drumming with your feet while playing another instrument.I think it would be really cool to experiment with different trigger sounds. The muscles in your foot severely limits the nuances available to play, and trying to imitate the sounds of a regular drum-set will not go over well.I think it is possible to achieve much cooler playing, if you skip the idea of your pedals needing to imitate a drum-set entirely. Experiment with some 808 bass, electric kicks, etc.Combining that with your great piano playing would create an entirely new feel of music, whereas it can easily end up sounding like a good pianist struggling to cooperate with a much worse drummer
I spent 5 minutes searching amazon.de for replacements to the various products recommended and my search came up empty.Is there someone who has put together the needed list of bright lighting products on amazon.de? I tried doing it myself and ended up hopelessly confused. What I'm asking for is eg. two desk lamps and corresponding light bulbs that live up to the criteria.I'll pay $50 to the charity of your choice, if I make a purchase based off your list.
And there doesn’t need to be an “overall goodness” of the job that would be anything else than just the combination of those two facts.
There needs to be an "overall goodness" that is exactly equal to the combination of those two facts. I really like the fundamental insight of the post. It's important to recognize that your mind wants to push your perception of the "overall goodness" to the extremes, and that you shouldn't let it do that.If you now had to make a decision on whether to take the job, how would you use this electrifying zap help you make the decision?
I would strongly prefer a Lesswrong that is completely devoid of this.
Half the time it ends up in spiritual vaguery, of which there's already too much on Lesswrong. The other half ends up being toxic male-centric dating advice.
For those who, like me, have the attention span and intelligence of a door hinge the ELI5 edition is:
Outer alignment is trying to find a reward function that is aligned with our values (making it produce good stuff rather than paperclips)
Inner alignment is the act of ensuring our AI actually optimizes the reward function we specify.
An example of poor inner alignment would be us humans in the eyes of evolution. Instead of doing what evolution intended, we use contraceptives so we can have sex without procreation. If evolution had gotten its inner alignment right, we would care as much about spreading our genes as evolution does!
GPT-3's goal is to accurately predict a text sequence. Whether GPT-3 is capable of reason, or whether we can get it to explicitly reason is two different questions.
If I had you read Randall Munroe's book "what if" but tore out one page and asked you to predict what will be written as the answer, there's a few good strategies that come to mind.
One strategy would be to pick random verbs and nouns from previous questions and hope some of them will be relevant for this question as well. This strategy will certainly do better than if you picked your verbs and nouns from a dictionary.
Another, much better strategy, would be to think about the question and actually work out the answer. Your answer will most likely have many verbs and nouns in common, the numbers you supply will certainly be closer than if they were picked at random! The problem is that this requires actual intelligence, whereas the former strategy can be accomplished with very simple pattern matching.
To accurately predict certain sequences of text, you will get better performance if you're actually capable of reasoning. So the best version of GPT, needs to develop intelligence to get the best results.
I think it has, and is using varying degrees of reason to answer any question depending on how likely it thinks the intelligent answer will be to predict the sequence. This why it's difficult to wrangle reason out of GPT-3, it doesn't always think using reason will help it!
Similarly it can be difficult to wrangle intelligent reasoning out of humans, because that isn't what we're optimized to output. Like many critiques I see of GPT-3, I could criticize humans in a similar manner:
"I keep asking them for an intelligent answer to the dollar value of life, but they just keep telling me how all life has infinite value to signal their compassion."
Obviously humans are capable of answering the question, we behave every day as if life has a dollar value, but good luck getting us to explicitly admit that! Our intelligence is optimized towards all manner of things different from explicitly generating a correct answer.
So is GPT-3, and just like most humans debatably are intelligent, so is GPT-3.
I don't get the divestment argument, please help me understand why I'm wrong.
Here's how I understand it:
If Bob offers to pay Alice whatever Evil-Corp™ would have paid in stock dividends in exchange for what Alice would have paid for an Evil-Corp™ stock, Evil-Corp™ has to find another buyer. Since Alice was the buyer willing to pay the most, Evil-Corp™ now loses the difference between what Alice was willing to pay and the next-most willing buyer, Eve, is willing to pay.
Is that understanding correct, or am I missing something crucial?
If my understanding is right, then I don't understand why divestment works.
