Yes, many streamers on Twitch, and content creators on YouTube have faced such accusations, some of them have been extensively harassed, to the point they even provided evince, medication signed by doctors out of desperation for the harassment to stop, needless to say in some cases it didn't.
In AlphaZero for example, there were 44 million training games total for 700,000 steps of training for the full 9 hours.
Turning that to human-scale numbers, 44million games with on average 60 moves, at 1 second thinking time per move,
> 44000000*60/60/60/24/365 = 83,7138508371 years of training experience in 9 hours
The whole field of Reinforcement learning has agents training and playing games for many orders of magnitude more time than a human ever will. In-fact, we can scale this to over 100k of actions per second, in a single machine:
Then, there is also distributed Reinforcement Learning, where hundreds of agents can play at different machines and share experience, see AlphaZero, LeelaZero, R2D2 agent, R2D3 agent, Apex, Acer, Asynchronous PPO.
> but the data isn't useful without the context of experience
The experience is the data in Reinforcement Learning.
> and all processing power can do it overfit model without experience.
That is wrong, the agents perform what is called exploration to avoid getting stuck in simple strategies.
> Even if we put AI into an army of robots running around and experiencing things, there are still scaling limits to encoding and communicating knowledge and understanding.
True, but machines scale better because they speak the same language, or they can learn to tune their language to get their message across.
> Human organizations are a great example of the scaling limits of intelligence.
Human organization is a testament to how far we can get with something as limiting as the commonly used language. The language that we use to communicate is subject to misinterpretation due to our subjective experiences, this limitation is not shared by machines.
If the universe is a game you are playing, then yes playing that game is "experience", but for an AI to engage with reality it has to have experience in reality, not a game. The ability to play go very well doesn't enable an AGI to better understand reality.
> The experience is the data in Reinforcement Learning.
This is very true, and the critical problem. Data about how reality responds to an AI's actions is very sparse right now.
AIs do have a potential advantage in communications efficiency, but at some level of scale compression will happen, locally "irrelevant" data will be discarded and simplified approximations replace it. None of this will change the "big O" of the scalability of intelligence, just the constant factors. There is no exponential kickoff point.
What is the difference between experiencing reality and a game?
The difference I can see is that there is no one explicit objective function, but this doesn't stop generally capable agents [1], and doesn't imply that inverse RL is not possible.
> The ability to play go very well doesn't enable an AGI to better understand reality.
I disagree, model based RL constructs a model of the agent's reality and can use it to plan ahead, train the agent, or do some form of monte-carlo tree search. The latter is something very similar to how we imagine and think about the future.
I'm in total agreement about the potential of growing AGI out of these methods, but there will be bottlenecks well before the gods of the singularity come knocking.
Are you sure it's the amygdala? IFAIK, and please correct me, we make choices through our amygdala when we are teenagers - hence the impulses - while we use our prefrontal cortex for choices when we become adults.
I am not a native speaker but the repetition of "best X we have ever built" or "best X yet" or "most advanced" and their unimaginative variations took away what could have been one of the best (pun intended) product launches of the year.
The fact that there is still the potential for jailbreaks in iOS surprises me and doesn't seem to help the secure-by-default argument.
Why is a trillion-dollar company which designs their own silicon only two steps ahead of some hackers? Instead of $200 billion in the bank, unspent, shouldn't those devices be reviewed and redesigned until impregnable?
Computing devices are usually insecure due to limits on experience, time and cost. None of those applies to Apple in any meaningful manner.
Personally I'll just stick with cheap Android phones running custom ROMs and treat them as insecure, disposable terminals.
So long there is a hardware input source (usb) it's impossible to guarantee security, this is the reality. There is not a single device with an input source such as USB that is secure. Physical access guarantees lack of security.
Also, it's not some hackers. There's quite a big community out there looking for bugs and every time, such 'hacking' requires unlocked phone.
> Instead of $200 billion in the bank, unspent, shouldn't those devices be reviewed and redesigned until impregnable?
The problem is the Mythical Man-Month. Apple's devices are built on a mountain of ancient C code. XNU is a bizarre Mach/BSD hybrid, built for the sake of expedience. (This is not to bash Apple; most other devices aren't much better.)
Apple has been working to improve the situation, but there's a limit as to how rapidly all those millions of lines of code can be changed.
I remember watching an anime, around 3 or so years ago, called "psychopass". It was about a dystopian country that was governed by technology.
The system would decide what would be the best position for somebody in the government if they desired to go there. It'd also monitor people and evaluate in real time their psyche. People who were predisposed to psychopathic and/or sociopathic behaviour were flagged and monitored. The police would use guns that tranquilized flagged people and disintegrated people deemed public danger.
This article painted China as a predecessor of the country presented in the anime.
As for the ranking / credit system. I don't believe that such an idea is feasible, as it resembles elo. We know from online games such as League of Legends that elo is not an appropriate metric as it's often governed by multiple variables out of the individual player's control. While in the 'long run' it evens out, it often creates the illusion that a player stuck because of their environment and not themselves, which while may be true in a few cases, in most cases is false.