Lets assume I know Bob is doing this and I have the same risk-profile as Alice. I know the market price to be distorted, Evil-Corp™ stocks are being sold for less than what they're worth! After all, Alice deemed the stock to be worth more than what the stock was sold for. If it was not worth the price Alice was willing to pay for it, she wouldn't have offered to give that price.
Why wouldn't I just buy the stock from Eve offering to pay the price set by Alice?
As Benjamin Graham put it:
in the short run, the market is a voting machine; in the long run, the market a weighing machine.
I think that's a very fair way to put it, yes. One way this becomes very apparent, is that you can have a conversation with a starcraft player while he's playing. It will be clear the player is not paying you his full attention at particularly demanding moments, however.
Novel strategies are thought up inbetween games and refined through dozens of practice games. In the end you have a mental decision tree of how to respond to most situations that could arise. Without having played much chess, I imagine this is how people do chess openers do as well.
I considered using system 1 and 2 analogies, but because of certain resevations I have with the dichotomy, I opted not to. Basically I don't think you can cleanly divide human intelligence into those two catagories.
Ask a starcraft player why they made a certain maneuver and they will for the most part be able to tell you why he did it, despite never having thought the reason out loud until you asked. There is some deep strategical thinking being done at the instinctual level. This intelligence is just as real as system 2 intelligence and should not be dismissed as being merely reflexes.
My central critique is essentially of seeing starcraft 'mechanics' as unintelligent. Every small maneuver has a (most often implicit) reason for being made. Starcraft players are not limited by their physical capabilities nearly as much as they are limited by their ability to think fast enough. If we are interested in something other than what it looks like when someone can think at much higher speeds than humans, we should be picking another game than starcraft.
Before doing the whole EA thing, I played starcraft semi-professionally. I was consistently ranked grandmaster primarily making money from coaching players of all skill levels. I also co-authored a ML paper on starcraft II win prediction.
TL;DR: Alphastar shows us what it will look like when humans are beaten in completely fair fight.
I feel fundamentally confused about a lot of the discussion surrounding alphastar. The entire APM debate feels completely misguided to me and seems to be born out of fundamental misunderstandings of what it means to be good at starcraft.
Being skillful at starcraft, is the ability to compute which set of actions needs to be made and to do so very fast. A low skilled player, has to spend seconds figuring out their next move, whereas a pro player will determine it in milliseconds. This skill takes years to build, through mental caching of game states, so that the right moves become instinct and can be quickly computed without much mental effort.
As you showed clearly in the blogpost, Mana (or any other player) reach a much higher apm by mindlessly tabbing between control groups. You can click predetermined spots on the screen more than fast enough to control individual units.
We are physically capable of playing this fast, yet we do not.
The reason for this, is that in a real game my actions are limited by the speed it takes to figure them out. Likewise if you were to play speedchess against alpha-zero you will get creamed, not because you can't move the pieces fast enough, but because alpha-zero can calculate much better moves much faster than you can.
I am convinced a theoretical AI playing with a mouse and keyboard with the motorcontrols equivalent of a human, would largely be making the same 'inhuman' plays we are seeing currently. Difficulty of input is simply not the bottleneck.
Alphastar can only do its 'inhuman' moves because it's capable of calculating starcraft equations MUCH faster than humans are. Likewise, I can only do 'pro' moves because I'm capable of calculating starcraft equations much faster than an amateur.
You could argue that it's not showcasing the skills we're interested in, as it doesn't need to put the same emphasis on long-term planning and outsmarting its opponent, that equal human players have to. But that will also be the case if you put me against someone who's never played the game.
If what we really care about is proving that it can do long term thinking and planning in a game with a large actionspace and imperfect information, why choose starcraft? Why not select something like Frozen Synapse where the only way to win is to fundamentally understand these concepts?
The entire debate of 'fairness' seems somewhat misguided to me. Even if we found an apm measure that looks fair, I could move the goal post and point out that it makes selections and commands with perfect precision, whereas a human has to do it through a mouse and keyboard. There are moves that are extremely risky to pull off due to the difficulty of precisely clicking things. If we supplied it a virtual mouse to move arround, I could move the goal post again and complain how my eyes cannot take in the entire screen at once.
It's clear alphastar is not a fair fight, yet I think we got a very good look at what the fair fight eventually will look like. Alphastar fundamentally is what superhuman starcraft intelligence looks like (or at least it will be with more training) and it's abusing the exact skillset that make pro players stand out from amateurs in the first place.